Signal Design for Modern Radar Systems

Introduction
	Practical Signal Design
		The Why
		The How
		The What
	Radar Application Focus Areas
		Designing Signals with Good Correlation Properties
		Signal Design to Enhance SINR
		Spectral Shaping and Coexistence with Communications
		Automotive Radar Signal Processing and Sensing for Autonomous Vehicles
	What this Book Offers
	References
Convex and Nonconvex Optimization
	Optimization Algorithms
		Gradient Descent Algorithm
		Newton's Method
		Mirror Descent Algorithm
		Power Method-Like Iterations
		Majorization-Minimization Framework
		Block Coordinate Descent
		Alternating Projection
		Alternating Direction Method of Multipliers
	Summary of the Optimization Approaches
	Conclusion
	References
PMLI
	The PMLI Formulation
		Fixed-Energy Signals
		Unimodular or Constant-Modulus Signals
		Discrete-Phase Signals
		PAR-Constrained Signals
	Convergence of Radar Signal Design
	PMLI and the Majorization-Minimization Technique: Points of Tangency
	Application of PMLI
		A Toy Example: Synthesizing Cross-Ambiguity Functions
		PMLI Application with Dinkelbach's Fractional Programming
		Doppler-Robust Radar Code Design
		Radar Code Design Based on Information-Theoretic Criteria
		MIMO Radar Transmit Beamforming
	Matrix PMLI Derivation for (3.71) and (3.75)
	Conclusion
	Exercise Problems
	References
MM Methods
	System Model
	MM Method
		MM Method for Minimization Problems
		MM Method for Minimax Problems
	Sequence Design Algorithms
		ISL Minimizers
		PSL Minimizers
	Numerical Simulations
	Conclusion
	Exercise Problems
	References
BCD Method
	The BCD Method
		Rules for Selecting the Index Set
		Convergence of BCD
	BSUM: A Connection Between BCD and MM
	Applications
		Application 1: ISL Minimization
		Application 2: PSL Minimization
		Application 3: Beampattern Matching in MIMO Radars
	Conclusion
	Exercise Problems
	References
	Appendix 5A
	Appendix 5B
	Appendix 5C
Other Optimization Methods
	System Model
		System Model in the Spatial Domain
		System Model in the Spectrum Domain
	Problem Formulation
	Optimization Approach
		Convergence
		Computational Complexity
	Numerical Results
		Convergence Analysis
		Performance Evaluation
		The Impact of Similarity Parameter
		The Impact of Zero Padding
	Conclusion
	References
	Appendix 6A
Deep Learning for Radar
	Deep Learning for Guaranteed Radar Processing
		Deep Architecture for Radar Processing
		Numerical Studies and Remarks
	Deep Radar Signal Design
		The Deep Evolutionary Cognitive Radar Architecture
		Performance Analysis
	Conclusion
	Exercise Problems
	References
Waveform Design in 4-D Imaging MIMO Radars
	Beampattern Shaping and Orthogonality
		System Model
		Problem Formulation
	Design Procedure Using the CD Framework
		Solution for Limited Power Constraint
		Solution for PAR Constraint
		Solution for Continuous Phase
		Solution for Discrete Phase
	Numerical Examples
		Contradictory Nature of Spatial and Range ISLR
		Trade-Off Between Spatial and Range ISLR
		The Impact of Alphabet Size and PAR
	Conclusion
	Exercise Problems
	References
	Appendix 8A
	Appendix 8B
	Appendix 8C
	Appendix 8D
	Appendix 8E
Waveform Design for Spectrum Sharing
	Scenario and Signal Model
		Communication Link and CSI
		Transmit Signal Model
		Signal Model at Targets
		Backscatter Signal Model
		Clutter Model
		Signal Model at ACV
		CSI Exploitation
	Performance Indicators
		ACV SNR Evaluation
		SCNR at JRCV
	Waveform Design and Optimization Formulation
		Design Methodology
		Optimization Problem for ACV
		Formulation of JRC Waveform Optimization
		Solution to the Optimization Problem
		JRC Algorithm Design
		Complexity Analysis
		Range-Doppler Processing
	Numerical Results
		Convergence Behavior of the JRC Algorithm
		Performance Assessment at the Radar Receiver
		Performance Assessment at the Communications Receiver
		Trade-Off Between Radar and Communications
	Conclusion
	References
	Appendix 9A
	Appendix 9B
	Appendix 9C
Doppler-Tolerant Waveform Design
	Problem Formulation
	Optimization Method
	Extension of Other Methods to PECS
		Extension of MISL
		Extension of CAN
	Performance Analysis
		Norm Minimization
		Doppler-Tolerant Waveforms
		Comparison with the Counterparts
	Conclusion
	References
	Appendix 10A
Waveform Design for STAP in MIMO Radars
	Problem Formulation
	Transmit Sequence and Receive Filter Design
		Optimum Filter Design
		Code Optimization Algorithm
		Discrete Phase Code Optimization
		Continuous Phase Code Optimization
	Numerical Results
	Conclusion
	References
Cognitive Radar: Design and Implementation
	Cognitive Radar
	The Prototype Architecture
		LTE Application Framework
		Spectrum Sensing Application
		MIMO Radar Prototype
	Experiments and Results
	Performance Analysis
	Conclusion
	References
	Appendix 12A
	Appendix 12B
Conclusion
	Computational Efficiency
	Waveform Diversity
	Performance Trade-Off
About the Authors
Index