Advanced Signal Processing Handbook: Theory and Implementation for Radar, Sonar, and Medical Imaging Real Time Systems

Advanced Signal Processing Handbook: Theory and Implementation for Radar, Sonar & Medical Imaging Real-Time Systems......Page 1
Copyright......Page 2
Preface......Page 3
Editor......Page 5
Contributors......Page 6
Dedication......Page 8
Contents......Page 9
1.2 Overview of a Real-Time System......Page 14
1.3 Signal Processor......Page 16
1.3.2 Tomography Imaging CT/X-Ray and MRI Systems......Page 18
1.3.4 Active and Passive Systems......Page 20
1.4 Data Manager and Display Sub-System......Page 21
1.4.1 Post-Processing for Sonar and Radar Systems......Page 22
1.4.2 Post-Processing for Medical Imaging Systems......Page 24
1.4.3 Signal and Target Tracking and Target Motion Analysis......Page 27
1.4.5 Multi-Sensor Data Fusion......Page 30
References......Page 32
2.1 The Filtering Problem......Page 34
2.2 Adaptive Filters......Page 35
2.3.1 Transversal Filter......Page 37
2.3.2 Lattice Predictor......Page 38
2.3.3 Systolic Array......Page 40
2.4 Approaches to the Development of Linear Adaptive Filtering Algorithms......Page 41
2.4.1 Stochastic Gradient Approach......Page 42
2.4.2 Least-Squares Estimation......Page 44
2.5 Real and Complex Forms of Adaptive Filters......Page 46
2.6 Nonlinear Adaptive Systems: Neural Networks......Page 47
2.6.1.1 Multilayer Perceptrons and Back-Propagation Learning......Page 48
2.6.1.2 Radial-Basis Function (RBF) Networks......Page 51
2.6.2.1 Principal Components Analysis......Page 53
2.6.2.2 Self-Organizing Maps......Page 54
2.6.5 Dynamically Driven Recurrent Networks......Page 55
2.7 Applications......Page 57
2.7.1 System Identification......Page 60
2.7.2 Spectrum Estimation......Page 62
2.7.3 Signal Detection......Page 63
2.7.4 Target Tracking......Page 65
2.7.5 Adaptive Noise Canceling......Page 68
2.7.6 Adaptive Beamforming......Page 73
2.7.6.1 Adaptive Beamformer with Minimum-Variance Distortionless Response......Page 74
2.7.6.2 Adaptation in Beam Space......Page 76
2.8 Concluding Remarks......Page 78
References......Page 79
Nomenclature......Page 82
3.1 Introduction......Page 83
3.2.1 The Approximation Theorem......Page 85
3.2.2 The Identifiability Problem......Page 86
Proof......Page 87
3.3.1 The Maximum Likelihood Approach......Page 88
3.3.2 The Stochastic Gradient Descent Approach......Page 89
3.3.3 The EM Approach......Page 90
3.3.4 The EM Algorithm for Adaptive Mixtures......Page 93
3.4 Computer Generation of Mixture Variables......Page 94
3.5 Mixture Applications......Page 96
3.5.1 Applications to Non-Linear Filtering......Page 97
3.5.2 Non-Gaussian Noise Modeling......Page 102
3.5.3 Radial-Basis Functions (RBF) Networks......Page 107
References......Page 113
4.1 Introduction......Page 117
4.2.1 Basic Concept and Formulation......Page 118
4.2.2 Identifiability......Page 119
4.2.3 Bartlett Matched Field Processor Family......Page 120
4.3.2 Deterministic Sources......Page 125
4.3.3 Non-Stationary Random Sources......Page 127
4.3.4 Wide-Sense Stationary Random Sources......Page 129
4.4.1 Background Theory......Page 130
4.4.2 Formulation......Page 132
4.5.1 Background Theory......Page 133
4.5.2 Formulation......Page 135
4.6.1 Simulation Results......Page 138
4.6.2 Experimental Results......Page 142
References......Page 145
Abstract......Page 148
5.1 Introduction......Page 149
5.2.1 Motivation......Page 152
5.2.2 Overview......Page 156
5.2.4 Model-Based Processor (Kalman Filter)......Page 157
5.2.6 Extended Kalman Filter......Page 159
5.2.7 Model-Based Processor Design Methodology......Page 160
