China Satellite Navigation Conference (CSNC) 2020 Proceedings: Volume III

At present, China’s BDS-3 basic system has been completed and started to provide global services. However, the accuracy of satellite clock difference seriously restricts the service performance of BDS, and the performance of satellite atomic clock directly determines the accuracy of satellite clock difference. To solve this problem, this paper studies and evaluates the performance of BDS-3 spaceborne atomic clock in detail. Based on the precision satellite clock data of BDS from August to October 2019, using the median method, this paper pre-processed the BDS-2 and BDS-3 data, and obtained the fitting residuals of the spaceborne atomic clock by using the polynomial fitting method. In addition, in the frequency domain, this paper studied and compared the periodic characteristics of spaceborne atomic clock of BDS-3 and BDS-2. The experimental results show that all the clock difference of BDS show significant periodic characteristics, and the main period of BDS satellite clock difference is 12 h and 24 h respectively, corresponding to 0.5 times, 1 times and 2 times of each satellite orbit period. Compared with BDS-2, the main period term of BDS-3 is clearer, more accurate and more stable. In addition, the experiment also shows that the period of satellite clock difference is different in different orbits and in the same orbit the periodic term of satellite clock difference is also different. The period term of BDS-3 is consistent with that of other MEO satellites. Finally, the performance analysis of BDS atomic clock shows that the performance of BDS-3 hydrogen atomic clock is better than that of BDS-2 atomic clock.

When multi-GNSS system data fusion is performed, differences in signal structure and transmitting frequency between different systems can seriously affect the precision orbit determination or positioning performance. In this paper, the unification method of multi-GNSS bias reference is derived, and the ISB /IFB random model is constructed based on the first-order Gaussian Markov process. The observation equation is solved by the virtual observation value, and the multi-GNSS ISB/IFB multi-day and single-day sequences are obtained, analyzed and evaluated. The result of MGEX test data shows that the multi-day ISB/IFB of each GNSS system is very steady but with obvious stratification, and the time series of each satellite in the same system shows good consistency. The dynamic sequence of single-day BDS and Galileo ISB is steady, and the amplitude is basically within 1 ns; the multi-day GLONASS IFB of albh tracking station is between −2 ns and 3 ns, and the STD of single-day GLONASS IFB is within 0.4 ns.

In view of the difficulty in monitoring, evaluating and early warning of multi-channel time-frequency signals, this paper designed and developed a multi-channel time-frequency signal monitoring, evaluating and early warning system based on user datagram protocol. The design about the hardware and software architecture of system are introduced in detail. Considering the needs for practical engineering. This paper focuses on the study of some of key technologies. The working principle, design and implementation methods for multi-channel time-frequency measuring instrument is given. Research on time-frequency signal monitoring and early-warning method based on least squares support vector machine (LSSVM) method. The system has been applied to monitor and evaluate key time-frequency signals of BDS ground station; it was used to provide supporting data for analyzing, locating, handling failures of navigation equipment. System application result demonstrates that the signal monitoring accuracy of system has reached the design goal and achieved the expected function successfully.

The integrity of Beidou Satellite Navigation System (BDS) and its enhancement system is the key index to characterize the safe operation of navigation system and the key point of system performance evaluation. Aiming at the problem that the choice of the distribution model for integrity assessment needs data characteristics of positioning error as basis, this paper is based on the mechanism of positioning error and proposes to using the time series analysis method to analyze the characteristics of positioning error data of the BDS differential positioning from multiple angles of self-correlation, extremity and thick tail. And quantitative validation is also carried out by processing the actual positioning error data. The result shows that the differential positioning error shows the low correlation due to error cancellation which can satisfy the requirement of approximate independence of data for integrity modeling and evaluation. However, the positioning error shows thick tails in both vertical and horizontal directions. Compared with the normal distribution, the thickness tail of horizontal error is slighter, only 22.9% and the thickness tail of vertical error is heavier, reaching 60.7%. Combining the extreme value theory, the block maximum model describing the characteristics of sample thick tail is very suitable for the integrity evaluation of BDS.

Geomagnetic storms are a common natural phenomenon caused by solar activity and other factors, which are closely related to human production activities. In this paper, four ionospheric models during geomagnetic storms (130–136) are analyzed by selecting four stations in the Asia-Pacific region. The results show that during the occurrence of geomagnetic storms, the impact on the middle latitude region is higher than that in the low latitude region. For stations near the same latitude, the variation of VTEC is the same, and the range of variation is roughly the same. The correction rate of BDSK8 model is lower than that of BDGIM, GPSK8, NeQuick in low latitudes. At the same time, BDSK8 is more sensitive to negative phase disturbance of the ionosphere. In mid-latitudes, the correction rate of four models of large magnetic storms occurred in 134 days has a certain decline, the range of decline is about 2%–5%, The NeQuick model has a slightly worse correction effect at middle latitudes during the geomagnetic storms.

Research on pseudo-range dynamic positioning of 11 signals from the four major satellite navigation systems: GPS, BDS, Galileo and GLONASS by using the ship’s dynamic data in South China Sea. The result shows that the root-mean-squares (RMS) of three dimensional (3D) of B3I and B1I signals in BDS are all below 2.2 m, L1 signal in GPS is below 2.4 m, G1 signal in GLONASS is below 7.2 m, E1 signal in Galileo is below 3.2 m. The RMS of positioning error of each signal in GNSS is below 7.9 m.

Starting with Android 7.0, Google has opened APIs for smartphone users to obtain raw GNSS data, including pseudorange, carrier, and Doppler measurements. At present, the research of Android devices positioning based on original observations mostly focuses on GPS/GLONASS/Galielo, and there is few in-depth evaluation work on the data observation quality and positioning performance of BDS. In general, compared with traditional survey-grade GNSS receivers, observations of Android devices are not only affected by high measurement noise and multipath errors, but also by abnormalities such as duty cycle and phase error accumulation. Therefore, to improve the positioning accuracy of Android smartphones, the quality of the measured data and its influencing factors must be analyzed first. This article uses the Hisilicon Hi1103 positioning chip mounted on the HUAWEI Nova5 to evaluate the data quality and positioning performance of the BDS observation in a comprehensive perspective. The carrier-to-noise ratio, duty cycle, and measurement noise of different types of BDS satellites are evaluated and statistically analyzed. In static positioning performance assessment, the accuracy of SPP and PPP using BDS is evaluated using the positioning results of the measurement receiver. While in dynamic positioning performance assessment, because the accuracy of ordinary pseudo-range single point positioning is low, the author use an improved sliding window HATCH filter algorithm, which greatly improves the accuracy of dynamic positioning.

The Japanese Quasi-Zenith Satellite System (QZSS) provides Centimeter-Level Augmentation Service (CLAS) through L6 signal. The L6 augmentation messages includes satellite orbit correction, clock correction, phase bias, code bias, troposphere correction, ionosphere correction and other augmentation messages. These augmentation messages are used for a PPP-RTK service. Using PPP-RTK service, users in Japan can get high-precision real-time positioning results. Based on the measured data of AIRA, STK2, TSK2 and USUD of four MGEX stations in Japan, this paper analyzes the PPP augmentation performance of L6 augmentation signal by post static PPP, and compares it with the calculation results of QZSS final orbit and clock products. The results show that there is still a certain gap between the accuracy of orbit and clock augmented by L6 signal and the final products of QZSS. The static PPP based on L6 signal can realize centimeter-decimeter level positioning, and the positioning accuracy is lower than that of the final products of QZSS. Analysis reason: as CLAS are used to augment PPP-RTK services, PPP augmented service is out of scope of its pre-service. Therefore, the published orbit and clock correction are not a real-time precise orbit and clock correction, which leads to a gap between the corrected orbit and clock and the final products. Similarly, due to different application services, there are differences in positioning results.

