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Über dieses Buch

This book details some of the major developments in the implementation of compressive sensing in radio applications for electronic defense and warfare communication use. It provides a comprehensive background to the subject and at the same time describes some novel algorithms. It also investigates application value and performance-related parameters of compressive sensing in scenarios such as direction finding, spectrum monitoring, detection, and classification.



Electronic Defence and Compressive Sensing


Chapter 1. Introduction

In this book we describe applications of Compressive Sensing (CS) based algorithms for Electronic Support (ES) tasks such as direction-of-arrival (DOA) estimation of modulated communication signals and spectrum sensing.

Amit Kumar Mishra, Ryno Strauss Verster

Chapter 2. Electronic Defence Systems

Electronic Defence (ED) is defined as the art and science of preserving the use of the Electro-Magnetic (EM) spectrum for friendly use while denying its use to the enemy [157].

Amit Kumar Mishra, Ryno Strauss Verster

Chapter 3. Compressive Sensing: Acquisition and Recovery

The pioneering steps taken toward digitization of signals can be attributed to the theoretical work done by Kotelnikov, Nyquist, Shannon and Whittaker on sampling continuous-time band-limited signals [87, 128, 160, 187].

Amit Kumar Mishra, Ryno Strauss Verster

Simulations of Compressive Sensing Used for Electronic Support Applications


Chapter 4. Design of CS Based DOA Estimation for Modulated Shift-Keying Signal

In light of the data acquisition and recovery benefits that CS provides, as discussed in the previous chapters, it remains a non-trivial task to adopt CS techniques in the signal processing chain—from sampling to recovery—for DOA estimation.

Amit Kumar Mishra, Ryno Strauss Verster

Chapter 5. CS Based Shift-Keying Modulation

Shift-keying specific CS DOA estimation requires accuracy guarantees of CS recovered phase and magnitude estimates before being used as input information for the sub-space DOA estimation algorithms. Otherwise, if accuracy of phase and magnitude estimates cannot be guaranteed, the use of CS sampled and recovered information for DOA estimation will fail. Only when the accuracy guarantees are determined for shift-keying specific CS recovery, can we proceed to utilize CS recovered phase, magnitude, and BIE estimates as scalar inputs to sub-space DOA estimation algorithms.

Amit Kumar Mishra, Ryno Strauss Verster

Chapter 6. Modulation Specific CS DOA

Based on the results of the foregoing chapter, wherein accurate phase estimations were achieved using shift-keying sensing matrices for 2FSK and 2PSK signal, we further our investigation by using CS recovered phase estimates for DOA estimation—referred to as CS DOA in this chapter.

Amit Kumar Mishra, Ryno Strauss Verster

Chapter 7. CS Based Spectrum Sensing for ES

One of the major challenges of electronic defence (ED) systems is to sense a wide spectral band in real time. In this chapter we show the use of compressive sensing (CS) schemes to which have the potential of reducing the load on acquisition for ED spectrum monitoring.

Amit Kumar Mishra, Ryno Strauss Verster

Concluding Statements and Appendices


Chapter 8. Concluding Remarks

In this work we have covered the framework for electronic defence (ED) operations and system requirements of current electronic support (ES) receivers, with specific focus on how to use existing receiver types/architectures to aid in a theoretical implementation of compressive sensing (CS) techniques.

Amit Kumar Mishra, Ryno Strauss Verster

Chapter 9. Appendix: Some Useful Theoretical Background

A signal generated from such a point using an isotropic omni directional antenna, radiates into free space as an ever-expanding sphere [39] which then is able to interact with another resonating elements (i.e. receiver antenna).

Amit Kumar Mishra, Ryno Strauss Verster


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