كتاب Introduction to Radar Using Python and MATLAB
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 كتاب Introduction to Radar Using Python and MATLAB

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مُساهمةموضوع: كتاب Introduction to Radar Using Python and MATLAB    كتاب Introduction to Radar Using Python and MATLAB  Emptyالإثنين 20 مارس 2023, 6:13 am

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Introduction to Radar Using Python and MATLAB
Andy Harrison

كتاب Introduction to Radar Using Python and MATLAB  M_i_t_15
و المحتوى كما يلي :


Contents
Preface xiii
1 Introduction 1
1.1 History of Radar . 1
1.2 Radar Classification . 2
1.2.1 Frequency Band 2
1.2.2 Waveform . 3
1.2.3 Application . 3
1.2.4 Configuration . 4
1.3 Accompanying Software 6
1.3.1 Python 7
1.3.2 MATLAB . 9
Problems . 9
References . 12
2 Electromagnetic Fields and Waves 15
2.1 Maxwell’s Equations 15
2.2 Time Harmonic Electromagnetics 17
2.3 Electromagnetic Boundary Conditions . 18
2.3.1 General Material Interface . 18
2.3.2 Dielectric Interface . 19
2.3.3 Perfect Electric Conductor Interface 20
2.3.4 Perfect Magnetic Conductor Interface 20
2.3.5 Radiation Condition 20
2.4 Wave Equations and Solutions . 21
2.4.1 Scalar and Vector Potentials . 21
2.4.2 Fields Due to Sources 23
2.4.3 Source Free Fields 24
2.5 Plane Waves . 24
vvi Introduction to Radar Using Python and MATLAB
2.5.1 Plane Waves in Lossless Media 25
2.5.2 Plane Waves in Lossy Media 27
2.5.3 Plane Waves in Low-Loss Dielectrics . 29
2.5.4 Plane Waves in Good Conductors . 30
2.6 Plane Wave Reflection and Transmission 31
2.6.1 Perpendicular Polarization . 32
2.6.2 Parallel Polarization 36
2.6.3 Brewster Angle . 38
2.6.4 Critical Angle . 38
2.7 Tropospheric Refraction 39
2.7.1 Apparent Elevation . 41
2.7.2 Apparent Range 42
2.7.3 Beam Spreading 43
2.7.4 Ducting . 43
2.8 Earth Diffraction 44
2.8.1 Case 1: d ≥ dlos 45
2.8.2 Case 2: d < dlos 47
2.9 Plane Wave Attenuation 48
2.9.1 Atmospheric Attenuation 48
2.9.2 Attenuation in Vegetation 49
2.9.3 Rain Attenuation . 51
2.9.4 Cloud and Fog Attenuation 52
2.10 Examples 54
2.10.1 Plane Wave Propagation . 54
2.10.2 Reflection and Transmission . 55
2.10.3 Tropospheric Refraction . 56
2.10.4 Earth Diffraction . 58
2.10.5 Attenuation . 60
Problems . 64
References . 65
3 Antenna Systems 67
3.1 Antenna Parameters . 67
3.1.1 Radiation Pattern . 67
3.1.2 Beamwidth 70
3.1.3 Power Density 71
3.1.4 Radiation Intensity . 72
3.1.5 Directivity 73
3.1.6 Gain . 75
3.1.7 Bandwidth 76
3.1.8 Polarization . 76
3.2 Antenna Types . 79Contents vii
3.2.1 Linear Wire Antennas 79
3.2.2 Loop Antennas . 82
3.2.3 Aperture Antennas . 86
3.2.4 Horn Antennas 94
3.2.5 Antenna Arrays . 100
3.3 Examples 111
3.3.1 Finite Length Dipole . 111
3.3.2 Circular Loop . 112
3.3.3 Rectangular Aperture 113
3.3.4 Circular Aperture . 115
3.3.5 Pyramidal Horn . 116
3.3.6 Tschebyscheff Linear Array . 116
3.3.7 Planar Array 118
3.3.8 Circular Array 119
Problems . 120
References . 122
4 The Radar Range Equation 123
4.1 Hertzian Dipole . 123
4.1.1 Radiated Power . 125
4.1.2 Radiation Intensity . 126
4.1.3 Directivity and Gain 126
4.2 Basic Radar Range Equation . 127
4.2.1 Maximum Detection Range 130
4.2.2 Noise 130
4.2.3 Losses . 131
4.2.4 Radar Reference Range and Loop Gain . 131
4.3 Search Radar Range Equation 132
4.4 Bistatic Radar Range Equation . 135
4.4.1 Maximum Detection Range 137
4.5 Examples 139
4.5.1 Hertzian Dipole . 139
4.5.2 Basic Radar Range Equation 139
4.5.3 Search Radar Range Equation . 144
4.5.4 Bistatic Radar Range Equation 146
Problems . 150
References . 151
5 Radar Receivers 153
5.1 Configurations . 153
5.2 Noise . 155