Signal power level of GNSS satellites is key parameter for service performance. The relationship between navigation signal power and carrier-to-noise ratio (CNR) of GNSS receiver is described. The time variation characteristics of CNR for one station and satellite pair during 10 days and also characteristics between different stations is analyzed. Results show that the relationship between CNR and elevation angle is consistent and repeatable for a specified signal of one station and satellite pair during that 10 days. Then a model related CNR with elevation angle is established based on global observation data. Using the model, CNR changing trend could be predicted, and so its anomaly could be monitored. For more efficient monitoring, we use a mapping method to transform the CNR at different elevation angles to its corresponding value of 90-degree elevation angle. Finally, data from global tracking network are used to validate the feasibility and reliability of this approach. The results show that there are signal power changes for GPS satellites occurred during April 13th 2018 UTC.

According to the three-step construction plan of BDS, the global signal will cover worldwide by June of 2020. The BDGIM model is innovatively proposed to correct the single frequency ionospheric delay in BDS. As a new model, it is necessary to analyze the performance of BDGIM. Based on the ionosphere data of CODE, this paper compares the performance of BDGIM with that of BDSKlob, GPSKlob and NeQuickG in the aspects of space, time and the effects on single point positioning. The results show that compared with the other ionospheric models, BDGIM model is closest to CODE. Excluding the high latitude area, the BDGIM model is the best among all the single ionospheric models in the other areas. NeQuickG model shows the best performance in high latitude area and become worse in low and mid latitude areas. Compared with the BDSKlob model of BDS-2, the BDGIM model of BDS-3 has been greatly improved. The accuracy of BDGIM model in the Northern hemisphere is better than that in the Southern, and the correction ratio is better than 75% over China and exceed 65% worldwide. Compared with the SPP results of using BDSKlob model, the positioning accuracy based on BDGIM model is improved by 25% and the positioning improvement in high latitude area is more obvious, which almost reached 45%.

BDS-3 has been providing initial service from December 2018. BDS entered the stage of simultaneous service with 2 generations of satellites: BDS-2 and BDS-3. There are three different orbit for BDS satellites including GEO, IGSO and MEO, and 4 open service signals including B1I, B2I, B3I, B1C and B2a. Compared with BDS-2, the on-board payload of the BDS-3 has been redesigned, and the parameters of signals are designed to be better, especially in multipath mitigation. In order to verify the performance of BDS-3 signals in terms of multipath errors, we use data from the “international GNSS Monitoring and Assessment System (iGMAS)” multi-GNSS observation stations to analyze the multipath errors of BDS-2 and BDS-3. The results show that the pseudorange multipath error of BDS-2 has a systematic bias that varies with the elevation angle, and the performance of B3I signals is better than B1I for BDS-2 satellites. While B1I, B3I, B1C, and B2a signals of BDS-3 satellites have pseudorange multipath errors with zero mean characteristic, and BDS-3 B1I, B3I signals multipath error is significantly better than BDS-2. The B3I and B2a signals have better performance than B1I and B1C for BDS-3 satellites.

Low Earth orbit (LEO) satellites have unique advantages in navigation enhancement due to their high signal strength and rapid geometric changes, has become a hot spot in the field of satellite navigation. Firstly, based on the Beidou-3 satellite constellation, this paper designs a low-orbit satellite constellation to enhance navigation in specific areas, and uses the satellite visibility and DOP value of this constellation to analyze the enhancement effect on the Beidou-3 navigation satellite. Then the pseudo-range and carrier observation values of LEO satellites are simulated, and the observation values are used for precise point positioning, further analyzing the enhancement effect on positioning results after adding LEO satellites. The results show that the LEO satellite constellation designed in this paper can significantly improve the constellation configuration of Beidou-3 satellite, and the convergence time of precise positioning calculated based on simulation data has been significantly improved.

In order to evaluate the performance of the onboard atomic clock of BDS-3, mult-GNSS observation of the global distributed iGMAS and IGS/MGEX stations are collected, and the BDS/GPS combined precise orbit determination and clock estimation are conducted. The frequency stability of GPS and BDS-3 onboard atomic clocks is analyzed with the resulting clock products. For GPS satellites, the frequency stabilities evaluated using the achieveclock products are very close to those using the IGS clock products, which shows that the achieved satellite clock products are comparable to IGS clock products in quality. For BDS-3 satellite, the daily frequency stabilities (Allan deviations) of onboard rubidium clock are better than 2.4e−14. Except for C34 and C35, the daily frequency stabilities of onboard hydrogen clock are 3.8e−15–6.0e−15, which are very close to those of the clocks of GPS BLOCK IIF satellites.

High precision positioning based on mobile terminals has an important impact on current mapping surveys, intelligent transportation, smart cities, disaster emergency response, public safety and other fields. In 2016, Google released the Android 7.0 operating system, low-cost mobile platforms began to support GNSS raw observation output, from then on, high precision positioning based on Android intelligent devices became possible. However, multi-path effect and antenna phase center error have great influence when using GNSS module built-in in intelligent equipment for positioning, which cannot meet the needs of high-precision mapping tasks. This article gives an assessment of the positioning accuracy based on two smartphones, one is the Huawei P10 with single-frequency GNSS module, the other is the Xiaomi 8 with dual-frequency GNSS module. These tests were done in both kinematic and stationary modes. Besides these two smartphones, a geodetic GNSS dual-frequency receiver was also used for reference. The GNSS measurements were processed using a post differential strategy. The horizontal positioning accuracy obtained with the Huawei P10 was about 50 cm, and with the Xiaomi 8 it was about 10 cm, with respect to the Novatel GNSS dual-frequency receiver solution. The Xiaomi 8 gave a 10–30 cm accuracy level in stationary positioning test. It shows that the positioning accuracy of the GNSS module based on intelligent equipment can reach a good level, which means that it has potential to be use in less demanding topographic surveys and also in other fields like pipeline and urban surveys, GIS, intelligent transportation, among others, in which the positioning accuracy is not so demanding.

By establishing laser crosslinks with high-speed data transmission capability between satellites, the space communication network can achieve the goal of global seamless communication with only a few satellites. In order to adapt to the IP over CCSDS protocols for space communication network, the network consists of satellites should apply packet switching architecture. However, the speed of routing and forwarding is still very low in the space network due to the limited computing resources of satellite. In this paper, a packet switching scheme based on improved (Multi-protocol Label Switching, MPLS) is proposed for general satellites. By using routing protocol and signaling protocol, the constellation of satellites can realize the function of automatic packet switching, therefore the pressure of management and control on the ground operation system can be greatly reduced.

In this paper, a test method based on signal transponder was proposed to realize dynamic performance test and evaluation of high precision GNSS receiver, especially for the integrated receiver which was used in high-precision differential measurement under actual working conditions. In the method, a transponder was used to transmit navigation satellite signal into vehicular microwave anechoic chamber. The same satellite signal was simultaneously received by the tested receiver and the reference device installed in the chamber, which ensured that the observed position was equivalent to the same reference position, eventually the relative stability problem of comparison tests was solved. The test platform was constructed on the moving platform: the interior of the vehicle-type square cabin was installed with absorbing materials, and the vehicular microwave anechoic chamber was built to form an ideal signal transmitting condition. Several experiments were carried out on the platform to test the receiver’s differential measurement accuracy and velocity measurement accuracy under dynamic conditions. Test results fully verified the feasibility of the proposed method. This method could effectively test the performance of the high-precision receiver under the actual working condition, and provide an effective solution for dynamic performance test and evaluation of the receiver.

BDS ground test verification bed (GTVB) covers the three major levels of signal, information, and service of the BDS engineering project. It reproduces the interface and business relationship between the BDS space segment, the ground segment, and the user segment, verifies the main technical system, Simulate the operation management and service capabilities of the entire BDS. System integration and testing are organically combined at the physical level, signal level, and information level, enabling the system to work together, and comprehensively verifying and evaluating the system functions and performance, verifying whether the system meets the design requirements for the project, and providing a basis for project construction acceptance.This article introduces a cross-layer analysis method. This article introduces a cross-layer analysis method. It adopts the integration test principle of “cross-layer functional analysis, function and process integration, step-by-step implementation integration, and integration of integration and testing.” and organically combines the various sub-systems through RF links and communication networks. And complete the integration and testing of the entire system incrementally. Taking BDS satellite orbit determination accuracy test as an example, the analysis of the relationship between the system index and the sub-system test index is helpful for the fault separation and identification. The results show that the system-to-subsystem fault location and identification effect is good.

