Multistatic Passive Radar Target Detection: A detection theory framework

✍ Scribed by Amir Zaimbashi, Mohammad Mahdi Nayebi

• Publisher: Scitech Publishing
• Year: 2023
• Tongue: English
• Leaves: 396
• Series: Radar, Sonar and Navigation
• Category: Library

✦ Synopsis

This book is devoted to target detection in a class of radar systems referred to as passive multistatic radar. This system is of great interest in both civilian and military scenarios due to many advantages. First, this system is substantially smaller and less expensive compared to an active radar system. Second, the multistatic configuration improves its detection and classification capabilities. Finally, there are many signals available for passive sensing making them hard to avoid.

Multistatic Passive Radar Target Detection: A detection theory framework focuses on examining the multistatic passive radar target detection problem using the detection-theory framework, with the aim of presenting the latest research developments in this field. Early methods were based on intuition and lacked optimality, however, more recent methods with a clear theoretical basis have emerged, based on detection theory. The book offers timely and useful information to advanced students, researchers, and designers of passive radar (PR) systems.

The book is organized into four parts, with each part addressing a specific aspect of target detection in various radar systems. The first part, consisting of two chapters, covers the fundamentals of PR and traditional target detection algorithms. Part two comprises seven chapters and deals with the target detection issue in passive bistatic radar (PBR) with a reliable reference channel. Part three includes two chapters and focuses on the detection of targets in multistatic PR systems in the presence of noisy reference channels. Finally, part four, which consists of two chapters, discusses the target detection problem in multistatic and MIMO PRs when no reliable reference channel is available.

