Waveform Design for Active Sensing Systems: A Computational Approach

327 Pages·2012·16.58 MB·English

by  Hao He, Jian Li, Petre Stoica

WaveformDesignforActiveSensingSystems
AComputationalApproach
Withafocusondevelopingcomputationalalgorithmsforexaminingwaveformdesign
in diverse active sensing applications, this guide is ideal for researchers and practi-
tioners in the field. The three parts conveniently correspond to the three categories of
desirablewaveformproperties:goodaperiodiccorrelations,goodperiodiccorrelations
and beampattern matching. The book features various application examples of using
the newly designed waveforms, including radar imaging, channel estimation for com-
munications, an ultrasound system for breast cancer treatment and covert underwater
communications.Inadditiontonumericalresults,theauthorspresenttheoreticalanal-
yses describing lower bounds or limitations of performance. Focusing on formulating
practicalproblemsmathematicallyandsolvingthemathematicalproblemsusingefficient
and effective optimization techniques, the text pays particular attention to developing
easy-to-use computational approaches. Most algorithms are accompanied by a table
clearlydetailingiterationsteps,andcorrespondingMATLABcodesareavailableonthe
companionwebsite.
HaoHereceivedhisPhDfromtheDepartmentofElectricalandComputerEngineeringat
theUniversityofFlorida,USA,in2011.HisstudentpaperswonawardsattheIEEE13th
DSP Workshop & 5th SPE Workshop in 2009, and at the 2nd International Workshop
onCognitiveInformationProcessingin2010.
JianLiisaprofessorattheDepartmentofElectricalandComputerEngineering,Uni-
versityofFlorida,USA,andaFellowofIEEEandIET.Shehaspublishedthreebooks,
four book chapters, and some 400 papers in archival journals and conference records.
She is a co-author of the paper that received the M. Barry Carlton Award for the best
paperpublishedinIEEETransactionsonAerospaceandElectronicSystemsin2005.
Petre Stoica is a professor at the Department of Information Technology at Uppsala
University,Sweden,amemberoftheRoyalSwedishAcademyofEngineeringSciences
andtheEuropeanAcademyofSciences,anhonorarymemberoftheRomanianAcademy
andafellowoftheRoyalStatisticalSociety,IEEEandEURASIP.Hehaspublished10
books, 15 book chapters, and some 700 papers in archival journals and conference
records,andhaswonseveralawardsofIEEE,IEEandEURASIP.