The simulation of the random characteristics about short message burst signals is an important method to test the receiving performance, while the key is to find the random model of burst signals. This paper proposes a probability model of short burst signals based on the Poisson distribution by using the theorem of the binomial distribution to approximate the Poisson distribution, which can simulate the stochastic process of the signals entering the system. Based on the signals occupying system processing time obeys the negative exponential distribution, the M/M/n/n queuing model is constructed through the above probability model combined with the first-come-first-served principle of the simulation channels, which can analyze the system simulation performance for a given call loss rate. The Monte-Carlo method is used to simulate the signals inbound time and the channel processing time, which can reach the same conclusions as the theoretical analyses under the condition that the call loss rate of the general communication system is 0.5%. Thus, using Poisson distribution to model the short message inbound signals can realize the simulation of its random characteristics, which can provide the environment to test receiving performance for short message burst signals.

With the accomplishment of the BDS3 basic system on December 27, 2018 and its beginning to provide initial services, the performance of BDS3 on-orbit new hydrogen and rubidium atomic clock which is an important factor affecting its positioning and timing performance is needed to be evaluated urgently. Based on the precise clock products issued by Wuhan University, the noise level, frequency accuracy, frequency drift rate and frequency stability of BDS3 satellite hydrogen and rubidium atomic clock are evaluated and analyzed, and the comparison with the performance of BDS2 satellite atomic clock is also done. The experimental results show that the noise levels of hydrogen clock and rubidium clock are 0.157 ns and 0.178 ns, respectively, which are very close but better that those of BDS2 satellite (0.478 ns). BDS3 rubidium clock is greatly affected by frequency drift, with its daily frequency drift rate up to 10−13. While hydrogen clock is less affected by frequency drift, and its daily frequency drift rate is in the order of 10−14. The frequency accuracy level of both hydrogen and rubidium clock is better than the order of 10−11, and some satellites can reach the order of 10−12. The frequency stability of BDS3 rubidium clock is worse than that of hydrogen clock, but still greatly improved compared with that of BDS2 atomic clock. The mean values of frequency stability at thousand second, ten thousand second and one day of hydrogen clock are 3.85 × 10−14, 2.58 × 10−14 and 8.8 × 10−15, respectively, while the values of rubidium clock are 3.96 × 10−14, 2.65 × 10−14 and 1.40 × 10−14, respectively. The short-term stability (less than ten thousand seconds) of the two kinds of atomic clocks is similar, but the stability of hydrogen clock at one day is better than rubidium clock.

Satellite navigation system concerns the national economy and people’s livelihood. Especially, the applications of high-precision GNSS have an increasingly important impact on people’s daily life. High-precision GNSS devices not only provide higher measurement accuracy of satellite navigation signals, but also need to support differential correction, precision ephemeris, and high-precision processing algorithms. That means that high-precision GNSS applications face with higher technical threshold, compared with mass consumer applications. For the high-precision applications, broadband RF chip is an important part of high-precision OEM board, which determines the performance of high-precision OEM board.

Multi-constellation integrated navigation receiver will increase the number of visible satellites and improve positioning accuracy of the receiver. If all-in-view satellites are used for receiver positioning, the computational burden of the receiver will be increased. The traditional satellite selection algorithm is traversal algorithm; however, as the number of visible satellites increases, the traversal algorithm exists huge computation. In order to the problem, the improved particle swarm optimization (PSO) is given for satellite selection, in the proposed algorithm, each satellite subset is considered a particle without mass in search space, and the selected objective function is the geometric dilution of precision (GDOP). Particles update their position based on the proposed algorithm model. Moreover, the optimal satellite subset and the corresponding GDOP value are obtained. The performance of the algorithms is compared based on real navigation data. The simulation results show that proposed algorithm can improve satellite selection speed, and the satellite selection accuracy is better than that of the basic PSO satellite selection algorithm.

Navigation signal based on compound carrier (NSCC), as a novel signal scheme for navigation augmentation, has flexible multi-carrier structure and various scheme parameters, which enable it to possess significant efficiency of navigation augmentation, and also provide auxiliary information for signal synchronism algorithm design. This paper, based on NSCC structure and its parameter configuration, proposed a fine acquisition algorithm combining Quinn interpolation estimator and Zoom-FFT analyzer for NSCC with wideband but sparse signal construction. The Quinn estimator improved rough frequency estimation form the full-length FFT analyzer and located sensitive frequencies for sub-carriers for Zoom-FFT analyzer. Then, the Zoom-FFT analyzer provided high frequency resolution with no obvious computation addition and achieved high-accuracy frequency estimations for fine acquisition by zooming pre-determined frequency range of interest and refining related spectrum. Both the theory analysis and simulation results illustrate that the proposed algorithm can greatly suppress the fence effect and enhance estimation accuracy for fine acquisition with low computation cost and implementation simplicity.

Global Navigation Satellite Systems (GNSS) signals provide worldwide coverage and were originally designed to offer passive navigation. However the use of GNSS signals for remote sensing applications has captured the interest of the scientific community in the last decades. Usually, the GNSS-R signals are processed into Delay-Doppler map (DDM), a representation of the power of the correlation of the received signal with a local replica GNSS signal for a range of code delay and Doppler shift values. This is the same procedure used for the direct signal acquisition. Since the power of reflected GNSS signals are very low, a long integration time is needed to obtain better observation quality. As the integration time extended, the code frequency error of the local replica signal and the reflected signal cannot be ignored. In this work we present a method that aims to perform precise DDM generation through signal processing using modified Double Block Zero Padding (DBZP) circular correlation algorithm and code phase drift pre-compensation method. This method effectively suppresses the loss due to code phase miss-matching especially in long time integration and high code frequency circumstance. Analysis shows that the computational burden of the proposed algorithm is 1/9.11 the one of the traditional circular correlation method. Experiments show that the on-board GNSS-R receiver could perform real-time DDM processing for BDS B1I and GPS L1C/A signal. The signal processing accuracy satisfies the requirement of wind field retrieving process. This signal processing system effectively supports the development of China’s first GNSS-R sea surface wind field monitoring satellite system.

Aiming at the current situation of sifting pure frequency-modulated (FM) signal of ensemble local mean decomposition (ELMD) using hard threshold criterion, this paper proposes an improved ELMD method based on the adaptive sifting stopping criterion. The improved ELMD combined with the consecutive mean square error (CMSE) criterion, which is named as the adaptive local mean decomposition (ALMD), is used to separate the noise signal and extract the useful signal and applied to the research of GPS multipath effects. The results of numerical simulation show that compared with the traditional LMD using the hard threshold criterion and wavelet de-noising method, the de-noising method proposed in this paper is better and more stable. The usage of the proposed method, which aims to extract the multipath correction model from the coordinate residual time series, can weaken the influence of multipath effects to a certain extent, thus improve GPS positioning accuracy.

Multipath error is the main source of error affecting the accuracy of modern satellite navigation receivers. The MEDLL algorithm can effectively reduce the multi-path error by estimating the multipath parameters and is an effective multipath elimination technique in the baseband signal processing stage. However, in the scenario where the number of multipaths is large or the change is fast, the parameters cannot be fully estimated. The result is a large multipath residual, which in turn affects the multipath resistance. Carrier phase smoothing pseudorange (Hatch filtering) has good effect on improving the statistical characteristics of pseudorange and further eliminating multipath error. It is a commonly used pseudorange preprocessing method for measurement receivers and various differential enhancement systems, but its performance is very dependent. The choice of smoothing time. In this paper, a joint algorithm is proposed to estimate the multi-path in the MEDLL loop to control the smoothing time of Hatch. The algorithm is based on carrier phase tracking error and multipath error constraint. Compared with traditional fixed smoothing time Hatch filtering in multipath interference. When the residual is large, the effect is better, and at the same time, the defect of insufficient multipath elimination of the MEDLL algorithm in some scenarios is compensated, so that the multipath elimination in different stages of the receiver is more sufficient and effective.