5.3 State-Space Ocean Acoustic Forward Propagators......Page 163
5.4.1 Ocean Acoustic Data: Hudson Canyon Experimental Data......Page 171
5.4.2 Ocean Acoustic Application: Adaptive Model-Based Signal Enhancement......Page 173
5.4.2.1 Model-Based Signal Enhancement: Parametrically Adaptive Model......Page 174
5.4.3 Ocean Acoustic Application: Adaptive Environmental Inversion......Page 179
5.4.3.1 Adaptive Environmental Inversion: Augmented Gauss-Markov Model......Page 181
5.4.3.2 Adaptive Environmental Inversion: Sound Speed Estimation......Page 182
5.4.4.1 Model-Based Localization: Non-Linear Optimizer......Page 184
5.4.4.2 Model-Based Localization: Parametrically Adaptive Processor......Page 187
5.4.4.3 Model-Based Localization: Application to Hudson Canyon Data......Page 188
5.4.5 Ocean Acoustic Application: Model-Based Towed Array Processor......Page 191
5.4.5.1 Model-Based Towed Array Processor: Adaptive Processing......Page 192
5.4.6 Model-Based Towed Array Processor: Application to Synthetic Data......Page 194
5.5 Summary......Page 197
References......Page 198
Abbreviations and Symbols......Page 201
6.1 Introduction......Page 203
6.2 Background......Page 204
6.3.1 Space-Time Processing......Page 207
6.3.2 Definition of Basic Parameters......Page 209
6.3.3 Detection and Estimation......Page 210
6.3.4 Cramer-Rao Lower Bound (CRLB) Analysis......Page 212
6.4 Optimum Estimators for Array Signal Processing......Page 214
6.4.1.1 Linear Array Conventional Beamformer......Page 215
6.4.2 Multi-Dimensional (3-D) Array Conventional Beamformer......Page 218
6.4.2.1.2 Planar Array Beamformer......Page 219
6.4.3 Influence of the Medium’s Propagation Characteristics on the Performance of a Receiving Array......Page 222
6.4.4 Array Gain......Page 225
6.5.1 Synthetic Aperture Processing......Page 226
6.5.1.1 FFT Based Synthetic Aperture Processing (FFTSA Method)......Page 227
6.5.1.2 Yen and Carey's Synthetic Aperture Method......Page 229
6.5.1.4 Spatial Overlap Correlator for Synthetic Aperture Processing (ETAM Method)......Page 230
6.5.2.1 Minimum Variance Distortionless Response (MVDR)......Page 233
6.5.2.2 Generalized Sidelobe Canceller (GSC)......Page 234
6.5.2.3 Steered Minimum Variance (STMV) Broadband Adaptive Beamformer......Page 235
6.6 Implementation Considerations......Page 237
6.6.1 Evaluation of Convergence Properties of Adaptive Schemes......Page 239
6.6.1.1 Convergence Characteristics of GSC and GSC-SA Beamformers......Page 240
6.6.1.2 Convergence Characteristics of STMV and STMV-SA Beamformers......Page 241
6.6.2.1 Sub-Aperture Configuration for Line Arrays......Page 242
6.6.2.2 Sub-Aperture Configuration for Circular Array......Page 243
6.6.2.3 Sub-Aperture Configuration for Cylindrical Array......Page 245
6.6.3 Signal Processing Flow of a 3-D Generic Sub-Aperture Structure......Page 247
6.7 Concept Demonstration: Simulations and Experimental Results......Page 251
6.7.1.1 Synthetic Data: Passive......Page 253
6.7.1.2 Synthetic Data: Active......Page 255
6.7.1.3 Real Data......Page 260
6.7.2.1.1 Narrowband CW Pulses......Page 262
6.7.2.1.2 Broadband FM Pulses......Page 265
6.8 Conclusion......Page 266
References......Page 267
Abstract......Page 270
7.1.2 Methods......Page 271
7.1.2.1 Preprocessing......Page 272
7.1.2.2.1 Point-Based Segmentation......Page 273
7.1.2.2.2 Edge-Based Segmentation......Page 274
7.1.2.2.3 Region-Based Segmentation......Page 276
7.1.2.3 Surface-Based Rendering......Page 277
7.1.2.4 Volume-Based Rendering......Page 279
7.1.2.7 Intelligent Visualization......Page 284
7.1.2.9 Image Quality......Page 285
7.2.1 Radiological Data......Page 287
