Inverse Synthetic Aperture Radar Imaging with MATLAB Algorithms

ISBN-13: 9781119521334 / Angielski / Twarda / 2021 / 672 str.

Caner Ozdemir

Spis treści

Preface to the Second Edition xviAcknowledgments xixAcronyms xx1 Basics of Fourier Analysis 11.1 Forward and Inverse Fourier Transform 11.1.1 Brief History of FT 11.1.2 Forward FT Operation 21.1.3 IFT 31.2 FT Rules and Pairs 31.2.1 Linearity 31.2.2 Time Shifting 31.2.3 Frequency Shifting 41.2.4 Scaling 41.2.5 Duality 41.2.6 Time Reversal 41.2.7 Conjugation 41.2.8 Multiplication 41.2.9 Convolution 51.2.10 Modulation 51.2.11 Derivation and Integration 51.2.12 Parseval's Relationship 51.3 Time-Frequency Representation of a Signal 51.3.1 Signal in the Time Domain 61.3.2 Signal in the Frequency Domain 61.3.3 Signal in the Joint Time-Frequency (JTF) Plane 71.4 Convolution and Multiplication Using FT 111.5 Filtering/Windowing 121.6 Data Sampling 141.7 DFT and FFT 161.7.1 DFT 161.7.2 FFT 171.7.3 Bandwidth and Resolutions 171.8 Aliasing 191.9 Importance of FT in Radar Imaging 191.10 Effect of Aliasing in Radar Imaging 231.11 Matlab Codes 26References 332 Radar Fundamentals 352.1 Electromagnetic Scattering 352.2 Scattering from PECs 382.3 Radar Cross Section 392.3.1 Definition of RCS 402.3.2 RCS of Simple-Shaped Objects 432.3.3 RCS of Complex-Shaped Objects 442.4 Radar Range Equation 442.4.1 Bistatic Case 462.4.2 Monostatic Case 492.5 Range of Radar Detection 502.5.1 Signal-to-Noise Ratio 512.6 Radar Waveforms 532.6.1 Continuous Wave 532.6.2 Frequency-Modulated Continuous Wave 562.6.3 Stepped-Frequency Continuous Wave 592.6.4 Short Pulse 612.6.5 Chirp (LFM) Pulse 622.7 Pulsed Radar 692.7.1 Pulse Repetition Frequency 692.7.2 Maximum Range and Range Ambiguity 692.7.3 Doppler Frequency 702.8 Matlab Codes 74References 823 Synthetic Aperture Radar 853.1 SAR Modes 863.2 SAR System Design 873.3 Resolutions in SAR 883.4 SAR Image Formation 913.5 Range Compression 923.5.1 Matched Filter 923.5.1.1 Computing Matched Filter Output via Fourier Processing 953.5.1.2 Example for Matched Filtering 963.5.2 Ambiguity Function 993.5.2.1 Relation to Matched Filter 1003.5.2.2 Ideal Ambiguity Function 1013.5.2.3 Rectangular-Pulse Ambiguity Function 1023.5.2.4 LFM-Pulse Ambiguity Function 1023.5.3 Pulse Compression 1053.5.3.1 Detailed Processing of Pulse Compression 1053.5.3.2 Bandwidth, Resolution, and Compression Issues for LFM Signal 1093.5.3.3 Pulse Compression Example 1103.6 Azimuth Compression 1103.6.1 Processing in Azimuth 1103.6.2 Azimuth Resolution 1163.6.3 Relation to ISAR 1173.7 SAR Imaging 1183.8 SAR Focusing Algorithms 1183.8.1 RDA 1193.8.1.1 Range Compression in RDA 1203.8.1.2 Azimuth Fourier Transform 1263.8.1.3 Range Cell Migration Correction 1283.8.1.4 Azimuth Compression 1293.8.1.5 Simulated SAR Imaging Example 1303.8.1.6 Drawbacks of RDA 1333.8.2 Chirp Scaling Algorithm 1333.8.3 The omega-kA 1333.8.4 Back-Projection Algorithm 1343.9 Example of a Real SAR Imagery 1353.10 Problems in SAR Imaging 1363.10.1 Range Migration and Range Walk 1363.10.2 Motion Errors 1373.10.3 Speckle Noise 1403.11 Advanced Topics in SAR 1403.11.1 SAR Interferometry 1403.11.2 SAR Polarimetry 1423.12 Matlab Codes 143References 1584 Inverse Synthetic Aperture Radar Imaging and Its Basic Concepts 1624.1 SAR versus ISAR 1624.2 The Relation of Scattered Field to the Image Function in ISAR 1664.3 One-Dimensional (1D) Range Profile 1674.4 1D Cross-Range Profile 1724.5 Two-Dimensional (2D) ISAR Image Formation (Small Bandwidth, Small Angle) 1764.5.1 Resolutions in ISAR 1804.5.1.1 Range Resolution 1814.5.1.2 Cross-Range Resolution: 1814.5.2 Range and Cross-Range Extends 1814.5.3 Imaging Multibounces in ISAR 1824.5.4 Sample Design Procedure for ISAR 1854.5.4.1 ISAR Design Example #1: "Aircraft Target" 1894.5.4.2 ISAR Design Example #2: "Military Tank Target" 1934.6 