The advantage of GNSS vector tracking (VT) has been thoroughly analyzed. Different from scalar tracking in which each channel works independently, vector tracking combines all channels through a Kalman filter and drives all numerically controlled oscillators (NCO) simultaneously. This feature enables vector tracking based receiver to be more robust against signal interference and blockage. Most current studies have already tested the performance of vector tracking on post processing software receivers. For the purpose of improving the applicability of vector tracking in real-world situation, this paper presents a scheme of vector delay lock loop (VDLL) based real time scalar-vector tracking receiver. The proposed receiver has the ability to switch into vector tracking from scalar tracking swiftly as soon as the signal loss is detected. An extended Kalman filter (EKF) is used to calculate navigation solution. In this paper the theory of vector tracking is first reviewed briefly. Then the system architecture of developed receiver is described in detail. Finally, in the experiment section an analog front end was used to collect live BDS signal, and static position experiment was conducted to verify the superiority of scalar-vector tracking to conventional scalar tracking in the scenario with signal blockage. Results show that the developed real time scalar-vector tracking receiver is able to obtain correct navigation solution constantly during signal loss while scalar receiver cannot. In conclusion, the superiority of vector tracking loop to conventional scalar tracking loop in the environment with signal blockage is verified.

Since its version 7.0, Android has opened the access interface of GNSS original observed quantity, which has provided a data base for mobile phones to achieve high-precision positioning. The key technologies of mobile phone positioning mainly include wireless performance optimization of antenna, high-precision navigation and positioning algorithm for mobile phone, and high-precision positioning implementation scheme based on Android operating system. This paper first gives an analysis on the current situation of the market and research of high-precision positioning based on mobile phones, then expound on how to make breakthrough in several key technologies, and briefly analyzes the future development trend in the end.

Code Shift Keying (CSK) modulation type can obtain a high information transmission rate while maintaining the correlation characteristics of the spread spectrum signal, and has been attracting attention in the field of satellite navigation in recent years. Different from the conventional Direct Sequence Spread Spectrum (DSSS) method, demodulating CSK modulation data requires external time synchronization information. For this reason, the receiver can obtain the corresponding synchronization information from the pilot signal of the same frequency, or obtain the frequency and symbol synchronization information from the received signals of other frequencies of the same satellite to assist in demodulating the CSK modulation data when there is no pilot signal of the same frequency. In this paper, a signal receiving method is proposed, which can reduce the threshold of CSK signal data demodulation, aiming at one data signal which is modulated by BPSK DSSS and another modulated by CSK DSSS, both of them share the same carrier and have orthogonal phase. Namely, the dual auxiliary signal receiving method obtains the corresponding Doppler frequency offset information from the pilot signals of other frequencies of the same satellite to assist in tracking the BPSK DSSS data signal of the same frequency point as CSK signal, obtain the symbol synchronization information, and then assist in demodulating the CSK modulation data. Compared with the single auxiliary signal receiving method which only relies on BPSK signal of orthogonal multiplexing at the same frequency to demodulate CSK data with coherent demodulation or demodulate CSK data with non-coherent demodulation assisted by pilot signals at other frequencies, this method has better signal tracking robustness and lower data demodulation threshold. The method proposed in this paper combines cross-frequency pilot signal assistance and co-frequency signal coherent assistance, which can not only assist the coherent demodulation of CSK signal, but also assist non-coherent demodulation of CSK signal, and has better adaptability to complex environments. The theoretical calculation results show that the threshold of CSK signal demodulation can be reduced by about 3 dB by using the dual auxiliary signal receiving method proposed in this paper.

Using real-time broadcast ephemeris to calculate satellite orbit information and clock parameters is an important calculation work in GNSS terminal positioning solution. Considering the development trend of GNSS terminal’s low power consumption and Soc, the application and implementation of satellite orbit interpolation algorithm in GNSS receiver are analyzed. From the aspects of computing efficiency, application strategy and continuity, the performance of interpolation algorithm in GNSS real-time operation is analyzed. An implementation of GNSS satellite orbit interpolation algorithm is given to meet the needs of GNSS high frequency sub-location applications. The calculation results show that the method can fit the position and velocity parameter information of GNSS satellites orbit operation in real time. The satellite position accuracy is better than 1e-4 m and the velocity accuracy is better than 1e-3 m/s. It basically meets the requirements of high-frequency real-time calculation of GNSS receivers, and continuity.

The multipath fading independency between different Global Navigation Satellite System (GNSS) frequency bands and space-separated antennas can be used to improve robustness of high-precision GNSS receivers in harsh urban environments. This research focuses on a new sensitive and robust fading monitoring architecture for GNSS diversity branches, and implementation of the method on an Adaptive Diversity reception-based Tracking Loop (ADTL). Firstly, fluctuations in the amplitude and phase of multipath fading signals are characterized. Performance of different design parameters in the fading monitoring method is analyzed in details. Next, diversity combining strategies including the non-linear Selective Combining (SC) and the Maximum-Ratio Combining (MRC) are utilized in ADTL for different fading conditions. Experimental results with Monte-Carlo simulation and real GNSS fading signals demonstrated that: (1) the proposed novel method can achieve robust and sensitive fading monitoring with response delay less than 20 ms; (2) Compared with traditional Phase Lock Loops (PLLs), the ADTL algorithm significantly reduced the navigation bit error rate due to half-cycle sudden-phase change caused by phase losing of lock.

Due to the non-ideal characteristics of antennas and radio frequency (RF) channels, the adaptive array antenna can resist interference but meanwhile introduces biases to the carrier phase measurements in the receiver, resulting in the failure of meeting the requirements of the high-precision positioning. This paper proposed a processing scheme for the anti-jamming high-precision receivers with array antennas based on the adaptive beamforming algorithm. After equalizing RF channels, we can obtain the amplitude and phase patterns of each antenna element, measured by the real satellite signals, and then generate the calibrated steering vectors with the aids of the satellite signal directions and the relative positions among the antennas. Finally, the received signals are processed with the adaptive beamforming algorithm based on the calibrated steering vectors. The experiments based on the real satellite signals proved that the proposed scheme could provide continuous, stable and unbiased carrier phase measurements even with the existence of interference.

Focused on the independence and precision requirements for vehicle navigation, an integrated navigation scheme with geomagnetic matching (GM) and dead reckoning (DR) was proposed. The reference magnetic map was constructed which included magnetic intensities, coordinates of the reference points and road sections information. Then, a zero-mean correlation coefficient method was utilized to match the measured magnetic intensities with the magnetic map, and thereby to estimate the vehicle position. The positioning results from GM and DR were fused by a designed EKF to correct the heading and mileage errors of DR. Furthermore, the corrected DR results could effectively reduce the matching search range and solve the discontinuity of GM results at road intersections. Vehicle experiments showed that the proposed scheme can provide accurate and continuous positioning results and meet the demands of vehicle navigation well.

WIFI signal is met with an extensive application in the context of indoor wireless positioning. Nonetheless, the major challenge confronting indoor positioning systems based on ranging is the interference caused by multi-path and non-line-of-sight environments under the indoor context. Owning to the limitations on bandwidth and multipath resolution, it’s difficult for commercial WIFI devices to be effective in identifying LOS/NLOS scenarios. The application and expansion of the IEEE 802.11n protocol makes it much easier for commercial WIFI devices to obtain spatial information of subcarriers and MIMO systems. The channel state information of Space-Frequency domain is applied in this paper to establish the joint distribution of WIFI signal arrival angle and flight time, and extracts features from its estimated clustering results to complete non-line-of-sight identification. The results from conducting experiment indicate that the proposed method exhibits an excellent detection rate and robustness to LOS and NLOS environments in static scenarios.

In November 2016, China launched its first X-ray pulsar navigation satellite (XPNAV-1), in order to study the feasibility of using the regularly emitted X-ray signals from pulsars for spacecraft navigation. Over the past two years, a large amount of observations have been obtained by the XPNAV-1 satellites. The Crab pulsar (i.e. PSR0531+21) is its main observational source in which 3506627 s observations are made in 1251 orbits during 451 days. In order to study the X-ray pulsar observation performance of XPNAV-1 satellite in the past two years, those observations of Crab pulsar are processed fully. Each recovered pulse profile from daily observation have a mean similarity of 90.67% with the standard profile to be obtained from Rossi X-ray Timing Explorer (RXTE) satellite. The estimated pulse periods of Observation data of approximate to 3000 s is generally consistent with timing model of Fermi satellite and Crab ephemeris of Jodrell Bank Observatory (the mean errors of those two models are less than 10 ns). The observational results show that the pulsar data has been correctly received by the satellite, which is in good agreement with RXTE satellite and Jodrell Bank Observatory. Moreover, it is found that the X-ray detector on XPNAV-1 satellite has maintained a good technical status.

