Build your knowledge of SAR/ISAR imaging with this comprehensive and insightful resource
The newly revised Second Edition of Inverse Synthetic Aperture Radar Imaging with MATLAB Algorithms covers in greater detail the fundamental and advanced topics necessary for a complete understanding of inverse synthetic aperture radar (ISAR) imaging and its concepts. Distinguished author and academician, Caner Özdemir, describes the practical aspects of ISAR imaging and presents illustrative examples of the radar signal processing algorithms used for ISAR imaging. The topics in each chapter are supplemented with MATLAB codes to assist readers in better understanding each of the principles discussed within the book.
This new edition incudes discussions of the most up-to-date topics to arise in the field of ISAR imaging and ISAR hardware design. The book provides a comprehensive analysis of advanced techniques like Fourier-based radar imaging algorithms, and motion compensation techniques along with radar fundamentals for readers new to the subject.
The author covers a wide variety of topics, including:
- Radar fundamentals, including concepts like radar cross section, maximum detectable range, frequency modulated continuous wave, and doppler frequency and pulsed radar
- The theoretical and practical aspects of signal processing algorithms used in ISAR imaging
- The numeric implementation of all necessary algorithms in MATLAB
- ISAR hardware, emerging topics on SAR/ISAR focusing algorithms such as bistatic ISAR imaging, polarimetric ISAR imaging, and near-field ISAR imaging,
- Applications of SAR/ISAR imaging techniques to other radar imaging problems such as thru-the-wall radar imaging and ground-penetrating radar imaging
Perfect for graduate students in the fields of electrical and electronics engineering, electromagnetism, imaging radar, and physics, Inverse Synthetic Aperture Radar Imaging With MATLAB Algorithms also belongs on the bookshelves of practicing researchers in the related areas looking for a useful resource to assist them in their day-to-day professional work.
Table of Contents
Preface to the Second Edition xvi
Acknowledgments xix
Acronyms xx
1 Basics of Fourier Analysis 1
1.1 Forward and Inverse Fourier Transform 1
1.1.1 Brief History of FT 1
1.1.2 Forward FT Operation 2
1.1.3 IFT 3
1.2 FT Rules and Pairs 3
1.2.1 Linearity 3
1.2.2 Time Shifting 3
1.2.3 Frequency Shifting 4
1.2.4 Scaling 4
1.2.5 Duality 4
1.2.6 Time Reversal 4
1.2.7 Conjugation 4
1.2.8 Multiplication 4
1.2.9 Convolution 5
1.2.10 Modulation 5
1.2.11 Derivation and Integration 5
1.2.12 Parseval’s Relationship 5
1.3 Time-Frequency Representation of a Signal 5
1.3.1 Signal in the Time Domain 6
1.3.2 Signal in the Frequency Domain 6
1.3.3 Signal in the Joint Time-Frequency (JTF) Plane 7
1.4 Convolution and Multiplication Using FT 11
1.5 Filtering/Windowing 12
1.6 Data Sampling 14
1.7 DFT and FFT 16
1.7.1 DFT 16
1.7.2 FFT 17
1.7.3 Bandwidth and Resolutions 17
1.8 Aliasing 19
1.9 Importance of FT in Radar Imaging 19
1.10 Effect of Aliasing in Radar Imaging 23
1.11 Matlab Codes 26
References 33
2 Radar Fundamentals 35
2.1 Electromagnetic Scattering 35
2.2 Scattering from PECs 38
2.3 Radar Cross Section 39
2.3.1 Definition of RCS 40
2.3.2 RCS of Simple-Shaped Objects 43
2.3.3 RCS of Complex-Shaped Objects 44
