Waveform Diversity: Theory & Applications Theory & Application

by Pillai, S; Li, Ke Yong; Selesnick, Ivan; Himed, Braham

• ISBN13: 9780071622899
• ISBN10: 0071622896
• Edition: 1st
• Format: Hardcover
• Copyright: 2011-05-13
• Publisher: McGraw-Hill Education

Summary

Practical techniques for taking full advantage of the emerging communications engineering trend of waveform diversityWaveform Diversityexplains how to design an optimum set of waveforms that respects constraints on bandwidth, transmit energy, and pulse duration. This is realized by maximizing the signal to interference/noise power ratio at the receiver output so as to maximize the performance of the underlying task such as target detection or data estimation. The book shows how waveform diversity can be exploited spatially using a multiple set of sensors for both transmission and/or reception, and in the time-frequency domain using distinct waveforms of different durations over different spectral bands. The use of other features such as polarization, energy distribution of various transmit signals are also covered in this cutting-edge guide.Waveform Diversity Examines the topic as it relates to both the transmitter and receiver Reveals real-world applications that can save both bandwidth and transmit energy Is written by renowned experts in the fieldIn-depth coverage of waveform diversity: Waveform Design and Matched Filtering; New Methods for Optimum Transmitter and Receiver Design; Optimum Causal Waveform Design; Discrete-Time Waveform Design; Multichannel Waveform Design; Adaptive Radar

Author Biography

Dr. S. U. Pillai is a professor of Electrical Engineering at Polytechnic University in Brooklyn. He is the author or coauthor of four textbooks, including Space Based Radar.
Ke Yong Li is a Staff Engineer at C & P Technologies, Inc. He is a coauthor of Space Based Radar.

Table of Contents

List of Abbreviations	p. xiii
Introduction	p. 1
Introduction	p. 1
Organization of the Book and Notations	p. 4
References	p. 6
Waveform Design and Matched Filtering	p. 11
Introduction	p. 12
Matched Filter Receivers	p. 15
Matched Filter Receivers in White Noise	p. 17
Matched Filter Receivers in Colored Noise	p. 25
Chirp and Pulse Compression	p. 31
Joint Transmitter-Receiver Design in Noise	p. 37
Joint Time-Bandwidth Optimization	p. 50
Transform of a Chirp Signal	p. 59
References	p. 66
New Methods for Optimum Transmitter and Receiver Design	p. 69
Introduction	p. 69
Transmitter Waveform Design	p. 74
Transmitter Threshold Energy	p. 76
Method I: Desired Band Approach	p. 79
Threshold Energy	p. 80
Energy-Bandwidth Tradeoff	p. 91
Simultaneous Savings on Energy and Bandwidth	p. 98
Method II: Whitening Approach	p. 107
Energy-Bandwidth Tradeoff	p. 120
Optimization of a Functional	p. 127
References	p. 129
Constant Envelope Transmit Signals	p. 131
Convex Sets	p. 132
Methods of Alternating Projections	p. 134
Relaxed Projection Operators	p. 136
Unimodular Sequences Using Cyclic Algorithms	p. 145
General Unimodular Sequences	p. 152
Constant Envelope Signals with Prescribed Discrete Fourier Transform Magnitude	p. 157
Pulse Compression and Huffman Code	p. 166
References	p. 174
Optimum Waveform Design	p. 177
Point Target in White Noise and Arbitrary Clutter	p. 177
Point Target, White Noise, White Clutter (Flat-Flat-Flat Case)	p. 178
Finite Transmit Bandwidth	p. 179
Optimality of Chirp Waveforms	p. 182
Optimum Tx-Rx: Causal Case	p. 183
Noise Only Case	p. 188
High Clutter Case	p. 192
General Case: Clutter and Noise	p. 194
Rational all-Pass Filters	p. 200
References	p. 205
Discrete-Time Waveform Design	p. 207
Matched Filter	p. 207
Optimum Causal Matched Filter	p. 211
Tx-Rx Design in Colored Noise and Interference	p. 225
Multichannel Transmit Signal Design	p. 233
References	p. 250
Sparsity-Based Receivers	p. 255
Introduction	p. 255
Majorization-Minimization	p. 257
The Landweber Iteration	p. 260
Soft-Thresholding	p. 262
Iterated Soft-Thresholding Algorithm	p. 264
Fast ISTA (FISTA)	p. 272
Nonlinear Receiver as a Bayesian Estimator	p. 273
Sparsity-Based Range-Doppler Processing	p. 276
Space-Time Adaptive Processing	p. 282
l2 Regularization	p. 290
References	p. 292
Index	p. 295
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