The completion of the BeiDou navigation satellite system has promoted the pace of informatization construction and promoted the development of satellite navigation industry, basically satisfying the needs of users in China for positioning and navigation and timing (PNT) services. However, the service performance of global satellite navigation systems (GNSS) is seriously degraded or even unable to work in environments such as blocking and strong interference. Therefore, it is urgent to further enhance the capabilities of the BeiDou satellite navigation system, as well as to coordinate other types of PNT methods, and introduce new technologies, new systems and new methods so as to establish the BeiDou integrated PNT system. Based on the BeiDou integrated PNT system, the development trend of Beidou PNT application services was discussed, application service architecture is designed and researched, the suggestions for key development focus of application services is given out, with a view to contributing ideas and suggestions for the demonstration, construction, application, and service of Beidou integrated PNT system and for the development of Beidou integrated PNT application service industry and its coordinated development with high-tech, and lay the theoretical foundation for socio-economic structural transformation and upgrading.

When underwater vehicles and underwater robots are used for underwater tasks such as resource sampling, environmental exploration and wreck salvage, the positioning system is capable of reflecting the location information in a timely and accurate manner. Traditional underwater navigation and positioning is based on inertial navigation, assisted by surface satellite signals to achieve positioning information feedback, which requires frequent surface alignment, which increases the safety risk of underwater vehicle and reduces work efficiency. By setting up an underwater beacon array, establishing high-precision marine surveying datum, and utilizing the principle of underwater acoustic positioning, the precise navigation and positioning of underwater vehicle can be realized. This makes up for the deficiency of inertial navigation systems and improves the safety and working efficiency of underwater vehicle. In this research, a set of underwater stereo high-precision positioning system was built by integrating technologies including beacon transponder reference position calibration, sound ray bending ranging error correction, the high-precision positioning of long baseline underwater vehicles. The system built was tested in the Yangtze River with semi-physical simulation experiment. Feasibility and efficiency of the proposed methodology related to underwater navigation beacon array was successfully validated.

High-precision wireless localization has attractive application prospects. Cooperative localization is an effective tool to improve localization accuracy. However, compared with non-cooperative localization, in cooperative localization networks, large-scale neighboring links and nonlinear measurement functions cause the associated objective function to be non-convex. It is difficult to obtain global optimum using classical particle swarm optimization (PSO) algorithm or analytical methods. In order to solve this problem, a classified particle swarm optimization (CPSO) algorithm is proposed in this paper. For classical PSO, all search particles have the same inertial weight and learning factor. Unlike classical PSO, the proposed CPSO algorithm classified different search particles based on particle cost value and set different inertial weights and learning factors for search particles. Meanwhile, considering the unavoidable reference node location error, localization result could be achieved by calculating the weighted average of close-range particle locations. Simulation results prove that the CPSO algorithm improves positioning accuracy by 25.3% compared with classical PSO algorithm.

Traditional swarm robots mainly rely on a single GPS for positioning. Complex environment or the failure of the GPS receiver may cause some robots cannot be located because their GPS signals lose, so cooperative positioning of swarm robots is required. Due to the heavy information transmission task of the centralized algorithm, the positioning accuracy will decrease, and the robustness of the entire network will be reduced. Therefore, A distributed collaborative positioning algorithm based on UWB ranging is proposed. In the case of GPS loss of some robots, it uses centroid coordinates to represent the position relationship between known nodes and unknown nodes based on the GPS observation information of other robots and UWB ranging information between neighboring robots and performs distributed iterative estimation of the position of each robot, achieves the position of swarm robots. Compared with centralized algorithms, the positioning accuracy of the system is improved. The convergence of the algorithm is proved and the simulations show that compared with the traditional MDS algorithm, the proposed algorithm improves the positioning accuracy by 13.31%.

In the complex environment of the city, the visible Beidou satellites are distributed along the road in a strip, which causes a significant decline in positioning performance. The high-density deployment of 5G systems provides an opportunity to improve the geometric distribution of satellites. However, due to the difference in the noise of the pseudo-range measurement between systems, there exists a large positioning error in the traditional solution to the least squares. As a result, this paper introduces the elevation prior determination weight and Helmert variance component estimation model to assign weights to Beidou and 5G systems to improve joint positioning accuracy. The simulation results show that compared to the equal weight model, the PDOP value is reduced by 11.76%, the circular probability error is reduced by 6.8%, and the positioning errors in the three directions of East North Down are reduced by 0.8%, 36.6% and 4.6% respectively. At the same time, the positioning stability has been improved.

In complex indoor environments, the non-line-of-sight (NLOS) error severely affects the accuracy and reliability of the position estimation. The combined Chan/Newton method uses Chan algorithm to estimate the initial value, then searches for the position accurately by Newton’s method. However, in the environment with many NLOS base stations, the accuracy and convergence of the positioning algorithm will decrease sharply. This paper proposes an improved Chan/Newton combined position estimate algorithm. Firstly, we take weighting method based on minimum residual principle for Chan’s position estimate values produced by different base stations combination, the results of which are utilized in our improved Newton’s method as initial values. Next, an amendment factor to modify the range measurement and a damping factor are adopted for constructing accurate objective function and stabling iteration convergence respectively. Finally, weighting the initial values and iteration results to obtain the final location information. Experimental evaluations show that the proposed algorithm has a better performance in terms of location accuracy and convergence in NLOS conditions.

A vehicle GNSS navigation device may provide inaccurate position results or even fail to work in urban environments when the GNSS signals are blocked or reflected by tree canopies or buildings. To achieve more reliable and continuous vehicle navigation solution, this paper proposes a multi-sensor navigation system based on a consumer-grade MEMS IMU, fused with a GNSS receiver, an odometer and a barometer. An IMU error model is constructed in this integrated system to estimate and compensate for the errors of the gyros and accelerometers in motion because without any aided sensors, the accuracy of a consumer-grade MEMS-IMU would degrade fast due to its large bias and noise. Meanwhile, the vehicle motion state is detected to further aid the navigation system to ensure the system can continue to work even in the absence of GNSS or odometer. In addition, a plug-and-play multi-sensor fusion filter derived from Kalman filter framework is designed to ensure that the system operates normally when the available sensors switch over due to the vehicle’s moving through different scenarios. The filter employs UD decomposition to update the measurement so as to achieve real time positioning even on a low cost MCU processor. The proposed multi-sensor integrated system is implemented based on navigation chip of Allystar Technology Co. The fields result shows that, under challenging urban canyon environments, the developed integrated system can achieve continuous, stable and reliable positioning, and in particular during GNSS outage, the positioning accuracy can maintain an error within 1% of the traveled distance without fusing odometer while within 0.5% when odometer is deployed. With the aiding of a barometer, the elevation positioning accuracy can be maintained at about 2 m.

Due to the limitations of the Global Satellite Navigation System (GNSS), its performance in the harsh environment will be limited or even completely rejected. As a new method to enhance GNSS performance, cooperative localization based on inter-node measurements has attracted extensive attention in recent years. However, the positioning accuracy and network performance are always in the state of “Shift from one to other”. The main work is to extract four characteristics of cooperative localization network, design and optimize the multiple access strategy based on time division, which makes it possible for all nodes to perceive the topology of the whole network. Finally, the proposed method is verified by simulation, and the results show the feasibility of the proposed method. This method effectively reduces the amount of measurement frames and prolongs the lifetime of the network. At the same time, the MAC delay is reduced and the positioning frequency is improved.