2D ISAR Image Formation (Wide Bandwidth, Large Angles) 1974.6.1 Direct Integration 1984.6.2 Polar Reformatting 2014.7 3D ISAR Image Formation 2054.7.1 Range and Cross-Range resolutions 2094.7.2 A Design Example for 3D ISAR 2104.8 Matlab Codes 217References 2435 Imaging Issues in Inverse Synthetic Aperture Radar 2465.1 Fourier-Related Issues 2465.1.1 DFT Revisited 2465.1.2 Positive and Negative Frequencies in DFT 2505.2 Image Aliasing 2525.3 Polar Reformatting Revisited 2555.3.1 Nearest Neighbor Interpolation 2555.3.2 Bilinear Interpolation 2585.4 Zero Padding 2605.5 Point Spread Function 2645.6 Windowing 2695.6.1 Common Windowing Functions 2695.6.1.1 Rectangular Window 2695.6.1.2 Triangular Window 2695.6.1.3 Hanning Window 2725.6.1.4 Hamming Window 2725.6.1.5 Kaiser Window 2725.6.1.6 Blackman Window 2765.6.1.7 Chebyshev Window 2775.6.2 ISAR Image Smoothing via Windowing 2775.7 Matlab Codes 280References 3046 Range-Doppler Inverse Synthetic Aperture Radar Processing 3066.1 Scenarios for ISAR 3066.1.1 Imaging Aerial Targets via Ground-Based Radar 3076.1.2 Imaging Ground/Sea Targets via Aerial Radar 3096.2 ISAR Waveforms for Range-Doppler Processing 3126.2.1 Chirp Pulse Train 3126.2.2 Stepped Frequency Pulse Train 3146.3 Doppler Shift's Relation to Cross-Range 3166.3.1 Doppler Frequency Shift Resolution 3176.3.2 Resolving Doppler Shift and Cross-Range 3186.4 Forming the Range-Doppler Image 3196.5 ISAR Receiver 3206.5.1 ISAR Receiver for Chirp Pulse Radar 3206.5.2 ISAR Receiver for SFCW Radar 3216.6 Quadrature Detection 3236.6.1 I-Channel Processing 3246.6.2 Q-Channel Processing 3246.7 Range Alignment 3266.8 Defining the Range-Doppler ISAR Imaging Parameters 3276.8.1 Image Frame Dimension (Image Extends) 3276.8.2 Range and Cross-Range Resolution 3286.8.3 Frequency Bandwidth and the Center Frequency 3286.8.4 Doppler Frequency Bandwidth 3286.8.5 Pulse Repetition Frequency 3296.8.6 Coherent Integration (Dwell) Time 3296.8.7 Pulse Width 3306.9 Example of Chirp Pulse-Based Range-Doppler ISAR Imaging 3316.10 Example of SFCW-Based Range-Doppler ISAR Imaging 3366.11 Matlab Codes 339References 3477 Scattering Center Representation of Inverse Synthetic Aperture Radar 3497.1 Scattering/Radiation Center Model 3507.2 Extraction of Scattering Centers 3527.2.1 Image Domain Formulation 3527.2.1.1 Extraction in the Image Domain: The "CLEAN" Algorithm 3527.2.1.2 Reconstruction in the Image Domain 3557.2.2 Fourier Domain Formulation 3627.2.2.1 Extraction in the Fourier Domain 3627.2.2.2 Reconstruction in the Fourier Domain 3647.3 Matlab Codes 368References 3828 Motion Compensation for Inverse Synthetic Aperture Radar 3858.1 Doppler Effect Due to Target Motion 3868.2 Standard MOCOMP Procedures 3888.2.1 Translational MOCOMP 3898.2.1.1 Range Tracking 3898.2.1.2 Doppler Tracking 3908.2.2 Rotational MOCOMP 3908.3 Popular ISAR MOCOMP Techniques 3928.3.1 Cross-Correlation Method 3928.3.1.1 Example for the Cross-Correlation Method 3948.3.2 Minimum Entropy Method 3988.3.2.1 Definition of Entropy in ISAR Images 3988.3.2.2 Example for the Minimum Entropy Method 3998.3.3 JTF-Based MOCOMP 4028.3.3.1 Received Signal from a Moving Target 4038.3.3.2 An Algorithm for JTF-Based Rotational MOCOMP 4048.3.3.3 Example for JTF-Based Rotational MOCOMP 4068.3.4 Algorithm for JTF-Based Translational and RotationalMOCOMP 4088.3.4.1 A Numerical Example 4108.4 Matlab Codes 415References 4369 Bistatic ISAR Imaging 4409.1 Why Bi-ISAR Imaging? 