7.2.4.1 Introduction......Page 290
7.2.4.2 Collecting 3D Ultrasound Data......Page 292
7.2.4.3 Visualization of 3D Ultrasound......Page 293
7.2.5 3D Cardiac Reconstruction from 2D Projections......Page 296
7.2.5.1.1 Introduction......Page 297
7.2.5.1.3 Occlusal Surface Restoration......Page 298
7.2.5.2 Reconstruction of Coronary Vessels......Page 299
7.2.5.3 Reconstruction of Ventricles......Page 303
7.2.6 Visualization of Laser Confocal Microscopy Data Sets......Page 304
7.2.7.2 Proposed "Virtual Simulation"......Page 311
7.2.8 Conclusions......Page 312
References......Page 316
A7.1 Introduction......Page 323
A7.3 The Fourier Transform......Page 324
A7.4 Grey Scale Manipulation Techniques......Page 326
A7.4.2 Image Windowing Techniques......Page 327
A7.5.3 High-Pass Filtering......Page 328
A7.6.1 Local Averaging Masks......Page 331
A7.6.3 Gaussian Filter......Page 332
A7.6.4 Low-Pass Filtering......Page 334
A7.7.1 Laplacian Operator......Page 336
A7.7.2 Prewitt, Sobel, and Robinson Operators......Page 337
References......Page 338
Frequently Used Symbols......Page 340
8.1.1 Tracking Systems......Page 342
8.1.3 Bayesian Approach......Page 343
8.1.4 Sensor Fusion Aspects......Page 344
8.2.1 Basic Notions......Page 345
8.3.1 Object Dynamics......Page 346
8.3.1.1 Example: A Simplified Model......Page 347
8.3.2.1 Example: Swerling-I Targets......Page 348
8.3.4 Resolution......Page 349
8.3.5 Data Association......Page 350
8.3.5.2 Example: Small Object Clusters......Page 351
8.4.1 Finite Mixture Densities......Page 353
8.4.2.2 Example: Innovation Statistics......Page 355
8.4.4 Retrodiction......Page 356
8.4.4.1 Example: Rauch-Tung-Striebel Smoothing......Page 357
8.5.1 Moment Matching......Page 358
8.5.2 IMM-Type Prediction......Page 359
8.5.3 PDA-Type Filtering......Page 360
8.5.3.2 Example: JPDA Filtering for Small Clusters......Page 361
8.5.4.1 Individual Gating......Page 363
8.5.4.3 Local Combining......Page 364
8.5.5.1 Example: Standard IMM Retrodiction......Page 365
8.6.1 JPDA Formation Tracking......Page 366
8.6.2 MHT and Retrodiction......Page 367
References......Page 369
Abbreviations and Symbols......Page 372
9.1 Introduction......Page 374
9.2.1 Various Types of Measurements......Page 375
9.2.2 Observability......Page 377
9.2.2.1 Fundamental Ambiguities......Page 378
9.2.2.2 Nth-Order Dynamics Target......Page 379
9.3.1 Bearings-Only Tracking--Typical TMA Problem......Page 380
9.3.2.1 General Case......Page 382
9.3.2.2 Bearings-Only Tracking......Page 384
9.3.3 Step 2--Estimation Algorithm......Page 385
9.3.3.1 The Modified Polar Extended Kalman Filter......Page 386
9.3.3.2 The Maximum Likelihood Estimator......Page 388
9.3.4 Step 3--Optimal Observer Motion......Page 389
9.4 Conclusion......Page 390
References......Page 391
Defining Terms......Page 393
10.1.2 Why Exploit Sound for Underwater Applications?......Page 394
10.1.4 Sonar......Page 395
10.2.2 Sound Velocity Profiles......Page 396
10.2.3 Three Propagation Modes......Page 397
10.2.4 Multipaths......Page 398
10.2.5 Sonar System Performance......Page 399
10.3 Underwater Sound Systems: Components and Processes......Page 400
10.3.1 Signal Waveforms......Page 401
10.3.2 Sonar Transducers......Page 403
10.3.4 Sonar Projectors (Transmitters)......Page 404
10.3.6 Receiving Arrays......Page 405
10.3.8 Dynamic Range Control......Page 406
10.3.10 Displays......Page 407
10.4.1 Detection......Page 409
10.4.3 Classification......Page 411
10.5.1 Adaptive Beamforming......Page 412
10.5.3 Acoustic Data Fusion......Page 413
Acknowledgment......Page 414
Further Information......Page 415