As a marine environmental parameter, sound velocity has an important impact on sound propagation in the ocean. In the same sea area, the sound velocity profile (SVP) changes dynamically due to the influence of marine environment, season change and other factors. To accurately obtain the SVP of seawater in time is of great significance to improve the positioning accuracy of underwater acoustic equipment for marine research and development. As the main data source of physical oceanography research, Argo data has abundant ocean hydrological observations, which provides scientific reference basis for studying ocean temperature, salt, pressure structure and spatio-temporal variation of hydrological elements. Aiming at the problem that the SVP can’t be accurately obtained in time, this paper proposes a method of SVP inversion and prediction based on radial basis function (RBF) neural network. The method is based on the nonlinear function approximation capability of neural network, by using the measured temperature, salinity of the sea area and Argo data to build the sound velocity profile prediction model. The proposed SVP prediction method was verified with the Argo data of the Atlantic Ocean from 2004 to 2018. The results show that the prediction profiles based on neural network is closer to the actual SVPs that those of the average sound velocity method. Compared with error back propagation (BP) neural network, RBF neural network has the same accuracy and higher efficiency. Therefore, the SVP prediction method based on RBF neural network is more suitable for real-time or near real-time prediction of marine SVP.

With the improvement of location technology, the demand for location-based application services grows. The commonly used global navigation satellite system has a poor performance in the center of the city with dense buildings, the interior of buildings and other similar places. WLAN positioning has become a very convenient solution for indoor positioning since it does not need additional positioning equipment. The key to build and optimize the location fingerprint database is to select the appropriate APs. Current AP selection algorithms usually ignore the fact that the wireless transmission environment is very complex leading the signal strength of AP time-varying characteristics; and because of the low-delay requirements of indoor positioning, the traditional algorithms for network access with high complexity are not suitable for AP selection scene. To solve those problems, firstly we analyzed the upper bound of AP selection performance from the perspective of information theory, its mathematical expression is also been given; Then we proposed a novel AP selection model for fingerprint location, which considering both the time-varying signal and complexity cost. From the experimental results, positioning accuracy using the AP selection algorithm model proposed in this paper has been improved by 47% compared with the traditional AHP algorithm.

In the face of discontinuous GNSS signal and INS error accumulation in complex urban environment, the research on multi-source information fusion positioning method assisted by high-precision map is essential. In order to meet the real-time, continuous and reliable positioning requirements of vehicle navigation, this paper presents the principle and method of constructing high-precision map with stereo vision, and introduces the key technologies of map generation and data cleaning. Meanwhile, it analyzes the performance of the map-aided visual-inertial fusion positioning method. Firstly, the visual point cloud map is constructed based on mobile surveying. The local coordinates of road marking points are obtained by the front intersection of common-view pictures, then the camera pose solved from GNSS/SINS converted road marking points from local coordinate system to ECEF. However, the quantity of road marking points is large, and the absolute precision is difficult to evaluate. Therefore, this paper gives the quality indexes of evaluating point cloud map precision and data cleaning method. By using the method of deep learning to target recognition and semantic segmentation, only the long-term static stable road markings can be maintained in the map. In the meantime, a visual positioning method based on Octomap and DBOW acceleration is proposed. The KITTI dataset test shows that point cloud map is constructed and an average data cleaning rate is 35.05%, that many error observations are excluded. When it comes to positioning, the accuracy of visual/GNSS/INS integrated positioning yields about 2 cm and 0.06°. When integrated with INS, a positioning accuracy of 10 cm can be maintained with only one road landmark matched successfully in the case of GNSS long time (20 min) unlock.

To realize robust high-precision positioning in outdoor diverse environments, the prevailing solution is to integrate multiple complementary sensors like GNSS RTK, INS and LiDAR. In the cases where there is no prior LiDAR map, the global accuracies of fusion positioning and mapping depend on the only global positioning technology, RTK, whose cm-level fix result availability, however, plunges greatly in GNSS-Difficult areas. To improve RTK performance, we propose a new RTK/INS/LiDAR fusion positioning algorithm base on LiDAR features in ambiguity domain, in which we tightly integrate the measurements of the repeated-observed LiDAR features with the ones of RTK. Both theoretical analysis and simulation experiment results prove that the addressed method can provide a higher RTK fix rate to maintain the global accuracy and stability of the fusion positioning in GNSS-Difficult areas.

Global Navigation Satellite System (GNSS) has been widely used in people’s life. Generally, GNSS signals suffer from severe attenuation in urban canyon environments. the 5th generation wireless systems (5G) and GNSS hybrid positioning technique is a promising localization technique because 5G base stations are able to help GNSS relieve the problem of lacking visible satellites in urban environments. However, 5G-GNSS hybrid positioning faces the time synchronization problem. The conventional methods based on time of arrival (TOA) or time difference of arrival (TDOA) require that the time synchronization accuracy between two base stations should at least be 30-nanosecond level to make sure the range error is below 10 m, which is difficult to achieve in real applications. This work proposes a 5G-GNSS hybrid positioning scheme basing on AOA-TOA measurements. We combine the angle of arrival (AOA) estimates from 5G base stations and TOA measurements from GNSS satellites to perform hybrid localization. Moving averaging operation is then performed on the raw position estimates to further reduce the effect of noise. The principle of the proposed algorithm is explained detailedly. Numerical results demonstrate that the proposed method can be free from the influence of the time synchronization error, thus it improves the accuracy and robustness of hybrid positioning system in comparison with conventional methods.

As an important supplement and backup to the Global Navigation Satellite System (GNSS), the ground-based positioning system is desirable for low cost and high flexibility. In GNSS denied environments, the spatial reference cannot be determined via GNSS services. A large number of systems obtain the coordinates of base stations by artificial measurement, but this can be limited by terrain or other conditions and is difficult to achieve rapid deployment. The spatial reference establishment methods affect its deployment flexibility, while the accuracy of the coordinates of base stations has a crucial influence on the positioning performance. Some methods estimate the coordinates of base stations via code measurements, but cannot establish high-precision spatial references. Existing methods based on carrier measurements rely on the known calibration points of a receiver, which still need artificial measurement. To overcome the shortcomings of existing methods in accuracy or autonomy, this research proposes a carrier measurements based spatial reference establishment method, which can precisely estimate the coordinates of base stations without known calibration points. A theoretical model of the coordinate estimation problem is established for ground-based positioning systems, and the proposed algorithm obtains the maximum likelihood estimation based on the observations of a mobile receiver. The simulation results show that the proposed method can achieve centimeter-level accuracy of coordinate estimation without dependence on calibration points. Compared with existing methods, the proposed method has advantages in estimation accuracy and autonomy, and can be applied in the rapid deployment of ground-based positioning systems, thereby improving the flexibility and practicability.

The performance of navigation can be significantly enhanced by coupling the Global Navigation Satellite System (GNSS) and the Inertial Navigation System (INS) because the characteristics of these two systems complement each other. Among those structures of coupling, Ultra-Tight Coupling (UTC) fully uses the information of both systems, therefore has attracted much attention of researchers. To do researches of UTC, it is reasonable that the simulation platform should be built first. Although there have been several open source simulation platforms for the researches of Tight Coupling (TC), which have become important tools for the analysis of TC, the researches about designing simulation platform of UTC is rare, and the standard of simulation has not been settled either, becoming a barrier of the development of UTC. In this paper, a Software Defined Receiver (SDR) for UTC simulation is proposed. The SDR is derived from the open source code of TC SDR with many modules added, including the GNSS signal generation, transmitting, acquisition, and tracking. The tracking results of receiver are transformed to the errors of pseudo-range, and then used in the Extended Kalman Filter (EKF) for coupling. The output of EKF on the other hand adjusts the INS and the loop of GNSS as feedback. The design of SDR for UTC does not need to simulate the navigation data, hence is easy to be realized. The simulation results are also presented to show the validity of the designed SDR.