5.3 Dynamic Range . 157viii Introduction to Radar Using Python and MATLAB
5.4 Bandwidth . 159
5.5 Gain Control . 160
5.6 Filtering 162
5.7 Demodulation . 165
5.7.1 Noncoherent Detection . 166
5.7.2 Coherent Detection . 167
5.8 Analog-to-Digital Conversion 169
5.8.1 Sampling 169
5.8.2 Quantization 170
5.9 Digital Receivers 172
5.9.1 Direct Digital Downconversion 173
5.9.2 Hilbert Transform 174
5.10 Examples 176
5.10.1 Sensitivity Time Control . 176
5.10.2 Noise Figure 177
5.10.3 Receiver Filtering 177
5.10.4 Noncoherent Detection . 178
5.10.5 Coherent Detection . 179
5.10.6 Analog-to-Digital Conversion . 179
5.10.7 Analog-to-Digital Resolution 180
Problems . 182
References . 183
6 Target Detection 185
6.1 Optimal Detection . 185
6.1.1 Neyman-Pearson Lemma 187
6.1.2 Noncoherent Detection . 188
6.1.3 Coherent Detection . 190
6.2 Pulse Integration 193
6.2.1 Coherent Integration . 194
6.2.2 Noncoherent Integration . 194
6.2.3 Binary Integration 197
6.2.4 Cumulative Integration . 198
6.3 Fluctuating Target Detection . 198
6.3.1 Swerling 0 202
6.3.2 Swerling I . 204
6.3.3 Swerling II 205
6.3.4 Swerling III . 205
6.3.5 Swerling IV . 207
6.3.6 Shnidman’s Equation . 209
6.4 Constant False Alarm Rate . 212
6.4.1 Cell Averaging CFAR 213Contents ix
6.4.2 Cell Averaging Greatest of CFAR . 214
6.4.3 Censored Greatest of CFAR . 216
6.4.4 Cell Averaging Smallest of CFAR . 218
6.4.5 Ordered Statistic CFAR 218
6.4.6 Cell Averaging Statistic Hofele CFAR 219
6.5 Examples 221
6.5.1 Probability Distributions . 221
6.5.2 Detection Probability with Gaussian Noise . 221
6.5.3 Detection Probability with Rayleigh Noise . 222
6.5.4 Single Pulse signal-to-noise . 224
6.5.5 Binary Integration 224
6.5.6 Optimum Binary Integration . 225
6.5.7 Coherent Pulse Integration . 226
6.5.8 Noncoherent Pulse Integration . 227
6.5.9 Shnidman’s Approximation 228
6.5.10 Constant False Alarm Rate 229
Problems . 232
References . 233
7 Radar Cross Section 235
7.1 Definition 235
7.1.1 Angle Variation . 236
7.1.2 Frequency Variation 236
7.1.3 Polarization Variation 238
7.2 Scattering Matrix 239
7.3 Scattering Mechanisms . 242
7.4 Prediction Methods . 243
7.4.1 Analytical Techniques 243
7.4.2 Numerical Techniques . 259
7.4.3 Measurement Techniques 280
7.5 Radar Cross-Section Reduction 286
7.5.1 Shaping . 287
7.5.2 Radar Absorbing Material . 287
7.5.3 Passive Cancellation . 287
7.5.4 Active Cancellation 288
7.5.5 Electronic Countermeasures . 288
7.6 Examples 288
7.6.1 Two-Dimensional Strip 288
7.6.2 Two-Dimensional Cylinder 289
7.6.3 Two-Dimensional Cylinder Oblique Incidence . 290
7.6.4 Rectangular Plate . 290
7.6.5 Stratified Sphere 291x Introduction to Radar Using Python and MATLAB
7.6.6 Circular Cone . 292
7.6.7 Rounded Nose Cone . 294
7.6.8 Frustum . 294
7.6.9 Physical Optics . 295
7.6.10 Finite Difference Time Domain Method 298
Problems . 302
References . 303
8 Pulse Compression 309
8.1 Range Resolution . 309
8.2 Stepped Frequency Waveforms . 311
8.3 Matched Filter . 315
8.4 Stretch Processing . 320
8.5 Windowing 326
8.6 Ambiguity Function . 327
8.6.1 Single Unmodulated Pulse . 329
8.6.2 Single LFM Pulse 331
8.6.3 Generic Waveform Procedure . 333
8.7 Phase-Coded Waveforms . 335
8.7.1 Barker Codes . 336
8.7.2 Frank Codes 338
8.7.3 Pseudorandom Number Codes . 338
8.8 Examples 341
8.8.1 Stepped Frequency Waveform . 341
8.8.2 Matched Filter 342
8.8.3 Stretch Processor . 343
8.8.4 Unmodulated Pulse Ambiguity 344
8.8.5 LFM Pulse Ambiguity . 344
8.8.6 Coherent Pulse Train Ambiguity 346
8.8.7 LFM Pulse Train Ambiguity . 348
8.8.8 Barker Code Ambiguity 350
8.8.9 PRN Code Ambiguity 354
8.8.10 Frank Code Ambiguity . 356
Problems . 358
References . 359