2.4 Radar Range Equation 44
2.4.1 Bistatic Case 46
2.4.2 Monostatic Case 49
2.5 Range of Radar Detection 50
2.5.1 Signal-to-Noise Ratio 51
2.6 Radar Waveforms 53
2.6.1 Continuous Wave 53
2.6.2 Frequency-Modulated Continuous Wave 56
2.6.3 Stepped-Frequency Continuous Wave 59
2.6.4 Short Pulse 61
2.6.5 Chirp (LFM) Pulse 62
2.7 Pulsed Radar 69
2.7.1 Pulse Repetition Frequency 69
2.7.2 Maximum Range and Range Ambiguity 69
2.7.3 Doppler Frequency 70
2.8 Matlab Codes 74
References 82
3 Synthetic Aperture Radar 85
3.1 SAR Modes 86
3.2 SAR System Design 87
3.3 Resolutions in SAR 88
3.4 SAR Image Formation 91
3.5 Range Compression 92
3.5.1 Matched Filter 92
3.5.1.1 Computing Matched Filter Output via Fourier Processing 95
3.5.1.2 Example for Matched Filtering 96
3.5.2 Ambiguity Function 99
3.5.2.1 Relation to Matched Filter 100
3.5.2.2 Ideal Ambiguity Function 101
3.5.2.3 Rectangular-Pulse Ambiguity Function 102
3.5.2.4 LFM-Pulse Ambiguity Function 102
3.5.3 Pulse Compression 105
3.5.3.1 Detailed Processing of Pulse Compression 105
3.5.3.2 Bandwidth, Resolution, and Compression Issues for LFM Signal 109
3.5.3.3 Pulse Compression Example 110
3.6 Azimuth Compression 110
3.6.1 Processing in Azimuth 110
3.6.2 Azimuth Resolution 116
3.6.3 Relation to ISAR 117
3.7 SAR Imaging 118
3.8 SAR Focusing Algorithms 118
3.8.1 RDA 119
3.8.1.1 Range Compression in RDA 120
3.8.1.2 Azimuth Fourier Transform 126
3.8.1.3 Range Cell Migration Correction 128
3.8.1.4 Azimuth Compression 129
3.8.1.5 Simulated SAR Imaging Example 130
3.8.1.6 Drawbacks of RDA 133
3.8.2 Chirp Scaling Algorithm 133
3.8.3 The ω-kA 133
3.8.4 Back-Projection Algorithm 134
3.9 Example of a Real SAR Imagery 135
3.10 Problems in SAR Imaging 136
3.10.1 Range Migration and Range Walk 136
3.10.2 Motion Errors 137
3.10.3 Speckle Noise 140
3.11 Advanced Topics in SAR 140
3.11.1 SAR Interferometry 140
3.11.2 SAR Polarimetry 142
3.12 Matlab Codes 143
References 158
4 Inverse Synthetic Aperture Radar Imaging and Its Basic Concepts 162
4.1 SAR versus ISAR 162
4.2 The Relation of Scattered Field to the Image Function in ISAR 166
4.3 One-Dimensional (1D) Range Profile 167
4.4 1D Cross-Range Profile 172
4.5 Two-Dimensional (2D) ISAR Image Formation (Small Bandwidth, Small Angle) 176
4.5.1 Resolutions in ISAR 180
4.5.1.1 Range Resolution 181
4.5.1.2 Cross-Range Resolution: 181
4.5.2 Range and Cross-Range Extends 181
4.5.3 Imaging Multibounces in ISAR 182
4.5.4 Sample Design Procedure for ISAR 185
4.5.4.1 ISAR Design Example #1: “Aircraft Target” 189
4.5.4.2 ISAR Design Example #2: “Military Tank Target” 193
4.6 2D ISAR Image Formation (Wide Bandwidth, Large Angles) 197
4.6.1 Direct Integration 198
4.6.2 Polar Reformatting 201
4.7 3D ISAR Image Formation 205
4.7.1 Range and Cross-Range resolutions 209
4.7.2 A Design Example for 3D ISAR 210
4.8 Matlab Codes 217
References 243
5 Imaging Issues in Inverse Synthetic Aperture Radar 246
5.1 Fourier-Related Issues 246
5.1.1 DFT Revisited 246
5.1.2 Positive and Negative Frequencies in DFT 250
5.2 Image Aliasing 252
5.3 Polar Reformatting Revisited 255
5.3.1 Nearest Neighbor Interpolation 255
5.3.2 Bilinear Interpolation 258
5.4 Zero Padding 260
5.5 Point Spread Function 264
5.6 Windowing 269
5.6.1 Common Windowing Functions 269
5.6.1.1 Rectangular Window 269
5.6.1.2 Triangular Window 269
5.6.1.3 Hanning Window 272