In the classic inertial-based foot-mounted PDR (Pedestrian Dead Reckoning) system, the EKF (Extended Kalman Filter) algorithm assisted by ZUPT (zero-velocity update) is widely used. However, in the actual test, the system still has a significant positioning deviation, as the ZUPT algorithm is poor in observability of system’s heading errors. In this paper, for enhancing the robustness of the PDR system’s heading, a new calibrating heading method has been proposed. It is mainly implemented by using some anchor points with known position coordinates. Firstly, since the inertial-based PDR system cannot obtain accurate initial geographic heading independently, a calibration line consisting of two known anchor points is constructed. At the initial stage, the pedestrian first walks along this line to obtain its test heading. Then using the actual heading of the line minus its test heading to get the heading offset which can be used to calibrate the initial heading effectively. Secondly, during the pedestrian movement, several known anchor points are set at the heading change points (the turning points). During pedestrian traveling, by judging whether pedestrian walk along the route between adjacent anchor points, then using the real heading of adjacent anchor points to correct the inertial recursive heading of the PDR system in real time. Also, when pedestrian passes these anchor points, by comparing the difference between the test and true coordinates of anchor points, the turning points’ position can be calibrated. Moreover, each time the pedestrian passes the anchor point, intentionally stopping for 1–2 s to guarantee in a stable stance position, then the ZARU (Zero Angular Rate Update) is used to calibrate the bias of the gyroscope. Finally, the effectiveness of heading calibration results is shown in the experiment part.

With the wide application of satellite navigation, positioning and timing function in civil infrastructure, the reliable and effective operation of these important facilities strongly depends on the safety of satellite navigation system. The detection on navigation deception signals is one of the important methods to ensure safety, which has become a research hotspot in recent years. Among many methods the detection based on spatial direction information makes full use of the characteristics of electromagnetic wave direction which is difficult to be replicated, and has the features of high detection accuracy and strong ability to distinguish true from false. However, most of the existing methods need to be based on multi-antenna or multi-platform direction finding. In order to solve this problem, the new method is put forward in this paper. Firstly the pattern characteristics of the satellite navigation signal receiving antenna are deeply studied. The intensity of each satellite navigation signal captured is measured by the tilt rotation of a single antenna, and the azimuth angles of actual arrival for satellite navigation signals are obtained by the maximum fitting estimation after the curve smoothing. Then the azimuth angles of the reference signals are calculated by the navigation satellite almanac information downloaded beforehand. Based on the information, the deception jamming signal can be judged effectively by contrasting the actual azimuth mutual angle matrix with the reference one. The validity and accuracy of this method are verified by simulations. It provides a new technical way for the single antenna satellite navigation receiver to detect on navigation deception signals by spatial information.

With the increasing dependence of civil infrastructure on the satellite navigation system such as positioning, speed measurement and time service in recent years, the threat of navigation deception jamming becomes more and more serious. So the effective detection on navigation deception signal has become a recent research hotspot. Although various deception detection methods have been proposed continuously, due to the limitation of various boundary conditions, there are few practical applications in engineering. In this paper, the image sensors such as cameras, which are widely used on UAV platforms, are used to process the continuous output of ground imaging data. Based on optical flow computation, the real motion speed of the platform can be obtained in real time. The navigation deception jammer can only affect the satellite navigation receiver, but it cannot control the movement mode of the platform. Therefore, the navigation receiver captured and influenced by deception jammer can be judged by contrasting the velocity of the optical flow measurement with that from the satellite navigation receiver. When the navigation deception jamming signal comes from the same direction, this direction can also be estimated by combining the measurement of reference frequency with the specific motion of the platform. Finally, the feasibility and validity of above approach are verified by simulations. Moreover, the existing hardware modules on the platform can be made use of, and signal processing software only needs to be added to enhance the anti-deception ability of the existing platform. So it has good engineering application values.

Adaptive beamforming based on the oblique projection technique, which can maximum retain useful signal and form nulls in the interference direction. The oblique projection technique is applied to GPS anti-jamming with good effect. GPS satellite signal is very weak, at the same time, the steering vector of the satellite signal is difficult to obtain. these make the oblique projection technique difficult to apply to GPS anti-jamming. Aiming at this problem, this paper proposes a low-complexity subspace tracking algorithm for acquiring GPS satellite steering vectors based on the cyclostationary characteristics of GPS satellite C/A codes. Simulation experiments results demonstrate of this algorithm.

GNSS (Global Navigation Satellite System) jamming events become more and more rampant, involve larger and larger regions, and cause interruption of or threat against services of position, velocity and time (PVT). Along with the quantitatively rapid growth and wide prevalence of smart phones embedded with satellite navigation function modules, it is quite possible to locate wide-area jammers by using satellite navigation terminals. This paper presents a jammer localization approach based on crowdsourcing observation data, which is capable of completing jammer localization with a high success rate and an accurate result, by fusing C/N0 (carrier-to-noise density power ratio) measurements and inherent parameters of satellite navigation terminals. The approach has advantages of large area coverage, real time, low need of software and hardware configuration of terminals, low demand on the position relationship of a jammer and its surrounding terminals, and insensitiveness to jamming characteristics.

The spoofing interference is significantly harmful for the applications based on GNSS technology. Aiming to realize the high-speed and high-accuracy anti-spoofing, a joint spoofing detection, recognition and elimination scheme is proposed based on the Long-Short-Time Memory (LSTM) neural network in this paper. First, by analyzing and utilizing the time-sequence characteristics of the spoofing attack, a spoofing detection and attack-mode recognition algorithm is designed by using a LSTM neural network. Second, two algorithms to identify the correlation peak based on the comparison of the peak-mean with the historical-mean and a LSTM network are designed for the static attack and the dynamic attack, respectively. Finally, the parameters of the spoofing peak given by the correlation peak identification module are input to a sub-space projection based signal eliminator to cancel the interference. Test results show that a higher accuracy for spoofing detection and identification could be obtained by the proposed solution and the spoofing signal could be efficiently suppressed. In addition, our scheme is executed during the signal acquisition stage. Therefore, it is beneficial to identify and eliminate interference earlier and more quickly.

Under the complex war environment based on Global Navigation Satellite Systems (GNSS), suppression interference and spoofing interference would be used in combination by enemy. Thus, the difficulty of interference detection and recognition in the receiver could increase significantly due to the uncertain appearance of these two categories of attacking signals. Aiming to this issue, a BP (Back Propagation) neural network based two-stage interference classification and recognition scheme is proposed towards the combined interference scenario with suppression interference and spoofing. Both networks utilize a three-layer fully connected neural network to realize classifying decisions. The first-stage recognition module adopt nine characteristic parameters extracted from time, frequency and power domains of the digital intermediate frequency (IF) signals, which are fed into a BP neural network, to recognize six typical suppression interferences, such as Single Tone Interference (STI), Multi-Tone Interference (MTI), Linear Frequency Modulation Interference (LFMI), Pulse Interference (PI), BPSK Narrowband Interference (BPSKNBI) and BPSK Wideband Interference (BPSK WBI). However, since spoofing interference has the similar structure as the true satellite signal, the second-stage recognition module is introduced to distinguish the spoofing signal from the true satellite signal by using eleven new characteristic parameters extracted from the two-dimensional array output by the acquisition processing of a receiver. The test results show that the proposed scheme can recognize a kind of suppression interference or a spoofing signal appeared randomly more quickly and accurately.

GNSS (Global Navigation Satellite System) spoofing has a great impact on the receiver getting trusted position, navigation and timing information, letting the receiver output erroneous information without any notice and causing an incalculable loss to the user. Since the spatial location of the spoofing interference source, the relative position between the repeater and the user, the parameter characteristics of the deceptive signal are different from the authentication signal, the research on the all above difference are getting great improvements. In the complex electromagnetic interference environment, the carrier-to-noise ratio (CN0) estimation will decrease with the increase of the jamming power. However, the CN0 will not follow this rule under the repeater spoofing scene, which may give rise to false missing probability of the spoofing detection method based on CN0 estimation. In addition, the spoofing detection method based on absolute total power measurements will get higher false alarm probability under the jamming interference scene. This paper proposes a constant false-alarm rate (CFAR) repeater spoofing detection method based on In-Phase correlation values under common signal power scenarios and power-enhanced signal scenarios. This method is realized and verified by simulation under various scenes.