9 Target Tracking 361
9.1 Tracking Filters 361
9.1.1 Alpha-Beta Filter . 362
9.1.2 Alpha-Beta-Gamma Filter . 366
9.1.3 Kalman Filter . 371
9.2 Multitarget Tracking 381Contents xi
9.2.1 Global Nearest Neighbor . 383
9.2.2 Joint Probabilistic Data Association . 385
9.2.3 Multiple Hypothesis Tracker 389
9.2.4 Random Finite Set 393
9.3 Measurement Model 394
9.4 Examples 396
9.4.1 Alpha-Beta Filter . 396
9.4.2 Alpha-Beta-Gamma Filter . 397
9.4.3 Kalman Filter: Constant Velocity 399
9.4.4 Kalman Filter: Constant Acceleration . 401
9.4.5 Adaptive Kalman Filter: Epsilon Method 403
9.4.6 Adaptive Kalman Filter: Sigma Method 408
Problems . 410
References . 411
10 Tomographic Synthetic Aperture Radar 413
10.1 Tomography . 413
10.1.1 History 413
10.1.2 Line Integrals and Projections . 416
10.1.3 SAR Imaging . 422
10.1.4 Three-Dimensional Tomography 424
10.2 Examples 431
10.2.1 Two-Dimensional 432
10.2.2 Three-Dimensional . 436
Problems . 440
References . 441
11 Countermeasures 443
11.1 Passive Jamming 443
11.1.1 Chaff 443
11.1.2 Passive Deception 446
11.2 Active Jamming . 447
11.2.1 Continuous Noise 447
11.2.2 Active Deception . 453
11.3 Digital Radio Frequency Memory 456
11.4 Examples 457
11.4.1 Jammer to Signal: Self-Screening . 457
11.4.2 Jammer to Signal: Escort 458
11.4.3 Crossover Range: Self-Screening . 459
11.4.4 Crossover Range: Escort 460
11.4.5 Burn-Through Range: Self-Screening 462
11.4.6 Burn-Through Range: Escort . 462xii Introduction to Radar Using Python and MATLAB
11.4.7 Moving Target Indication . 463
Problems . 464
References . 465
About the Author 46
Index
Index
Allan Cormack, 414
Ambiguity function, 327
Barker codes, 336
Frank codes, 338
generic waveform, 333
LFM pulse, 331
PRN codes, 338
balance property, 340
correlation property, 341
run property, 341
unmodulated pulse, 329
Analog-to-digital conversion, 169
effective number of bits, 172
quantization, 170
sampling, 169
Antenna
bandwidth, 76
beamwidth, 70
directivity, 73
effective aperture, 129
gain, 75
lobes, 68
pattern, 67
pattern cuts, 68
pattern multiplication, 102
polarization, 76
polarization loss factor, 77
polarization mismatch, 77
radiation intensity, 72
radiation zones, 69
sidelobe level, 68
Antenna types
aperture, 86
array, 100
Hertzian dipole, 123
horn, 94
linear wire, 79
loop, 82
Automatic gain control, 155
Brewster angle, 38
Cassini ovals, 137
Cauchy-Schwarz, 317
Christian Hulsmeyer, 1 ¨
Constant false alarm rate, 212
cell averaging, 213
cell averaging greatest of, 214
cell averaging smallest of, 218
censored greatest of, 216
ordered statistic, 218
statistic Hofele, 219
Countermeasures, 443
active jamming, 447
active deception, 453
471472 INDEX
burn-through range, 451
continuous noise, 447
cross-eye, 455
crossover range, 451
ERP, 450
escort, 450
inverse gain, 455
jammer-to-signal, 450
RGPO, 453
self-screening, 450
VGPO, 454
DRFM, 456
MTI, 445
blind speed, 446
passive jamming, 443
chaff, 443
passive deception, 446
STAP, 452
Critical angle, 38
Detection, 185
coherent, 190
error function, 189
false alarm rate, 186
Neyman-Pearson, 186, 187
noncoherent, 188
Shnidman’s approximation, 209
Swerling models, 199
Diffraction, 44
Dynamic range, 157
1-dB compression point, 157
intermodulation distortion, 158
spurious free, 157
EMI scanner, 414
Equivalence principle, 86
GitHub, 6
Heinrich Hertz, 1
Image frequency, 162
Intermediate frequency, 154
James Clerk Maxwell, 1, 15
Johann Radon, 413
Low-noise amplifier, 154
Marcum’s Q function, 192
Matched filter, 315, 318
North filter, 315
signal-to-noise, 318
time-bandwidth product, 319
MATLAB®, 6, 9
Maxwell’s equations, 15
Ampere’s law, 16
boundary conditions, 18
general interface, 18