Waveform Design for
Active Sensing Systems
A Computational Approach
HAOHE
UniversityofFlorida
JIANLI
UniversityofFlorida
PETRESTOICA
UppsalaUniversitet,Sweden
CAMBRIDGE UNIVERSITY PRESS
Cambridge,NewYork,Melbourne,Madrid,CapeTown,
Singapore,Sa˜oPaulo,Delhi,MexicoCity
CambridgeUniversityPress
TheEdinburghBuilding,CambridgeCB28RU,UK
PublishedintheUnitedStatesofAmericabyCambridgeUniversityPress,NewYork
www.cambridge.org
Informationonthistitle:www.cambridge.org/9781107019690
(cid:1)C CambridgeUniversityPress2012
Thispublicationisincopyright.Subjecttostatutoryexception
andtotheprovisionsofrelevantcollectivelicensingagreements,
noreproductionofanypartmaytakeplacewithoutthewritten
permissionofCambridgeUniversityPress.
Firstpublished2012
PrintedintheUnitedKingdomattheUniversityPress,Cambridge
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ISBN978-1-107-01969-0Hardback
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Contents
Preface pagexi
Notation xiii
Abbreviations xiv
1 Introduction 1
1.1 Signalmodel 2
1.2 Designmetrics 4
1.3 Reviewofexistingwaveforms 6
PartI Aperiodiccorrelationsynthesis 15
2 Singleaperiodicsequencedesign 17
2.1 Cyclicalgorithm-new(CAN) 18
2.2 Weightedcyclicalgorithm-new(WeCAN) 21
2.3 Numericalexamples 25
2.3.1 Integratedsidelobelevel(ISL)design 25
2.3.2 Weightedintegratedsidelobelevel(WISL)design 25
2.3.3 Channelestimationincommunications 30
2.3.4 Quantizationeffects 31
2.4 Conclusions 34
Appendix2A Connectionswithaphase-retrievalalgorithm 35
3 Aperiodicsequencesetdesign 39
3.1 TheMulti-CANalgorithm 40
3.2 TheMulti-WeCANalgorithm 43
3.3 TheMulti-CA-original(Multi-CAO)algorithm 46
3.4 Numericalexamples 48
3.4.1 Multi-CAN 48
3.4.2 Multi-WeCAN 53
3.4.3 Multi-WeCANcontinued 55
3.4.4 Quantizationeffects 57
3.4.5 Syntheticapertureradar(SAR)imaging 57
3.5 Conclusions 65
vi Contents
Appendix3A ProofofEquation(3.28) 65
Appendix3B ProofofEquation(3.47) 66
4 Lowerboundsforaperiodicsequences 67
4.1 Boundderivation 67
4.2 Approachingthebound 69
4.3 Conclusions 73
5 Stopbandconstraintcase 74
5.1 StopbandCAN(SCAN) 75
5.2 WeightedSCAN(WeSCAN) 77
5.3 Numericalexamples 80
5.3.1 SCAN 80
5.3.2 WeSCAN 82
5.3.3 Relaxedamplitudeconstraint 82
5.3.4 Usingadifferentfrequencyformulation 87
5.4 Conclusions 87
6 Ambiguityfunction(AF) 88
6.1 AFproperties 88
6.2 Discrete-AF 97
6.3 Minimizingthediscrete-AFsidelobes 99
6.4 Conclusions 101
Appendix6A Widebandambiguityfunction 102
7 Crossambiguityfunction(CAF) 106
7.1 Discrete-CAFsynthesis 106
7.1.1 Theproposedalgorithm 107
7.1.2 Numericalexamples 109
7.2 CAFsynthesis 115
7.2.1 Theproposedalgorithm 116
7.2.2 Numericalexamples 118
7.3 Conclusions 121
Appendix7A Constantvolumepropertyofdiscrete-CAF 121
8 Jointdesignoftransmitsequenceandreceivefilter 123
8.1 Datamodelandproblemformulation 124
8.2 Agradientapproach 126
8.3 Afrequency-domainapproach 128
8.4 Specializationformatchedfiltering 134
8.5 Numericalexamples 136
8.5.1 Spotjamming 137
8.5.2 Barragejamming 140
Contents vii
8.5.3 Robustdesign 142
8.6 Conclusions 142
Appendix8A ProofofEquation(8.25) 145
Appendix8B Lagrangeapproach 146
PartII Periodiccorrelationsynthesis 147
9 Singleperiodicsequencedesign 149
9.1 Designcriteria 150
9.2 TheperiodicCAN(PeCAN)algorithm 153
9.3 Numericalexamples 154
9.4 Conclusions 155
Appendix9A ProofofEquation(9.9) 155
10 Periodicsequencesetdesign 158
10.1 TheMulti-PeCAOalgorithm 159
10.2 TheMulti-PeCANalgorithm 161
10.3 Numericalexamples 163
10.3.1 Multi-PeCAO 163
10.3.2 Multi-PeCAN 165
10.4 Conclusions 167
11 Lowerboundsforperiodicsequences 168
11.1 Boundderivation 168
(cid:1)
11.2 OptimalISLsequencesets 171
11.3 Numericalexamples 173
11.4 Conclusions 174
12 Periodicambiguityfunction(PAF) 175
12.1 PAFproperties 176
12.2 Discrete-PAF 177
12.3 Minimizingthediscrete-PAFsidelobes 182
12.4 Conclusions 184
PartIII Transmitbeampatternsynthesis 185
13 Narrowbandbeampatterntocovariancematrix 187
13.1 Problemformulation 188
13.2 Optimaldesigns 190
13.2.1 Maximumpowerdesignforunknowntargetlocations 190
13.2.2 Maximumpowerdesignforknowntargetlocations 191
13.2.3 Beampatternmatchingdesign 193
13.2.4 Minimumsidelobebeampatterndesign 196
viii Contents
13.2.5 Phased-arraybeampatterndesign 197
13.3 Numericalexamples 197
13.3.1 Beampatternmatchingdesign 198
13.3.2 Minimumsidelobebeampatterndesign 205
13.4 Conclusions 211
Appendix13A Covariancematrixrank 211
14 Covariancematrixtowaveform 213
14.1 Problemformulation 213
14.2 Cyclicalgorithmforsignalsynthesis 215
14.3 Numericalexamples 216
14.4 Conclusions 219
15 Widebandtransmitbeampatternsynthesis 222
15.1 Problemformulation 222
15.2 Theproposeddesignmethodology 225
15.2.1 Beampatterntospectrum 226
15.2.2 Spectrumtowaveform 227
15.3 Numericalexamples 229
15.3.1 Theidealizedtime-delayedcase 229
15.3.2 Anarrowmainbeam 230
15.3.3 Twomainbeams 233
15.3.4 Awidemainbeam 233
15.4 Conclusions 242
Appendix15A Narrowbandtransmitbeampattern 242
Appendix15B Receivebeampattern 243
PartIV Diverseapplicationexamples 245
16 Radarrangeandrange–Dopplerimaging 247
16.1 Problemformulation 247
16.2 Receiverdesign 249
16.2.1 Matchedfilter 249
16.2.2 Instrumentalvariable(IV)receivefilter 250
16.3 Iterativeadaptiveapproach(IAA) 251
16.4 Numericalexamples 252
16.4.1 NegligibleDopplerexample 252
16.4.2 Non-negligibleDopplerexample 255
16.5 Conclusions 255
17 Ultrasoundsystemforhyperthermiatreatmentofbreastcancer 259
17.1 Waveformdiversitybasedultrasoundhyperthermia 260
17.2 Numericalresults 262
Contents ix
17.3 Conclusions 266
18 Covertunderwateracousticcommunications–coherentscheme 267
18.1 Problemformulation 268
18.2 Spreadingwaveformsynthesis 269
18.3 Numericalexamples 273
18.4 Conclusions 279
19 Covertunderwateracousticcommunications–noncoherentscheme 280
19.1 RAKEenergy-baseddetectionoforthogonalsignals 280
19.2 RAKEdemodulatorforDPSKsignals 283
19.3 TheimpactofPandRonperformanceandanenhancedRAKEscheme 287
19.3.1 ImpactofPandRontheBERperformance 287
19.3.2 RAKEreceptionbasedontheprincipalarrival 288
19.4 Numericalexamples 290
19.4.1 Binaryorthogonalmodulation 290
19.4.2 DPSKmodulation 296
19.5 Conclusions 300
References 301
Index 311