حس‌گری حرکت و ژست با رادار

This book provides a complete overview of radar system theory and design for consumer applications, from basic short range radar theory to the integration into the real-world products, focusing particularly on gesture sensing in consumer products. It brings you step-by-step through the theoretical understandings, design procedures, analysis tools, and design examples of radar systems. Packed with practical guidance learned from real consumer product development, the book explains how radar works in plain language; provides design principles applied in consumer products; demonstrates algorithms with real world measurement data; describes system trade-offs and cross-functional solutions for solving integration challenges; equips you to design your own radars in consumer electronics for motion sensing and gesture controls. The book focuses on consumer-oriented radar systems with its theory, specifications, application, challenges in integration and co-existence with other radio components. It is self-contained to cover radar hardware, waveforms/modulations, signal processing, detection and classification, machine learning and UX design. With its unique coverage of consumer-oriented radar systems, coupled with the authors' practical experience in designing radars for today's consumer products, this is a must-have book for engineers and researchers working with radar systems in consumer electronics and mobile devices such as cell phone, wearables, and in the automotive industry. Downloadable MATLAB(R) scripts and Simulink models are included. Artech House Radar Library Motion and Gesture Sensing with Radar 1 Contents 8 Preface 14 1 Introduction 16 1.1 Radar Basics and Types 17 1.2 Frequency Bands and Civil Applicatio 20 1.3 Radar Standardization 23 1.4 Book Outline 23 References 24 2 Radar System Architecture and Range Equation 26 2.1 Basic Hardware Components of Radar 26 2.1.1 Transmitter/Receiver (Transceiver) 27 2.1.2 Waveform Generator 30 2.1.3 Antennas 31 2.2 LFM Radar Architecture 34 2.3 Receiver Noise 34 2.4 Dynamic Range 36 2.5 Radar Range Equation 37 2.6 Radar System Integration 42 References 43 3 Radar Signal Model and Demodulation 46 3.1 Signal Modeling 46 3.1.1 Point Target 49 3.1.2 Distributed Target 50 3.2 Radar Waveforms and Demodulation 51 3.2.1 Matched Filter 53 3.2.2 Ambiguity Function 58 3.3 Frequency Modulated Waveforms 68 3.3.1 Conventional FMCW Waveforms 71 3.3.2 LFM Chirp Train (Fast Chirp) 77 3.3.3 Stretch Processing 78 3.4 Phase Coded Waveforms 81 3.4.1 Golay Codes 84 3.5 Summary 86 References 87 4 Radar Signal Processing 90 4.1 Range Processing (Fast Time Processi 92 4.1.1 Minimum Range and Maximum Unambigu 93 4.1.2 Pulse Compression 93 4.1.3 Range Resolution 94 4.1.4 Range Accuracy 98 4.1.5 Time Sidelobes Control 100 4.2 Doppler Processing (Slow Time Proces 103 4.2.1 Sampling Frequency in Slow Time Do 107 4.2.2 CIT Window Size 111 4.2.3 MTI and Clutter Cancellation 112 4.2.4 Moving Target Detector (Filter Ban 116 4.2.5 Doppler (Radial Velocity) Resoluti 117 4.2.6 Doppler (Radial Velocity) Accuracy 118 4.2.7 Doppler Sidelobes Control 119 4.3 Summary 120 References 120 5 Array Signal Processing 124 5.1 Array Manifold and Model 125 5.2 Conventional Beamforming 131 5.2.1 Uniform Array and FFT Based Beamfoming 133 5.2.2 Array Resolution, Accuracy, and Sidelobes Control 135 5.2.3 Digital Beamforming Versus Analog Beamforming 137 5.3 High-Resolution Methods 137 5.4 MIMO 141 5.4.1 Virtual Array 141 5.4.2 Basic MIMO Waveforms 144 5.4.3 Summary 147 References 148 6 Motion and Presence Detection 150 6.1 Introduction 150 6.2 Detection Theory 151 6.2.1 Hypothesis Testing and Decision Rules 151 6.2.2 Neyman-Pearson Criterion and Likelihood Ratio Test 154 6.3 Signal and Noise Models 155 6.3.1 Target RCS Fluctuations 155 6.3.2 Noise 158 6.4 Threshold Detection 159 6.4.1 Optimal Detection of Nonfluctuating Target 159 6.4.2 Detection Performance 161 6.4.3 Impact of Target Fluctuation 163 6.5 Constant False Alarm Rate Detection 164 6.5.1 Cell-Averaging CFAR 166 6.5.2 Greatest-of and Least-of CFAR 167 6.5.3 Ordered Statistics CFAR 168 6.6 Clutter Rejection 168 6.6.1 Regions of Interest 169 6.6.2 Doppler Filtering 169 6.6.3 Spatial Filtering 171 6.6.4 Adaptive and Machine Learned Clutter Filters 172 6.7 Interference 172 6.8 Detection Pipeline Design 173 References 173 7 Radar Machine Learning 176 7.1 Machine Learning Fundamentals 176 7.1.1 Supervised Learning 177 7.1.2 Linear Regression 179 7.1.3 Logistic Regression 185 7.1.4 Beyond Linear Models 188 7.1.5 Neural Networks 189 7.2 Radar Machine Learning 197 7.2.1 Machine Learning Considerations for Radar 197 7.2.2 Gesture Classification 200 7.3 Training, Development, and Testing Datasets 212 7.4 Evaluation Methodology 212 7.4.1 Machine Learning Classification Metrics 214 7.4.2 Classification Metrics for Time Series Data 217 7.5 The Future of Radar Machine Learning 219 7.5.1 What’s Next? 220 7.5.2 Self Supervised Learning 220 7.5.3 Meta Learning 220 7.5.4 Sensor Fusion 221 7.5.5 Radar Standards, Libraries, and Datasets 222 7.6 Conclusion 222 References 222 8 UX Design and Applications 226 8.1 Overview 226 8.2 Understanding Radar for Human-Computer Interaction 227 8.3 A New Interaction Language for Radar Technology 232 8.3.1 Explicit Interactions: Gestures 232 8.3.2 Implicit Interactions: Anticipating Users' Behaviors 234 8.3.3 Movement Primitives 236 8.4 Use Cases 238 References 244 9 Research and Applications 246 9.1 Technological Trends 246 9.2 Radar Standardization 248 9.3 Emerging Applications 248 References 249 About the Authors 252 Index 254 Radar:,Signal,processing;,Motion,sensor;,Gesture,sensing;,Artech,House;,978-1-63081-823-4 Radar: Signal processing,Motion sensor,Gesture sensing,Artech House,978-1-63081-823-4