5.6.1.4 Hamming Window 272
5.6.1.5 Kaiser Window 272
5.6.1.6 Blackman Window 276
5.6.1.7 Chebyshev Window 277
5.6.2 ISAR Image Smoothing via Windowing 277
5.7 Matlab Codes 280
References 304
6 Range-Doppler Inverse Synthetic Aperture Radar Processing 306
6.1 Scenarios for ISAR 306
6.1.1 Imaging Aerial Targets via Ground-Based Radar 307
6.1.2 Imaging Ground/Sea Targets via Aerial Radar 309
6.2 ISAR Waveforms for Range-Doppler Processing 312
6.2.1 Chirp Pulse Train 312
6.2.2 Stepped Frequency Pulse Train 314
6.3 Doppler Shift’s Relation to Cross-Range 316
6.3.1 Doppler Frequency Shift Resolution 317
6.3.2 Resolving Doppler Shift and Cross-Range 318
6.4 Forming the Range-Doppler Image 319
6.5 ISAR Receiver 320
6.5.1 ISAR Receiver for Chirp Pulse Radar 320
6.5.2 ISAR Receiver for SFCW Radar 321
6.6 Quadrature Detection 323
6.6.1 I-Channel Processing 324
6.6.2 Q-Channel Processing 324
6.7 Range Alignment 326
6.8 Defining the Range-Doppler ISAR Imaging Parameters 327
6.8.1 Image Frame Dimension (Image Extends) 327
6.8.2 Range and Cross-Range Resolution 328
6.8.3 Frequency Bandwidth and the Center Frequency 328
6.8.4 Doppler Frequency Bandwidth 328
6.8.5 Pulse Repetition Frequency 329
6.8.6 Coherent Integration (Dwell) Time 329
6.8.7 Pulse Width 330
6.9 Example of Chirp Pulse-Based Range-Doppler ISAR Imaging 331
6.10 Example of SFCW-Based Range-Doppler ISAR Imaging 336
6.11 Matlab Codes 339
References 347
7 Scattering Center Representation of Inverse Synthetic Aperture Radar 349
7.1 Scattering/Radiation Center Model 350
7.2 Extraction of Scattering Centers 352
7.2.1 Image Domain Formulation 352
7.2.1.1 Extraction in the Image Domain: The “CLEAN” Algorithm 352
7.2.1.2 Reconstruction in the Image Domain 355
7.2.2 Fourier Domain Formulation 362
7.2.2.1 Extraction in the Fourier Domain 362
7.2.2.2 Reconstruction in the Fourier Domain 364
7.3 Matlab Codes 368
References 382
8 Motion Compensation for Inverse Synthetic Aperture Radar 385
8.1 Doppler Effect Due to Target Motion 386
8.2 Standard MOCOMP Procedures 388
8.2.1 Translational MOCOMP 389
8.2.1.1 Range Tracking 389
8.2.1.2 Doppler Tracking 390
8.2.2 Rotational MOCOMP 390
8.3 Popular ISAR MOCOMP Techniques 392
8.3.1 Cross-Correlation Method 392
8.3.1.1 Example for the Cross-Correlation Method 394
8.3.2 Minimum Entropy Method 398
8.3.2.1 Definition of Entropy in ISAR Images 398
8.3.2.2 Example for the Minimum Entropy Method 399
8.3.3 JTF-Based MOCOMP 402
8.3.3.1 Received Signal from a Moving Target 403
8.3.3.2 An Algorithm for JTF-Based Rotational MOCOMP 404
8.3.3.3 Example for JTF-Based Rotational MOCOMP 406
8.3.4 Algorithm for JTF-Based Translational and RotationalMOCOMP 408
8.3.4.1 A Numerical Example 410
8.4 Matlab Codes 415
References 436
9 Bistatic ISAR Imaging 440
9.1 Why Bi-ISAR Imaging? 440
9.2 Geometry for Bi-Isar Imaging and the Algorithm 444
9.2.1 Bi-ISAR Imaging Algorithm for a Point Scatterer 444
9.2.2 Bistatic ISAR Imaging Algorithm for a Target 448
9.3 Resolutions in Bistatic ISAR 449
9.3.1 Range Resolution 449
9.3.2 Cross-Range Resolution 450
9.3.3 Range and Cross-Range Extends 451
9.4 Design Procedure for Bi-ISAR Imaging 452
9.5 Bi-Isar Imaging Examples 455
9.5.1 Bi-ISAR Design Example #1 455
9.5.2 Bi-ISAR Design Example #2 457
9.6 Mu-ISAR Imaging 465
9.6.1 Challenges in Mu-ISAR Imaging 467
9.6.2 Mu-ISAR Imaging Example 468