PEC, 20
PMC, 20
radiation condition, 20
continuity equation, 16
Faraday’s law, 16
gauge
axial, 23
Coulomb, 23
Dirac, 23
Fock-Schwinger, 23
Hamiltonian, 23
Lorenz, 23
Maximal Abelian, 23
Poincare, 23
radiation, 23
transverse, 23
Weyl, 23
Gauss’s law, 16
Lorenz condition, 22
potential
scalar, 21
vector, 21
wave equation, 21
NEXRAD, 2
WSR-88D, 2, 3
Noise power, 130, 155
noise factor, 130INDEX 473
noise figure, 130
cascaded network, 155
power spectral density, 130
Ohm’s law, 27
Penrose transform, 414
Permeability, 18
Permittivity, 17
Phase-coded waveforms, 335
Plane waves, 24
atmospheric attenuation, 48
attenuation constant, 28
cloud and fog attenuation, 52
phase constant, 28
phase matching, 35
rain attenuation, 51
vegetation attenuation, 49
Poynting vector, 71
Pulse compression, 309
range resolution, 309
windowing, 326
Pulse integration, 193
binary integration, 197
coherent, 194
cumulative, 198
noncoherent, 194
Pulse repetition interval, 134
Python®, 6, 7
IDE, 8
PyCharm, 8
PyDev, 8
Spyder, 8
installation, 7
Matplotlib, 7
NumPy, 7
SciPy, 7
Qt, 6, 7
Radar
applications, 3
classification, 2
configurations, 4
definition, 1
frequency bands, 2
history, 1
IEEE designation, 3
waveforms, 3
Radar absorbing material, 287
Radar cross section, 127
angle variation, 236
definition, 235
frequency variation, 236
frustum, 258
polarization variation, 238
prediction
analytical, 243
approximate methods, 271
measurement methods, 280
numerical methods, 259
rectangular plate, 251
reduction, 286
right circular cone, 255
rounded-nose cone, 257
scattering width, 244
stratified sphere, 253
two-dimensional cylinder, 247
two-dimensional cylinder oblique,
249
two-dimensional strip, 244
Radar range equation, 127
bistatic, 135
loop gain, 131
losses, 131
maximum detection range, 130, 137
power aperture product, 132
reference range, 131
Radar receivers, 153
bandwidth, 159
coherent detection, 167
configurations, 153
demodulation, 165
digital receivers, 172
direct digital downconversion, 173474 INDEX
filtering, 162
Bessel, 163
Butterworth, 163
Chebyshev, 163
elliptic, 163
finite impulse response, 173
gain control, 160
gain normalization, 162
noncoherent detection, 166
superheterodyne, 153
Radon transform, 413
Range profile, 312
Refraction, 40
apparent elevation, 41
apparent range, 42
beam spreading, 43
ducting, 43
SAR imaging, 422
Scattering matrix, 239
back scattering alignment, 242
coordinate systems, 241
forward scattering alignment, 242
Scattering mechanisms
cavaties, 243
creeping waves, 243
diffraction, 242
multibounce, 243
specular reflection, 242
surface waves, 243
Sensitivity time control, 154
Shadow region, 44
Sir Godfrey Hounsfield, 414
Skin depth, 30
Snell’s law, 35
Sommerfeld, 21
Stepped frequency, 311
dispersion, 313
effective bandwidth, 311
range resolution, 312
Stretch processing, 320
instantaneous frequency, 323
range resolution, 326
reference signal, 321
sampling, 323
Target tracking, 361
Mahalanobis distance, 383
measurement model, 394
multitarget tracking, 381
GNN, 382, 383
JPDA, 382, 385
MHT, 382, 389
RFS, 382, 393
tracking filters, 361
adaptive, 379
alpha-beta, 362
alpha-beta-gamma, 366
innovation, 363
Kalman, 371
Kalman gain, 372
measurement noise, 362
process noise, 362
residual, 363
state space model, 362
system state, 362
Telemobilosocpe, 1
Tomography, 413
ART, 419
CT, 414
filtered backprojection, 420
Fourier slice theorem, 417
MART, 420
polar reformatting, 419
SART, 420
SIRT, 419
three-dimensional, 424
linear trace, 424
planar slice, 424
Wavelength, 26
Wavenumber, 22
Windowing
Blackman-Harris, 106
Hamming, 106
Hanning, 106
Kaiser, 106

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