Principles of Modern Radar - Volume 2 1891121537

More documents

Recommendations

Info

9.3 Adaptive Jammer Cancellation 431E (SINR Loss)10.90.80.70.60.50.40.3FIGURE 9-30SINR loss as afunction of the ratioof data samples tochannels.0.20.100 1 2 3 4 5 6 7 8 9 10Snapshots/Channels9.3.4.2 Weight Jitter StabilizationIn addition to SINR loss, errors in estimating the adaptive weights can produce elevatedsidelobes that fluctuate from weight update to weight update. This is known as weightjitter, and it results from poor estimates of the noise eigenvalues in the covariance matrixestimate. The weight jitter can be stabilized by loading the diagonal of the covariancematrix strictly for the purpose of computing the weights [30,31].˜R = ˆR + δI (9.39)Diagonal loading has the effect of swamping out the noise eigenvalues with a fixed syntheticnoise level. Figure 9-31 shows the eigenvalue decomposition for a covariance matrixwith two different levels of diagonal loading indicated. The desired level would be just high60FIGURE 9-31Diagonal loading.7080Diagonal Loading LevelEigenvalue (dB)90100110Diagonal Loading Level1201301400 10 20 30 40 50 60 70 80
432 CHAPTER 9 Adaptive Digital Beamformingenough to cover all the noise eigenvalues without eclipsing any eigenvalues due to jammers.This is because the higher the diagonal loading level, the less jammer cancellationis achieved.9.3.4.3 Cholesky FactorizationThe adaptive weight estimation problem can be formulated as solving a system of linearequations.R x w = vCholesky factorization is a computationally efficient way of solving this problem inO(M 3 /3) operations [32]. The first step is to decompose the covariance matrix asR x = LDL Hwhere L is a lower triangular matrix, and D is a diagonal matrix. Software libraries forperforming this decomposition are widely available [33]. Using this decomposition of thecovariance matrix, the system of equations can be rewritten asLy = vwhere y = DL H w. Since L is a triangular matrix, and v is the known steering vector,it is easy to solve for y by applying back substitution. Once y is known, the weights arecomputed by solving the second triangular system using back substitution.L H w = D −1 yThe covariance based methods for estimating the adaptive weights have the disadvantagethat they involve squaring the data. This squaring causes an increase in dynamic range thatcan lead to numerical problems. If computing precision is limited, then there are methodsusing singular value decomposition or QR decomposition that solve for the adaptiveweights directly from the data without squaring it [34].9.3.5 Performance MetricsPerformance metrics are used to assess the effectiveness of the adaptive filter in cancellinga given jamming scenario. This section will define the most common metrics used forevaluating adaptive cancellation performance. Unfortunately, some of these metrics canbe precisely computed only in simulation and can be estimated or inferred only from hardwaremeasurements. Most of the performance metrics involve taking the ratio of variouscombinations of the signal, jammer, and noise powers with and without adaptive cancellation.Let S u ,J u , and N u be the unadapted signal, jammer, and noise powers, respectively,and S a ,J a , and N a , be the adapted signal, jammer, and noise powers, respectively:• N u = unadapted noise only• S u + N u = unadapted signal plus noise• J u + N u = unadapted jammer plus noise• J a + N a = adapted jammer plus noise• S a + J a + N a = adapted signal plus jammer plus noise
Page 2:
Principles of Modern Radar
Page 5 and 6:
Published by SciTech Publishing, an