✦ Table of Contents

Contents
About the Authors
Preface
Part I Passive radar basic principles and conventional target detection algorithms
1 An introduction to passive radar
1.1 Passive radar illuminators
1.1.1 FM radio signal characteristic
1.1.2 DVB-T signal characteristic
1.1.3 ATV signal characteristic
1.2 Geometry of passive radars
1.3 Power budget and passive radar coverage
1.4 Summary
References
2 Passive radar conventional target detection algorithms
2.1 Surveillance and reference signal models
2.2 Conventional interference removal approaches
2.2.1 Subspace-based interference removal approaches
2.2.2 Adaptive filter-based interference removal approaches
2.2.2.1 Least mean squares algorithms
2.2.2.2 Recursive least squares algorithms
2.3 Conventional PR target detection approaches
2.4 Performance results
2.4.1 Multipath removal capability: stationary multipath scatterers
2.4.2 Multipath removal capability: moving multipath scatterers
2.4.3 Detection performance evaluation
2.5 Summary
References
Part II Target detection in passive bistatic radar under high-SNR reference channel
3 Multitarget detection problem in single-band FM-based passive radar
3.1 Introduction
3.2 High-SNR RC-based problem formulation
3.2.1 GLRT-based detector: known _2 and when K = 1
3.2.2 GLRT-based detector: unknown _2 and when K = 1
3.2.3 Two-stage GLRT-based detector: general problem
3.2.4 First stage of 2S-GLRT-based detector
3.2.5 Second stage of 2S-GLRT-based detector
3.3 Analytical performance analysis
3.4 Simulation results
3.4.1 False alarm regulation evaluation
3.4.2 Detection performance evaluation
3.5 Summary
References
Appendix 3A: Derivation of detection performance
4 Multitarget detection in multiband FM-based passive bistatic radar: target detection quality improvement
4.1 Introduction
4.2 Signal modeling
4.3 Design of UMPI-based detector
4.3.1 First stage of UMPI-based detector
4.3.2 Second stage of UMPI-based detector
4.4 Analytical performance analysis
4.4.1 SW1-I target model
4.4.2 SW1-C target model
4.5 Performance results
4.6 Summary
References
Appendix 4A: Maximal invariant statistic distribution
Appendix 4B: Detection probability formulas for the SW1-I and SW1-C target models
5 Multitarget detection in multiband FM-based PBR: target range resolution improvement
5.1 Introduction
5.2 Signal modeling
5.3 Design of high-resolution UMPI test
5.3.1 First stage of UMPI-based detector
5.3.2 Second stage of UMPI-based detector
5.4 Analytical performance analysis
5.5 Analytical assessment of improved range resolution
5.6 Analytical performance analysis under amplitude mismatch
5.7 Simulation results
5.8 Summary
References
Appendix 5A: Maximal invariant derivation
Appendix 5B: Maximal invariant statistic pdfs
6 Broadband target detection algorithm in FM-based passive bistatic radar systems
6.1 Introduction
6.2 Signal modeling
6.3 Design of a broadband UMPI test
6.3.1 First stage of a UMPI-based detector
6.3.2 Second stage of a UMPI-based detector
6.4 Analytical performance evaluation
6.5 Enhancing range resolution with broadband detection
6.6 Enhancing target performance quality with broadband detection
6.7 Simulation results
6.8 Summary
References
Appendix 6A: MI statistic derivation
7 Multitarget detection in FM and digital TV-based passive radar: M-ary hypothesis testing framework
7.1 Signal modeling
7.2 M-ary hypothesis testing-based detection approach
7.2.1 BH-GLRT detector design
7.2.2 Forward and recursive implementation of BH-GLRT detector
7.2.3 Parallel implementation of FR-BH-GLR detector
7.2.4 FFT-based implementation of PI-FR-BH-GLR detector
7.3 Analytical performance evaluation
7.4 Simulation results
7.4.1 The importance of optimal detectors for passive radar
7.4.2 Performance of the proposed detection algorithm
7.4.3 A comparative evaluation of passive radar detection algorithms
7.5 Summary
References
8 Multitarget detection in analog TV-based passive radar systems
8.1 Introduction
8.2 Detection problem formulation
8.3 Multilayer GLR-based detection algorithm
8.3.1 Chirp z-transform implementation of MLa-GLR detection algorithm
8.3.2 Recursive implementation of the CZT-MLa-GLR detection algorithm
8.4 Robust S-CZT-MLa-GLR detection algorithm
8.5 Performance results
8.6 Summary
References
9 Multi-accelerating- target detection in passive radar systems
9.1 Introduction
9.2 Signal modeling
9.3 Detection problem formulation
9.4 Multilayer GLR-based detection algorithm
9.5 Chirp-FFT implementation of 3D-MLa-GLRT
9.6 Successive implementation of 3D-MCFFT-MLa-GLRT
9.7 Performance results
9.7.1 Detection performance of the 2D-SaR detection algorithm
9.7.2 Performance evaluation of the 3D-SaR detection algorithm
9.8 Summary
References
Part III Multistatic passive radar target detection under noisy reference channels
10 Noisy RC-based bistatic passive target detection
10.1 Introduction
10.2 Target detection problem formulation
10.3 LRT-based detector
10.4 Kernel-based detectors
10.4.1 Preliminaries
10.4.2 Kernelized LRT-based proposed detectors
10.5 Performance results
10.6 Summary
References
11 Noisy RC-based multistatic passive radar target detection
11.1 Introduction
11.2 Problem formulation
11.3 LRT-based proposed detectors
11.4 Performance results
11.5 Summary
References
Appendix 11A: General detection problems P1
Part IV Multistatic passive radar target detection without reference channels
12 Multistatic passive radar target detection without direct-path interference
12.1 Signal model and problem formulation
12.2 Detectors design
12.2.1 Proposed detectors for detection problem P1
12.2.1.1 P1-Rao detector
12.2.1.2 P1-Vol detector
12.2.1.3 P1-LRT-based proposed detectors
12.2.2 Proposed detectors for detection problem P2
12.2.3 Proposed detector for detection problem P3
12.3 CFAR analysis of proposed detectors
12.4 Performance results
12.4.1 False alarm probability evaluations
12.4.2 Detection performance evaluations
12.5 Summary
References
Appendix 12A: P1-Rao detector
Appendix 12B: P1-LRT detector
Appendix 12C: P2-C2-LRT detector
Appendix 12D: P3-LRT detector
13 MIMO passive radar target detection with direct-path interference
13.1 Introduction
13.2 Detection problem formulation
13.3 Detectors design
13.4 Performance results
13.4.1 Performance of SIMO systems
13.4.2 Performance of MIMO systems
13.4.3 Rao test statistic for target localization
13.5 Summary
References
Appendix 13A: Unc-Rao test statistic derivation
Index