4409.2 Geometry for Bi-Isar Imaging and the Algorithm 4449.2.1 Bi-ISAR Imaging Algorithm for a Point Scatterer 4449.2.2 Bistatic ISAR Imaging Algorithm for a Target 4489.3 Resolutions in Bistatic ISAR 4499.3.1 Range Resolution 4499.3.2 Cross-Range Resolution 4509.3.3 Range and Cross-Range Extends 4519.4 Design Procedure for Bi-ISAR Imaging 4529.5 Bi-Isar Imaging Examples 4559.5.1 Bi-ISAR Design Example #1 4559.5.2 Bi-ISAR Design Example #2 4579.6 Mu-ISAR Imaging 4659.6.1 Challenges in Mu-ISAR Imaging 4679.6.2 Mu-ISAR Imaging Example 4689.7 Matlab Codes 472References 48310 Polarimetric ISAR Imaging 48410.1 Polarization of an Electromagnetic Wave 48410.1.1 Polarization Type 48510.1.2 Polarization Sensitivity 48610.1.3 Polarization in Radar Systems 48710.2 Polarization Scattering Matrix 48810.2.1 Relation to RCS 49010.2.2 Polarization Characteristics of the Scattered Wave 49110.2.3 Polarimetric Decompositions of EM Wave Scattering 49310.2.4 The Pauli Decomposition 49410.2.4.1 Description of Pauli Decomposition 49410.2.4.2 Interpretation of Pauli Decomposition 49510.2.4.3 Polarimetric Image Representation Using Pauli Decomposition 49610.3 Why Polarimetric ISAR Imaging? 49710.4 ISAR Imaging with Full Polarization 49710.4.1 ISAR Data in LP Basis 49710.4.2 ISAR Data in CP Basis 49810.5 Polarimetric ISAR Images 49910.5.1 Pol-ISAR Image of a Benchmark Target 49910.5.1.1 The "SLICY" Target 49910.5.1.2 Fully Polarimetric EM Simulation of SLICY 49910.5.1.3 LP Pol-ISAR Images of SLICY 50010.5.1.4 CP Pol-ISAR Images of SLICY 50210.5.1.5 Pauli Decomposition Image of SLICY 50310.5.2 Pol-ISAR Image of a Complex Target 50710.5.2.1 The "Military Tank" Target 50710.5.2.2 Fully Polarimetric EM Simulation of "Tank" Target 50810.5.2.3 LP Pol-ISAR Images of "Tank" Target 50810.5.2.4 CP Pol-ISAR Images of "Tank" Target 51010.5.2.5 Pauli Decomposition Image of "Tank" Target 51210.6 Feature Extraction from Polarimetric Images 51510.7 Matlab Codes 515References 52911 Near-Field ISAR Imaging 53311.1 Definitions of Far and Near-Field Regions 53411.1.1 The Far-Field Region 53411.1.1.1 The Far-Field Definition Based on Target's Cross-Range Extend 53411.1.1.2 The Far-Field Definition Based on Target's Range Extend 53511.1.2 The Near-Field Region 53711.2 Near-Field Signal Model for the Back-Scattered Field 53711.3 Near-Field ISAR Imaging Algorithms 54011.3.1 "Focusing Operator" Algorithm 54011.3.2 Back-Projection Algorithm 54111.3.2.1 Fourier Slice Theorem 54211.3.2.2 BPA Formulation (3D Case) 54311.3.2.3 BPA Formulation (2D Case) 54411.4 Data Sampling Criteria and the Resolutions 54611.5 Near-Field ISAR Imaging Examples 54711.5.1 Point Scatterers in the Near-Field: Comparison of Far- and Near-Field Imaging Algorithms 54711.5.2 Near-Field ISAR Imaging of a Large Object 55211.5.3 Near-Field ISAR Imaging of a Small Object 55511.6 Matlab Codes 560References 56912 Some Imaging Applications Based on SAR/ISAR 57112.1 Imaging Subsurface Objects: GPR-SAR 57212.1.1 The GPR Problem 57212.1.2 B-Scan GPR in Comparison to Strip-Map SAR 57712.1.3 Focused GPR Images Using SAR 57712.1.3.1 GPR Focusing with omega-k Algorithm (omega-kA) 57912.1.3.2 GPR Focusing with BPA 58212.1.3.3 Other Popular GPR Focusing Techniques 58912.2 Thru-the-Wall Imaging Radar Using SAR 59012.2.1 Challenges in TWIR 59112.2.2 Techniques to Improve Cross-Range Resolution in TWIR 59112.2.3 The Use of SAR in TWIR 59212.2.4 Example of SAR-Based TWIR 59412.3 Imaging Antenna-Platform Scattering: ASAR 59612.3.1 The ASAR Imaging Algorithm 59712.3.2 Numerical Example for ASAR Imagery 60312.4 Imaging Platform Coupling Between Antennas: ACSAR 60512.4.1 The ACSAR Imaging Algorithm 60612.4.2 Numerical Example for ACSAR 60912.4.3 Applying ACSAR Concept to the GPR Problem 611References 615Appendix 619Index 628

O autorze

CANER ÖZDEMIR, PHD, teaches undergraduate and graduate courses on electromagnetics, antennas, radar, and signal processing at Mersin University in Turkey. He has published over 150 scientific journal articles and is the recipient of the URSI EMT-S Young Scientist Award in the 2004 International Symposium on Electromagnetic Theory, as well as the 2016 Best Paper Award in SPIE-Journal of Applied Remote Sensing.