Page 8:
Brief ContentsPreface xvPublisher A
Page 11 and 12:
xContents3.6 Adaptive MIMO Radar 10
Page 13 and 14:
xiiContents9.3 Adaptive Jammer Canc
Page 15 and 16:
xivContents15.3 Multisensor Trackin
Page 17 and 18:
xviPrefacehas always been the unlik
Page 19 and 20:
Publisher AcknowledgmentsTechnical
Page 21 and 22:
Editors and ContributorsVolume Edit
Page 23 and 24:
xxiiEditors and ContributorsDr. Lis
Page 25 and 26:
xxivEditors and ContributorsMr. Ara
Page 27 and 28:
2 CHAPTER 1 Overview: Advanced Tech
Page 30 and 31:
1.3 Radar and System Topologies 5FI
Page 32 and 33:
1.4 Topics in Advanced Techniques 7
Page 34 and 35:
Page 36 and 37:
Page 38 and 39:
Page 40 and 41:
1.6 References 15TABLE 1-1Summary o
Page 42:
PART IWaveforms and SpectrumCHAPTER
Page 45 and 46:
20 CHAPTER 2 Advanced Pulse Compres
Page 47 and 48:
Page 49 and 50:
Page 51 and 52:
Page 53:
Page 60 and 61:
2.2 Stretch Processing 35is applied
Page 62:
2.2 Stretch Processing 37TABLE 2-1
Page 67 and 68:
Page 69:
Page 73:
Page 77 and 78:
Page 79 and 80:
Page 81 and 82:
Page 86 and 87:
2.5 Stepped Frequency Waveforms 61T
Page 88:
2.5 Stepped Frequency Waveforms 63w
Page 94 and 95:
2.5 Stepped Frequency Waveforms 69I
Page 97:
Page 101:
Page 106 and 107:
2.9 References 812.7.4 SummaryWhile
Page 108 and 109:
2.9 References 83[27] Taylor, Jr.,
Page 110:
2.10 Problems 85shift across the pu
Page 113:
88 CHAPTER 3 Optimal and Adaptive M
Page 116 and 117:
3.2 Optimum MIMO Waveform Design fo
Page 119 and 120:
Page 121 and 122:
Page 123 and 124:
Page 126 and 127:
3.4 Optimum MIMO Design for Target
Page 128 and 129:
3.4 Optimum MIMO Design for Target
Page 130:
3.5 Constrained Optimum MIMO Radar
Page 133 and 134:
108 CHAPTER 3 Optimal and Adaptive
Page 136:
3.6 Adaptive MIMO Radar 111SINR Los
Page 140 and 141:
3.10 Problems 115[22] W. Y. Hsiang,
Page 142:
3.10 Problems 1179. A constrained o
Page 145:
120 CHAPTER 4 MIMO Radarperformance
Page 148:
4.3 The MIMO Virtual Array 123separ
Page 152 and 153:
4.4 MIMO Radar Signal Processing 12
Page 154 and 155:
Page 156 and 157:
Page 159 and 160:
134 CHAPTER 4 MIMO RadarFIGURE 4-7T
Page 161 and 162:
136 CHAPTER 4 MIMO Radar4.5.2 MIMO
Page 163 and 164:
138 CHAPTER 4 MIMO Radarnamely, R
Page 165 and 166:
140 CHAPTER 4 MIMO RadarTABLE 4-2 P
Page 167 and 168:
142 CHAPTER 4 MIMO RadarSINR Loss (
Page 169 and 170:
144 CHAPTER 4 MIMO Radar[10] H. V.
Page 172 and 173:
Radar Applications of SparseReconst
Page 174 and 175:
5.1 Introduction 149δ = M/N, the u
Page 177 and 178:
152 CHAPTER 5 Radar Applications of
Page 179 and 180:
Page 181 and 182:
Page 183 and 184:
Page 185 and 186:
Page 188 and 189:
5.2 CS Theory 163While the notion o
Page 190 and 191:
5.2 CS Theory 165as , where is a b
Page 192 and 193:
5.3 SR Algorithms 167than the norm
Page 194 and 195:
5.3 SR Algorithms 169the value of o
Page 196 and 197:
5.3 SR Algorithms 171takes special
Page 198 and 199:
5.3 SR Algorithms 173The function f
Page 200 and 201:
5.3 SR Algorithms 175of the TV norm
Page 202 and 203:
5.3 SR Algorithms 177One can argue
Page 204 and 205:
5.3 SR Algorithms 179probability ma
Page 206 and 207:
5.3 SR Algorithms 181only a subset
Page 208 and 209:
5.4 Sample Radar Applications 183pr
Page 210 and 211:
5.4 Sample Radar Applications 185We
Page 212 and 213:
5.4 Sample Radar Applications 187th
Page 214 and 215:
5.4 Sample Radar Applications 189tu
Page 216 and 217:
5.4 Sample Radar Applications 191Ra
Page 218 and 219:
5.4 Sample Radar Applications 193Ta
Page 221 and 222:
Page 223 and 224:
Page 225 and 226:
Page 227 and 228:
Page 229 and 230:
Page 231 and 232:
Page 233 and 234:
Page 236 and 237:
Spotlight SyntheticAperture RadarCH
Page 238 and 239:
6.1 Introduction 213• Image quali
Page 240 and 241:
6.2 Mathematical Background 215andf
Page 242 and 243:
6.2 Mathematical Background 2172π
Page 245:
220 CHAPTER 6 Spotlight Synthetic A
Page 249 and 250:
Page 251 and 252:
Page 253 and 254:
Page 256 and 257:
6.4 Sampling Requirements and Resol
Page 258 and 259:
6.4 Sampling Requirements and Resol
Page 261:
Page 264 and 265:
6.5 Image Reconstruction 239FIGURE
Page 266 and 267:
6.6 Image Metrics 241The contrast r
Page 268 and 269:
6.6 Image Metrics 243Along-track am
Page 270:
6.7 Phase Error Effects 245TABLE 6-
Page 273 and 274:
Page 275 and 276:
Page 277 and 278:
Page 279 and 280:
Page 281 and 282:
Page 283 and 284:
Page 285 and 286:
260 CHAPTER 7 Stripmap SAR3 m SAR O
Page 287 and 288:
262 CHAPTER 7 Stripmap SAR• RMA i
Page 289:
264 CHAPTER 7 Stripmap SARH 0 (ω)
Page 293:
268 CHAPTER 7 Stripmap SARTABLE 7-1
Page 299 and 300:
274 CHAPTER 7 Stripmap SARFIGURE 7-
Page 301:
276 CHAPTER 7 Stripmap SAR−500Sce
Page 310:
7.3 Doppler Beam Sharpening Extensi
Page 313 and 314:
288 CHAPTER 7 Stripmap SARand in th
Page 316 and 317:
7.4 Range-Doppler Algorithms 291to
Page 318:
7.4 Range-Doppler Algorithms 293For
Page 321:
296 CHAPTER 7 Stripmap SAR−150Col
Page 325 and 326:
300 CHAPTER 7 Stripmap SAR33 cycles
Page 327 and 328:
302 CHAPTER 7 Stripmap SARCrossrang
Page 329:
304 CHAPTER 7 Stripmap SARfrom freq
Page 332:
7.5 Range Migration Algorithm 307r,
Page 335:
310 CHAPTER 7 Stripmap SARkx (rad/m
Page 341:
316 CHAPTER 7 Stripmap SARThe diffe
Page 345 and 346:
320 CHAPTER 7 Stripmap SARLet us re
Page 347 and 348:
322 CHAPTER 7 Stripmap SARThe resul
Page 349 and 350:
324 CHAPTER 7 Stripmap SARscene. Th
Page 351 and 352:
326 CHAPTER 7 Stripmap SARdriven by
Page 353 and 354:
328 CHAPTER 7 Stripmap SARTABLE 7-3
Page 355 and 356:
330 CHAPTER 7 Stripmap SARFIGURE 7-
Page 357 and 358:
332 CHAPTER 7 Stripmap SAR7.10 REFE
Page 359 and 360:
334 CHAPTER 7 Stripmap SAR6. [MATLA
Page 362 and 363:
Interferometric SAR andCoherent Exp
Page 364 and 365:
8.1 Introduction 3398.1.1 Organizat
Page 366 and 367:
8.1 Introduction 341Rsabnv rw x ,w
Page 368 and 369:
8.2 Digital Terrain Models 343FIGUR
Page 372 and 373:
8.3 Estimating Elevation Profiles U
Page 374 and 375:
Page 377:
352 CHAPTER 8 Interferometric SAR a
Page 380:
Page 383 and 384:
Page 387 and 388:
Page 390 and 391:
8.5 InSAR Processing Steps 365ξ ta
Page 392:
8.5 InSAR Processing Steps 3670.1 0
Page 395:
Page 398 and 399:
8.5 InSAR Processing Steps 373While
Page 400 and 401:
8.6 Error Sources 375The second met
Page 402 and 403:
8.6 Error Sources 377If sufficient
Page 405 and 406: 380 CHAPTER 8 Interferometric SAR a
Page 413: 388 CHAPTER 8 Interferometric SAR a
Page 426 and 427: Adaptive Digital BeamformingCHAPTER
Page 428: 9.1 Introduction 403c k = clutter s
Page 433 and 434: 408 CHAPTER 9 Adaptive Digital Beam
Page 439: 414 CHAPTER 9 Adaptive Digital Beam
Page 442 and 443: 9.2 Digital Beamforming Fundamental
Page 448: 9.3 Adaptive Jammer Cancellation 42
Page 454 and 455: 9.3 Adaptive Jammer Cancellation 42
Page 458 and 459: 9.3 Adaptive Jammer Cancellation 43
Page 472: 9.5 Wideband Cancellation 447FIGURE
Page 479 and 480: 454 CHAPTER 10 Clutter Suppression
Page 486 and 487: 10.2 Space-Time Signal Representati
Page 492: 10.2 Space-Time Signal Representati
Page 506 and 507:
10.5 STAP Fundamentals 4810−5−1
Page 508 and 509:
10.6 STAP Processing Architectures
Page 510 and 511:
Page 512 and 513:
Page 514 and 515:
Page 516 and 517:
10.7 Other Considerations 4911 CPIM
Page 518 and 519:
10.9 Summary 49310.7.3 Computationa
Page 520 and 521:
10.10 References 495[12] Fenner, D.
Page 522:
10.11 Problems 497the PSD in Figure
Page 526 and 527:
11.2 Colored Space-Time Exploration
Page 528 and 529:
11.2 Colored Space-Time Exploration
Page 531 and 532:
506 CHAPTER 11 Space-Time Coding fo
Page 537:
Page 543 and 544:
Page 545:
Page 550 and 551:
11.8 References 525Cost reduction o
Page 552:
11.9 Problems 52711.9.2 Equivalence
Page 555 and 556:
530 CHAPTER 12 Electronic Protectio
Page 557 and 558:
Page 560:
12.2 Electronic Attack 535TABLE 12-
Page 563:
Page 566 and 567:
12.2 Electronic Attack 541variation
Page 569 and 570:
Page 571 and 572:
Page 573 and 574:
Page 575 and 576:
Page 577 and 578:
Page 579 and 580:
Page 582 and 583:
12.5 Antenna-Based EP 557are adjust
Page 586 and 587:
12.6 Transmitter-Based EP 561polari
Page 589 and 590:
Page 591 and 592:
Page 593 and 594:
Page 595 and 596:
Page 597:
Page 603 and 604:
Page 605:
Page 608 and 609:
12.11 Summary 583TABLE 12-4Summary
Page 610:
12.14 Problems 585[9] Stimson, G.W.
Page 614 and 615:
Introduction to RadarPolarimetryCHA
Page 616 and 617:
13.1 Introduction 591and precipitat
Page 618:
13.1 Introduction 593S: target scat
Page 622 and 623:
13.2 Polarization 597After substitu
Page 624 and 625:
13.2 Polarization 599zFIGURE 13-4Po
Page 626 and 627:
13.3 Scattering Matrix 601left-hand
Page 629 and 630:
604 CHAPTER 13 Introduction to Rada
Page 631 and 632:
Page 633 and 634:
Page 635 and 636:
Page 637:
Page 640 and 641:
13.4 Radar Applications of Polarime
Page 642 and 643:
13.4 Radar Applications of Polarime
Page 644 and 645:
13.5 Measurement of the Scattering
Page 646 and 647:
13.5 Measurement of the Scattering
Page 648 and 649:
13.8 References 623• Lee, Jong-Se
Page 650 and 651:
13.8 References 625[32] Kraus, J.D.
Page 652:
13.9 Problems 627with the result in
Page 656 and 657:
Automatic Target RecognitionCHAPTER
Page 658 and 659:
14.2 Unified Framework for ATR 633P
Page 660 and 661:
14.3 Metrics and Performance Predic
Page 662 and 663:
14.3 Metrics and Performance Predic
Page 664 and 665:
14.4 Synthetic Aperture Radar 639TA
Page 666 and 667:
14.4 Synthetic Aperture Radar 641Te
Page 668 and 669:
14.4 Synthetic Aperture Radar 64314
Page 670 and 671:
14.4 Synthetic Aperture Radar 645Un
Page 672 and 673:
14.4 Synthetic Aperture Radar 64714
Page 674 and 675:
14.4 Synthetic Aperture Radar 649se
Page 676 and 677:
14.4 Synthetic Aperture Radar 651th
Page 678 and 679:
14.5 Inverse Synthetic Aperture Rad
Page 680 and 681:
14.5 Inverse Synthetic Aperture Rad
Page 682 and 683:
14.6 Passive Radar ATR 657radar sys
Page 684 and 685:
14.7 High-Resolution Range Profiles
Page 686 and 687:
14.9 Further Reading 661take a targ
Page 688 and 689:
14.10 References 663[19] Q. H. Pham
Page 690 and 691:
14.10 References 665[56] M. Martore
Page 692 and 693:
14.10 References 667[92] E. Libby,
Page 694 and 695:
Multitarget, MultisensorTrackingCHA
Page 698 and 699:
15.1 Review Of Tracking Concepts 67
Page 700:
15.1 Review Of Tracking Concepts 67
Page 703 and 704:
678 CHAPTER 15 Multitarget, Multise
Page 705 and 706:
Page 708 and 709:
15.2 Multitarget Tracking 683TABLE
Page 710 and 711:
15.2 Multitarget Tracking 685remove
Page 713 and 714:
Page 715 and 716:
Page 717:
Page 720 and 721:
15.5 Further Reading 69515.4 SUMMAR
Page 722 and 723:
15.6 References 697[11] Blair, W.D.
Page 724 and 725:
15.7 Problems 6992. Common metrics
Page 726:
⎡⎤3 0 0 0 0 00 3 0 0 0 0P 2 =0
Page 730 and 731:
Human Detection With Radar:Dismount
Page 732 and 733:
environment that may mask the gener
Page 734 and 735:
D s % = Boulic-Thalmann model param
Page 736 and 737:
16.2 Characterizing the Human Radar
Page 739 and 740:
714 CHAPTER 16 Human Detection With
Page 741 and 742:
Page 743 and 744:
Page 745 and 746:
Page 748 and 749:
16.4 Technical Challenges in Human
Page 750 and 751:
16.4 Technical Challenges in Human
Page 752 and 753:
16.5 Exploiting Knowledge for Detec
Page 754 and 755:
16.7 Further Reading 729enable not
Page 756 and 757:
16.8 References 731[13] Broggi, A.,
Page 758 and 759:
16.8 References 733[53] G.E. Smith,
Page 760 and 761:
16.8 References 735Conference on So
Page 762:
16.9 Problems 737FIGURE 16-13Pendul
Page 765:
740 CHAPTER 17 Advanced Processing
Page 769 and 770:
Page 771 and 772:
Page 773 and 774:
Page 775 and 776:
Page 777 and 778:
Page 779 and 780:
Page 781 and 782:
Page 783 and 784:
Page 786 and 787:
17.3 Direct Signal and Multipath/Cl
Page 788 and 789:
17.3 Direct Signal and Multipath/Cl
Page 791 and 792:
Page 794 and 795:
17.4 Signal Processing Techniques f
Page 796:
17.4 Signal Processing Techniques f
Page 799 and 800:
Page 801 and 802:
Page 803 and 804:
Page 805 and 806:
Page 809:
Page 812:
17.5 2D-CCF Sidelobe Control 787TAB
Page 816 and 817:
17.6 Multichannel Processing for De
Page 819:
Page 822:
Page 828 and 829:
Page 830:
Page 835:
Page 838 and 839:
Page 840 and 841:
17.10 References 815While far from
Page 842 and 843:
17.10 References 817[20] Chetty, K.
Page 844 and 845:
17.11 Problems 819[52] Gao, Z., Tao
Page 846:
17.11 Problems 8215. Using the sign
Page 849 and 850:
824 Appendix A: Answers to Selected
Page 851 and 852:
Page 853:
Page 857 and 858:
ResolutionResolution withDimension
Page 859 and 860:
830 IndexASAR. See Advanced SAR (AS
Page 861 and 862:
832 IndexCross-polarization (XPOL),
Page 863 and 864:
834 IndexExciter-based EP (cont.)fr
Page 865 and 866:
836 IndexInterferencecolored noise,
Page 867 and 868:
838 IndexMoving target indication (
Page 869 and 870:
840 IndexPOI. See Probability of in
Page 871 and 872:
842 IndexSaturated (constant amplit
Page 873 and 874:
844 IndexStripmap SAR (cont.)remote
Page 875 and 876:
846 IndexWWald sequential test, com
show all

Principles of Modern Radar - Volume 2 1891121537

Create successful ePaper yourself

Delete template?

Save as template?