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Wireless Networks
Erschienen in: Wireless Networks 7/2020

03.06.2020

Optimum consultation for parallel distributed detection systems

verfasst von: Nedal Al-Ababneh

Erschienen in: Wireless Networks | Ausgabe 7/2020

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Abstract

An optimum consultation scheme for parallel distributed detection system is proposed. Two-way communication links are assumed between a set of local sensors and the fusion center. The observations of each sensor are assumed to be statistically independent of all other sensors observations. We also show that the proposed consulting scheme can be optimized such that its performance is identical to that of the optimum parallel scheme. It should be emphasized that the proposed consulting system exhibits the advantage of conditional nonrandom consultation between the fusion center and the sensors. Therefore, the sensors are less detectable which gives the system higher chance of survivability than that of the typical parallel system. Performance results for the case of two and the case of three sensors are given and compared with those of the centralized scheme.
Vorheriger Artikel An Autonomous Fault-Awareness model adapted for upgrade performance in clusters of homogeneous wireless sensor networks
Nächster Artikel Taylor kernel fuzzy C-means clustering algorithm for trust and energy-aware cluster head selection in wireless sensor networks

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Literatur
1.
Zhang, S., Theagarajan, L. N., Choi, S., & Varshney, P. K. (2019). Fusion of correlated decisions using regular vine copulas. IEEE Transactions on Signal Processing, 67(8), 2066–2079.MathSciNetCrossRef
2.
Al-Ababneh, N. (2019). Optimization of a distributed detection system with two consulting sensors using an improved detection scheme. AEU-International Journal of Electronics and Communications, 108, 158–162.CrossRef
3.
Yang, C., Feng, L., Zhang, H., He, S., & Shi, Z. (2018). A novel data fusion algorithm to combat false data injection attacks in networked radar systems. IEEE Transactions on Signal and Information Processing over Networks, 4, 125–136.MathSciNetCrossRef
4.
Geng, Z., Xu, R., Deng, H., & Himed, B. (2018). Fusion of radar sensing and wireless communications by embedding communication signals into the radar transmit waveform. IET Radar Sonar & Navigation, 12(6), 632–640.CrossRef
5.
Xie, Mingchi, Yi, Wei, Kirubarajan, Thia, & Kong, Lingjiang. (2018). Joint Node Selection and Power Allocation Strategy for Multitarget Tracking in Decentralized Radar Networks. IEEE Transactions on Signal Processing, 66(3), 729–743.MathSciNetCrossRef
6.
Al-Jarrah, M. A., Al-Jarrah, R., & Al-Ababneh, N. (2017). Decision fusion in mobile wireless sensor networks using cooperative multiple symbol differential space time coding. AEU International Journal of Electronics and Communications, 80, 127–136.CrossRef
7.
Nesa, N., & Banerjee, I. (2017). IoT-based sensor datafusion for occupancy sensing using Dempster-Shafer evidence theory for smart buildings. IEEE Internet of Things Journal, 4(5), 1563–1570.CrossRef
8.
Fakhrey, Harith, Tiwari, Rajesh, & Johnston, Martin. (2016). The optimum design of location-dependent key management protocol for a WSN with a random selected cell reporter. IEEE Sensors Journal, 16(19), 7217–7226.CrossRef
9.
Hu, Q., Su, H., Zhou, S., Liu, Z., & Liu, J. (2016). Target detection in distributed MIMO radar with registration errors. IEEE Transactions on Aerospace and Electronic Systems, 52, 438–450.CrossRef
10.
Tenny, R. R., & Sandell, N. R. (1981). Detection with distributed system. IEEE Transactions on Aerospace and Electronics Systems, AES–17, 501–510.CrossRef
11.
Chair, Z., & Varshney, P. K. (1986). Optimal data fusion in multiple sensor detection system. IEEE Transaction on Aerospace and Electronic systems, AES–22, 98–101.CrossRef
12.
Hoballah, I. Y., & Varshney, P. K. (1986). Neyman-Pearson detection with distributed sensors. In Proceedings of 25th IEEE conference decision control (vol. 25, pp. 237–241).
13.
Viswanathan, R., & Varshney, P. K. (1997). Distributed detection with multiple sensors: Part I. Fundamentals. Proceedings of IEEE, 85(1), 54–63.CrossRef
14.
Varshney, P. K. (2012). Distributed detection and data fusion. New York, NY: Springer.
15.
Sadjadi, F. A. (1986). Hypotheses testing in a distributed environment. IEEE Transaction on Aerospace and Electronics Systems, AES–22, 134–137.CrossRef
16.
Chen, B., & Willett, P. K. (2005). On the optimality of the likelihood-ratio test for local sensor decision rules in the presence of nonideal channels. IEEE Transactions on Information Theory, 51(2), 693–699.MathSciNetCrossRef
17.
Srinivasan, R. (1985). Distributed radar detection theory. IEE Proceedings, 133(part F), 55–60.MathSciNet
18.
Reibman, Amy R., & Nolte, L. W. (1987). Optimal detection and performance of distributed sensor systems. IEEE Transactions on Aerospace and Electronic Systems, 1, 24–30.CrossRef
19.
Conte, E., D’Addio, E., Farina, A., & Longo, M. (1983). Multistatic radar detection: synthesis and comparison of optimum and suboptimum receivers. IEE Proceedings F (Communications, Radar and Signal Processing), 130(6), 484–494.CrossRef
20.
Amy, R., & Nolte, L. W. (1987). Optimal detection and performance of distributed sensor systems. IEEE Transactions on Aerospace and Electronic Systems, AES–23, 24–30.
21.
Thomopoulos, Stelios C. A., Viswanathan, Ramanarayanan, & Bougoulias, Dimitrios C. (1987). Optimal decision fusion in multiple sensor systems. IEEE Transactions on Aerospace and Electronic Systems, 5, 644–653.CrossRef
22.
Thomopoulos, S. C. A., & Okello, N. N. (1992). Distributed detection with consulting sensors and communication cost. IEEE Transactions on Automatic Control, 37(9), 1398–1405.MathSciNetCrossRef
23.
Difranco, J. V., & Rubin, W. L. (1968). Radar detection. Upper Saddle River: Prentice-Hall.
24.
Van trees, H. L. (1968). Detection, estimation and modulation theory (Vol. I). New York: Wiley.MATH
Metadaten
Titel
Optimum consultation for parallel distributed detection systems
verfasst von
Nedal Al-Ababneh
Publikationsdatum
03.06.2020
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 7/2020
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-020-02365-5

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