Adaptive antenna array technique is an effective method for interference mitigation in Global Navigation Satellite Systems (GNSS) receivers. Among which, minimum mean square error (MMSE) algorithm could maximize the GNSS signal and reject interference, by minimizing the mean-square-error between the array output and a reference signal. Its performance depends on the reference signal that used. In practice, an ideal reference signal is difficult to obtain directly due to the low power of satellite signals. Thus MMSE algorithm is usually performed after code correlation when a local reference signal could be recovered from tracking results. However, due to the existence of tracking bias, the recovered local reference signal will deviate from an ideal one, resulting in performance deterioration. This paper analyzes the impact of tracking bias including code phase bias, carrier phase bias and carrier frequency bias, on performance of the post-correlation MMSE algorithm. The results show that, the loss of the array output SINR (signal to interference plus noise ratio) caused by tracking bias is ignorable considering the precision of the current tracking loops techniques. The performance of the post-MMSE algorithm approaches to that of an optimal beamformer.

In general, the accuracy and reliability of the GNSS receivers are seriously threatened by interference because the satellite signal arriving at the receivers is extremely weak. Under weak signal conditions, adaptive nulling based on antenna array has been proved to be the most effective interference mitigation method. In the context of navigation war, it has become a strategic to improve the satellite signal power through power-enhancement. Under this condition, the weak signal assumption will no longer hold on and whether adaptive nulling anti-jamming method is still effective deserves further study. In this paper, the adaptive nulling performance under satellite power-enhancement conditions is analyzed, the results show that, under weak interference condition (the interference-to-signal ratio (ISR) is less than 30 dB), the adaptive nulling algorithm will partially suppress the satellite signal when the power enhancement exceeds 20 dB. While when the ISR exceeds 40 dB, the adaptive nulling algorithm will mainly suppress the interference, and the attenuation of satellite signal is ignorable. From the perspective of the final navigation and positioning performance, the current adaptive nulling anti-jamming algorithm is still effective under power-enhancement conditions.

GNSS-dependent services are playing an important role in our lives, but GNSS signals are vulnerable to spoofing attacks. An intermediate spoofing attack, in which the navigation solution is diverted while receiver tracking loops maintain lock, is difficult to detect. In this paper, a novel anti-spoofing method based on multipath mitigation technology (MMT) is proposed to detect spoofing attacks and recover navigation solution. The method can estimate time delays of spoofing and authentic signals simultaneously and inspect the consistency of the measurements. It is easy to implement in a conventional single-antenna receiver by adding an anti-spoofing module. Experiments with the Texas spoofing test battery show that the proposed countermeasure has a promising capability of detecting a spoofing attack and recovering navigation solution in its early stage.

Global Navigation Satellite System (GNSS) is vulnerable to spoofing attack because of its low power and open civil signal structure. Loran-C system is independent of GNSS and can be used for anti-spoofing. In order to detect, identify the spoofing signals and exclude its influence on position, velocity, and time (PVT) results, the paper proposes the GNSS anti-spoofing method assisted by Loran-C system. When the number of Loran-C signals is relatively less, the difference observations of Loran-C are used to identify whether the GNSS positioning result is right or wrong, and the factors affecting the detection performance are studied. When the Loran-C receiver can provide independent positioning information, all spoofing signals are identified by the clustering algorithm after the consistency detection of GNSS pseudorange observations, Loran-C positioning information and satellite positions. Then if the number of remained GNSS signals after spoofing exclusion is less than 4, the GNSS signals and Loran-C signals are combined to improve the positioning accuracy and the Dilution of Precision (DOP) is used to measure the positioning accuracy. Finally, the feasibility of the proposed method is verified by simulation experiments.

The format of spoofing signal in Global Navigation Satellite System (GNSS) is identical to that of real navigation. Therefore, the spoofing has been a severe threat to GNSS. In loosely coupled GNSS/INS integration system, velocity and position are selected as the measurement innovations in Kalman filter (KF). In tightly coupled GNSS/INS integration system, inertial navigation system (INS) assists GNSS, with measurement innovations of pseudo-range and pseudo-range rate. In this paper, a spoofing attack test is performed by tightly coupled GNSS/INS integration system and loosely coupled GNSS/INS integration system respectively and the comparison between the capabilities of the two are made. The loosely or tightly coupled integrated system identifies the spoofing attack signals, by monitoring GNSS and INS. The inconsistency between velocity and position in loosely coupled integrated system, pseudo-range and pseudo-range rate in tightly coupled integrated system, which makes it possible to detect the spoofing attack signals. This paper presents the performance test on loosely/tightly coupled GNSS/INS integration system for anti-spoofing, by the trajectory generated by Spirent SimGen. The simulation result indicates that the algorithm of spoofing detection based on tightly coupled system outperforms that on the loosely coupled system.

Jamming recognition technology plays an important role in satellite navigation anti-jamming systems. Accurate and reliable recognition of jamming types is a necessary premise for adopting targeted anti-jamming means. To solve the problem of jamming recognition in satellite navigation systems, a jamming recognition algorithm based on deep neural network (DNN) is proposed in this paper. A set of jamming features with low complexity and high resolution is extracted in time, frequency and transform domains. Two jamming classifiers based on decision tree (DT) and DNN are constructed respectively, and their jamming recognition performance is compared. The simulation results indicate that when jamming-to-signal-and-noise ratio (JSNR) reaches 0 dB, the recognition rate of the DNN-based classifier for 12 types of typical suppressed jamming can reach more than 99%. Compared to the DT-based classifier, the DNN-based one improves the recognition rate of narrow band modulation, multi-tone, linear frequency modulation and sinusoidal frequency modulation jamming by more than 2 dB, better in recognition performance and easier to design. In the compound jamming situation, when JSNR reaches 10 dB, the recognition rate of the DNN-based classifier for all 10 types of compound jamming can reach more than 85%.

Due to the non-linearity of the space-time adaptive anti-jamming weighting process, satellite signal correlation peaks will inevitably be shifted and distorted, which will cause the receiver positioning accuracy to decrease. At present, the new generation of satellite navigation system has adopted a new BOC signal system. Compared with BPSK modulation, BOC modulated signals have split spectrum characteristics in the spectrum. In the current research, there are few studies on the effects of various anti-interference algorithms on BOC signals in anti-interference applications. Therefore, this paper studies the effect of anti-interference processing of adaptive array antenna on BOC signal. Based on the theoretical derivation, the effects of several typical algorithms on the distortion of the BOC signal correlation peaks are simulated and analyzed. A low distortion beamforming algorithm is proposed, and its performance in different interference environments is simulated and verified. Finally, some reasonable suggestions are proposed. The research results have certain guiding significance for the application of BOC signal under anti-interference conditions.

Due to the influence of transmission path attenuation, Received Global Navigation Satellite System (GNSS) signal is weak, and extremely susceptible to suppression interference, resulting in degradation of signal quality. In order to improve the safety and reliability of the navigation system, the detection and identification of interference signals are very important, and also provides the necessary prior information for the location of interference sources and interference suppression. Traditional interference recognition algorithms are mostly based on manually designed feature parameters such as power spectrums, and preset recognition thresholds to achieve interference classification. The algorithm has high complexity, poor real-time performance, and it is difficult to accurately identify interference types. Aiming at the shortcomings of traditional recognition technology, this paper proposes a GNSS interference source intelligent recognition algorithm, which uses electromagnetic fingerprint features to build a deep convolutional neural network to achieve suppression interference classification. Based on the constructed mathematical model, Pseudo Wigner-Vile (PWVD) electromagnetic fingerprint of interference signal is extracted. By learning different types of interference electromagnetic fingerprint features, the GoogLeNet model cloud realize the real-time identification of the unknown type of interference signal. The experimental results show that compared with the traditional interference signal recognition algorithm, the proposed algorithm has low implementation complexity and greatly improved recognition accuracy. Especially when the interference-to-noise ratio (JNR) is low, thermal noise robustness is stronger.

The Space-time adaptive processing method (STAP) used in array antenna GNSS receiver for interference suppression may induce pseudo-range measurement bias, which is one of the main error sources for precise application. In this paper, a distortionless blind beamformer for interference suppression is proposed. Firstly, subspace projection algorithm is employed for interference suppression. Secondly, the direction of the satellite signal is estimated by the sparse recovery method after de-spreading process. Furthermore, a space-time beamformer is constructed using the estimated direction information, which can achieve distortionless measurement and signal enhancement. Extensive results on simulation experiments demonstrate that the proposed method can achieve interference suppression, and the bias induced by space-time filtering can be reduced effectively.