Ch11 Theory & Implementation of Advanced Signal Processing for Active & Passive Sonar Systems......Page 416
11.1.2.1 The Passive Sonar Problem......Page 417
11.1.2.2 The Active Sonar Problem......Page 419
11.2 Theoretical Remarks......Page 420
11.2.1 Definition of Basic Parameters......Page 424
11.2.2 System Implementation Aspects......Page 427
11.2.3.1.1 Signal Ambiguity Function and Pulse Selection......Page 430
11.2.3.1.2 Effects of Medium......Page 431
11.2.3.2 Effects of Bandwidth in Active Sonar Operations......Page 432
11.2.3.3.2 Display Format for FM Type of Signals......Page 436
11.2.4 Comments on Computing Architecture Requirements......Page 439
11.3.1.1 Narrowband Acoustic Signals......Page 442
11.3.1.2 Broadband Acoustic Signals......Page 451
11.3.2 Active Towed Array Sonar Applications......Page 453
11.4 Conclusion......Page 456
References......Page 458
12.1 Introduction......Page 464
12.2 Fundamental Theory of Phased Arrays......Page 465
12.2.1.1.1 The Case of "True Time Delay"......Page 467
12.2.2 Linear Arrays......Page 468
12.2.2.1 Grating Lobes......Page 469
12.2.2.2 Side Lobe Level......Page 470
12.2.3 Two- and Three-Dimensional Arrays......Page 471
12.3.1 Statement of the Boundary Value Problem......Page 472
12.3.2 Solution of the N x N System of Equations......Page 474
12.4 Array Architectures......Page 475
References......Page 476
Abbreviations......Page 478
13.1 Introduction......Page 479
13.2.1 Resolution......Page 481
13.2.2 Scanning and Transducers......Page 482
13.3.3 Structure......Page 484
13.4.1 Single Channel......Page 485
13.4.2 Multi-Channel Systems, Arrays......Page 486
13.4.3 Doppler and Advanced Systems......Page 490
13.5 Conclusion......Page 492
References......Page 493
14.1 Introduction......Page 495
14.2 Limitations of Ultrasonography Addressed by 3-D Imaging......Page 496
14.3.1 Introduction......Page 497
14.3.2 Mechanical 3-D Scanning Devices......Page 498
14.3.2.2 Mechanical 3-D Scanning: Tilting......Page 500
14.3.2.3 Mechanical 3-D Scanning: Rotational......Page 503
14.3.3 Sensed Free-Hand 3-D Scanning......Page 504
14.3.3.3 Sensed Free-Hand 3-D Scanning: Magnetic Field Sensors......Page 505
14.3.4 Free-Hand Scanning without Position Sensing......Page 507
14.3.5 Dynamic 3-D Ultrasonography Using 2-D Arrays......Page 508
14.4.1 Feature-Based 3-D Reconstruction......Page 509
14.4.2 Voxel-Based 3-D Ultrasound Reconstruction......Page 510
14.5.1 Mechanical 3-D Scanning: Linear......Page 511
14.5.2 Mechanical 3-D Scanning: Tilting......Page 512
14.6 Viewing of 3-D Ultrasound Images......Page 513
14.6.3 Volume-Rendering (VR)......Page 514
14.7.2 Distance Measurement......Page 517
14.7.4 Volume Measurements: Theoretical Derivation of Variability......Page 518
14.7.5 Volume Measurements: Experimental Measurements with Balloons......Page 519
14.7.8 Intra- and Inter-Observer Variability in Measuring Prostate Volume......Page 520
14.8.1 Identification of Seeds......Page 521
14.9.3 Speed of Operation......Page 522
References......Page 523
15.1 Introduction......Page 529
15.2.1 Electromagnetic Radiation Interactions with Matter......Page 535
15.2.2.1 Transmission CT 3D Imaging......Page 540
15.2.3 Image Reconstruction Algorithms......Page 544
15.2.3.1 Transmission CT Algorithms......Page 545
15.2.3.2 Single Photon Emission CT (SPECT) Algorithms......Page 546
15.2.4 Fundamentals of the CT Measurement Equipment......Page 547
15.3.1.2 Improved Prosthetic Implant Design......Page 550
15.3.2.1 3D CT Analysis of Porosity in Ball Grid Arrays......Page 557
15.3.2.2 3D CT Analysis of Metal Powder Filling Methods......Page 558