9.7 Matlab Codes 472
References 483
10 Polarimetric ISAR Imaging 484
10.1 Polarization of an Electromagnetic Wave 484
10.1.1 Polarization Type 485
10.1.2 Polarization Sensitivity 486
10.1.3 Polarization in Radar Systems 487
10.2 Polarization Scattering Matrix 488
10.2.1 Relation to RCS 490
10.2.2 Polarization Characteristics of the Scattered Wave 491
10.2.3 Polarimetric Decompositions of EM Wave Scattering 493
10.2.4 The Pauli Decomposition 494
10.2.4.1 Description of Pauli Decomposition 494
10.2.4.2 Interpretation of Pauli Decomposition 495
10.2.4.3 Polarimetric Image Representation Using Pauli Decomposition 496
10.3 Why Polarimetric ISAR Imaging? 497
10.4 ISAR Imaging with Full Polarization 497
10.4.1 ISAR Data in LP Basis 497
10.4.2 ISAR Data in CP Basis 498
10.5 Polarimetric ISAR Images 499
10.5.1 Pol-ISAR Image of a Benchmark Target 499
10.5.1.1 The “SLICY” Target 499
10.5.1.2 Fully Polarimetric EM Simulation of SLICY 499
10.5.1.3 LP Pol-ISAR Images of SLICY 500
10.5.1.4 CP Pol-ISAR Images of SLICY 502
10.5.1.5 Pauli Decomposition Image of SLICY 503
10.5.2 Pol-ISAR Image of a Complex Target 507
10.5.2.1 The “Military Tank” Target 507
10.5.2.2 Fully Polarimetric EM Simulation of “Tank” Target 508
10.5.2.3 LP Pol-ISAR Images of “Tank” Target 508
10.5.2.4 CP Pol-ISAR Images of “Tank” Target 510
10.5.2.5 Pauli Decomposition Image of “Tank” Target 512
10.6 Feature Extraction from Polarimetric Images 515
10.7 Matlab Codes 515
References 529
11 Near-Field ISAR Imaging 533
11.1 Definitions of Far and Near-Field Regions 534
11.1.1 The Far-Field Region 534
11.1.1.1 The Far-Field Definition Based on Target’s Cross-Range Extend 534
11.1.1.2 The Far-Field Definition Based on Target’s Range Extend 535
11.1.2 The Near-Field Region 537
11.2 Near-Field Signal Model for the Back-Scattered Field 537
11.3 Near-Field ISAR Imaging Algorithms 540
11.3.1 “Focusing Operator” Algorithm 540
11.3.2 Back-Projection Algorithm 541
11.3.2.1 Fourier Slice Theorem 542
11.3.2.2 BPA Formulation (3D Case) 543
11.3.2.3 BPA Formulation (2D Case) 544
11.4 Data Sampling Criteria and the Resolutions 546
11.5 Near-Field ISAR Imaging Examples 547
11.5.1 Point Scatterers in the Near-Field: Comparison of Far- and Near-Field Imaging Algorithms 547
11.5.2 Near-Field ISAR Imaging of a Large Object 552
11.5.3 Near-Field ISAR Imaging of a Small Object 555
11.6 Matlab Codes 560
References 569
12 Some Imaging Applications Based on SAR/ISAR 571
12.1 Imaging Subsurface Objects: GPR-SAR 572
12.1.1 The GPR Problem 572
12.1.2 B-Scan GPR in Comparison to Strip-Map SAR 577
12.1.3 Focused GPR Images Using SAR 577
12.1.3.1 GPR Focusing with ω-k Algorithm (ω-kA) 579
12.1.3.2 GPR Focusing with BPA 582
12.1.3.3 Other Popular GPR Focusing Techniques 589
12.2 Thru-the-Wall Imaging Radar Using SAR 590
12.2.1 Challenges in TWIR 591
12.2.2 Techniques to Improve Cross-Range Resolution in TWIR 591
12.2.3 The Use of SAR in TWIR 592
12.2.4 Example of SAR-Based TWIR 594
12.3 Imaging Antenna-Platform Scattering: ASAR 596
12.3.1 The ASAR Imaging Algorithm 597
12.3.2 Numerical Example for ASAR Imagery 603
12.4 Imaging Platform Coupling Between Antennas: ACSAR 605
12.4.1 The ACSAR Imaging Algorithm 606
12.4.2 Numerical Example for ACSAR 609
12.4.3 Applying ACSAR Concept to the GPR Problem 611
References 615
Appendix 619
Index 628
