Signal Processing for Intelligent Sensor Systems with MATLAB 9

Transcription

1 Signal Processing for Intelligent Sensor Systems with MATLAB 9 Second Edition David С CRC Press Taylor & Francis Gro jroup Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Group, an informa business

2 Preface Acknowledgments Author xiii xv xvii Part I Fundamentals of Digital Signal Processing Chapter 1 Sampled Data Systems A/D Conversion Sampling Theory Complex Bandpass Sampling Delta-Sigma Analog Conversion MATLAB Examples Summary, Problems, and References 15 Problems 16 References 17 Chapter 2 z-transform Comparison of Laplace and z-transforms System Theory Mapping of s-plane Systems to the Digital Domain MATLAB Examples Summary 40 Problems 41 References 41 Chapter 3 Digital Filtering FIR Digital Filter Design HR Filter Design and Stability Whitening Filters, Invertibility, and Minimum Phase Filter Basis Polynomials Butterworth Filters Chebyshev Type I Filters Chebyshev Type II Filters Elliptical Filters Bessel Filters High-Pass, Band-Pass, and Band-Stop Filter Transformations MA Digital Integration Filter MATLAB Examples Summary 62 Problems 63 References 63

3 viii Chapter 4 Digital Audio Processing Basic Room Acoustics Artificial Reverberation and Echo Generators Flanging and Chorus Effects Bass, Treble, and Parametric Filters Amplifier and Compression/Expansion Processors Digital-to-Analog Reconstruction Filters Audio File Compression Techniques MATLAB Examples Summary 91 Problems 92 References 92 Chapter 5 Linear Filter Applications State Variable Theory Continuous State Variable Formulation Discrete State Variable Formulation Fixed-Gain Tracking Filters D FIR Filters Image Upsampling Reconstruction Filters MATLAB Examples Summary 119 Problems 120 References 121 Part II Frequency Domain Processing Chapter 6 Fourier Transform Mathematical Basis for the Fourier Transform Spectral Resolution Fast Fourier Transform Data Windowing Circular Convolution Issues Uneven-Sampled Fourier Transforms Wavelet and Chirplet Transforms MATLAB Examples Summary 165 Problems 167 References 168 Chapter 7 Spectral Density Spectral Density Derivation Statistical Metrics of Spectral Bins Probability Distributions and PDFs Statistics of the NPSD Bin SNR Enhancement and the Zoom FFT 176

4 ix Conversion of Random Variables Confidence Intervals for Averaged NPSD Bins Synchronous Time Averaging Higher-Order Moments Characteristic Function Cumulants and Polyspectra Transfer Functions and Spectral Coherence Intensity Field Theory Point Sources and Plane Waves Acoustic Field Theory Acoustic Intensity Structural Intensity Electromagnetic Intensity Intensity Display and Measurement Techniques Graphical Display of the Acoustic Dipole Calculation of Acoustic Intensity from Normalized Spectral Density Calculation of Structural Intensity for Compressional and Bending Waves Calculation of the Poynting Vector MATLAB Examples Summary 219 Problems 220 References 221 Chapter 8 Wavenumber Transforms Spatial Transforms Spatial Filtering and Beamforming Image Enhancement Techniques JPEG and MPEG Compression Techniques Computer-Aided Tomography Magnetic Resonance Imaging MATLAB Examples Summary 258 Problems 261 References 261 Part III Adaptive System Identification and Filtering Chapter 9 Linear Least-Squared Error Modeling Block Least Squares Projection-Based Least Squares General Basis System Identification Mechanics of the Human Ear Least-Squares Curve Fitting Pole-Zero Filter Models MATLAB Examples Summary 280

5 x Problems 280 References 281 Chapter 10 Recursive Least-Squares Techniques RLS Algorithm and Matrix Inversion Lemma Matrix Inversion Lemma Approximations to RLS LMS Convergence Properties System Modeling Using Adaptive System Identification Signal Modeling Using Adaptive Signal-Whitening Filters Lattice and Schur Techniques Adaptive Least-Squares Lattice Algorithm Wiener Lattice Double/Direct Weiner Lattice MATLAB Examples Summary 314 Problems 315 References 316 Chapter 11 Recursive Adaptive Filtering Adaptive Kaiman Filtering IIR Forms for LMS and Lattice Filters Frequency Domain Adaptive Filters MATLAB Examples Summary 355 Problems 357 References 357 Part IV Wavenumber Sensor Systems Chapter 12 Signal Detection Techniques RicianPDF Time-Synchronous Averaging Envelope Detection of a Signal in Gaussian Noise RMS, CFAR Detection, and ROC Curves Statistical Modeling of Multipath Multisource Multipath Coherent Multipath Statistical Representation of Multipath Random Variations in Refractive Index MATLAB Examples Summary 392 Problems 394 References 394

6 xi Chapter 13 Wavenumber and Bearing Estimation Cramer-Rao Lower Bound Bearing Estimation and Beam Steering Bearings from Phase Array Differences Multiple Angles of Arrival Wavenumber Filters Field Reconstruction Techniques Wave Propagation Modeling MATLAB Examples Summary 438 Problems 439 References 439 Chapter 14 Adaptive Beamforming and Localization Array "Null-Forming" Eigenvector Methods of MUSIC and MVDR Coherent Multipath Resolution Techniques Maximal Length Sequences FMCW and Synthetic Aperture Processing MATLAB Examples Summary 478 Problems 480 References 481 Part V Signal Processing Applications Chapter 15 Noise Reduction Techniques Electronic Noise Noise Cancellation Techniques Active Noise Attenuation MATLAB Examples Summary 520 Problems 521 References 522 Chapter 16 Sensors and Transducers Simple Transducer Signals Acoustic and Vibration Sensors Electromagnetic Mechanical Transducer Electrostatic Transducer Condenser Microphone Micro-Electromechanical Systems Charge Amplifier Reciprocity Calibration Technique 552

7 xii 16.3 Chemical and Biological Sensors Detection of Small Chemical Molecules Optical Absorption Chemical Spectroscopy Raman Spectroscopy Ion Mobility Spectroscopy Detecting Large Biological Molecules Nuclear Radiation Sensors MATLAB Examples Summary 570 Problems 572 References 572 Chapter 17 Intelligent Sensor Systems Automatic Target Recognition Algorithms Statistical Pattern Recognition Adaptive Neural Networks Syntactic Pattern Recognition Signal and Image Features Basic Signal Metrics Pulse-Train Signal Models Spectral Features Monitoring Signal Distortion Amplitude Modulation Frequency Modulation Demodulation via Inverse Hilbert Transform Dynamic Feature Tracking and Prediction Intelligent Sensor Agents Internet Basics IP Masquerading/Port Forwarding Security versus Convenience Role of the DNS Server Intelligent Sensors on the Internet XML Documents and Schemas for Sensors Architectures for Net-Centric Intelligent Sensors MATLAB Examples Summary 640 Problems 642 References 643 Index 645