15.3.3.1 Material Analysis of a DC Motor......Page 564
15.3.3.2 Material Analysis of High Explosives......Page 565
15.3.3.3 gamma-Ray Nondestructive Radioassay for Waste Management......Page 569
15.5 Future Work......Page 571
References......Page 572
16.1 Introduction......Page 577
16.1.1 CT Systems......Page 578
16.1.2 The Sinogram......Page 579
16.1.3 Image Reconstruction......Page 580
16.3 Reducing Motion Artifacts......Page 582
16.3.1 Established Methods......Page 583
16.3.4 ECG Gating......Page 584
16.3.5 Single-Breath-Hold ECG Gating......Page 585
16.4.1 Spatial Overlap Correlator to Identify Motion Effects......Page 587
16.4.1.2 Hardware Implementation......Page 590
16.4.1.3 Software Implementation......Page 591
16.4.2 Adaptive Processing to Remove Motion Artifacts......Page 592
16.4.2.1 Adaptive Interference Cancellation......Page 595
16.4.3.1 Phase Selection by Correlation......Page 598
16.4.3.2 Assembling the Coherent Sinogram......Page 599
16.4.5 Phantom Experiment......Page 600
16.4.6 Human Patient Results......Page 604
16.5 Conclusions......Page 607
References......Page 608
17.1 Introduction......Page 612
17.2 Basic NMR Phenomena......Page 613
17.4 NMR Signal......Page 615
17.5 Signal-to-Noise Ratio......Page 618
17.6 Image Generation & Reconstruction......Page 619
17.7 Selective Excitation......Page 624
17.8 Pulse Sequences......Page 626
17.9 Influence of Motion......Page 631
17.10 Correction of Motion during Image Series......Page 634
17.11 Imaging of Flow......Page 635
17.12 MR Spectroscopy......Page 637
17.13 System Design Considerations & Conclusions......Page 638
References......Page 639
18.1.1 Rationale......Page 641
18.2 Contrast Agent Kinetic Modeling......Page 642
18.3.2 Determinants of R1 contrast(t)......Page 643
18.3.2.1 Signal Equation......Page 644
18.3.2.2.1 Inversion Recovery......Page 645
18.3.2.2.2 Look-Locker......Page 647
18.3.2.3.1 T1 FARM......Page 648
18.4.1 Dynamic Range of T1 FARM......Page 651
18.4.2 Cardiac T1 FARM Concentration-Time Curves......Page 653
18.4.4 Future Enhancements and Modifications of T1 FARM......Page 654
References......Page 655
19.1 Introduction......Page 658
19.2.1 Literature Review......Page 659
19.2.2 Generic Medical Image Registration Scheme......Page 660
19.2.2.1 Transformation Models......Page 661
19.2.2.2 Matching Features — Measure of Match......Page 662
19.2.2.3 Determination of the Transformation Parameters Using Global Optimization Techniques......Page 663
19.2.3 Medical Image Registration Refinement Using Elastic Deformation......Page 665
19.2.3.2 Surface Matching Based on the Kohonen Model......Page 666
19.2.4.1 2-D Case: Automatic Retinal Image Registration......Page 671
19.2.4.2 3-D Case: Automatic CT-MRI Registration......Page 672
19.3.1.1 Fusion Using Logical Operators......Page 675
19.3.1.2 Fusion Using a Pseudocolor Map......Page 676
19.3.1.3 Clustering Algorithms for Unsupervised Fusion of Registered Images......Page 677
19.3.1.4 Fusion to Create Parametric Images......Page 680
19.4 Conclusions......Page 681
References......Page 683
20.1 Introduction......Page 688
20.2 Role of Imaging in External Beam Treatment Planning......Page 689
20.2.1.1.1 Interaction of X-Ray Irradiation with Matter......Page 690
20.2.1.1.2 Experimental Estimation of the HU--Relative Electron Density Relationship......Page 691
20.2.1.3 Clinical Examples of DRRs Application......Page 695
20.2.3 CT-Based Simulation......Page 698
20.3.1 General Remarks......Page 700
20.3.2 CT-Based Catheter Autoreconstruction......Page 704
20.3.4 CT-MR Image Registration......Page 707
20.4 Conclusion......Page 709
References......Page 719