2nd Edition

Signal Processing for Intelligent Sensor Systems with MATLAB®

By David C. Swanson Copyright 2011
    683 Pages 380 B/W Illustrations
    by CRC Press

    684 Pages 380 B/W Illustrations
    by CRC Press

    Signal Processing for Intelligent Sensors with MATLAB®, Second Edition once again presents the key topics and salient information required for sensor design and application. Organized to make it accessible to engineers in school as well as those practicing in the field, this reference explores a broad array of subjects and is divided into sections: Fundamentals of Digital Signal Processing, Frequency Domain Processing, Adaptive System Identification and Filtering, Wavenumber Sensor Systems, and Signal Processing Applications.

    Taking an informal, application-based approach and using a tone that is more engineer-to-engineer than professor-to-student, this revamped second edition enhances many of the features that made the original so popular. This includes retention of key algorithms and development methodologies and applications, which are creatively grouped in a way that differs from most comparable texts, to optimize their use.

    New for the Second Edition:

    • Inclusion of more solved problems
    • Web access to a large collection of MATLAB® scripts used to support data graphs presented throughout the book
    • Additional coverage of more audio engineering, transducers, and sensor networking technology
    • A new chapter on Digital Audio processing reflects a growing interest in digital surround sound (5.1 audio) techniques for entertainment, home theaters, and virtual reality systems
    • New sections on sensor networking, use of meta-data architectures using XML, and agent-based automated data mining and control

    Serving dual roles as both a learning resource and a field reference on sensor system networks, this book progressively reveals digestible nuggets of critical information to help readers quickly master presented algorithms and adapt them to meet their requirements. It illustrates the current trend toward agile development of web services for wide area sensor networking and intelligent processing in the sensor system networks that are employed in homeland security, business, and environmental and demographic information systems.

    Part I: Fundamentals of Digital Signal Processing

    Sampled Data Systems
    A/D Conversion
    Sampling Theory
    Complex Bandpass Sampling
    Delta–Sigma Analog Conversion

    Z-Transform
    Comparison of Laplace and z-Transforms
    System Theory
    Mapping of s-Plane Systems to the Digital Domain

    Digital Filtering
    FIR Digital Filter Design
    IIR Filter Design and Stability
    Whitening Filters, Invertibility, and Minimum Phase
    Filter Basis Polynomials

    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

    Linear Filter Applications
    State Variable Theory
    Fixed-Gain Tracking Filters
    2D FIR Filters
    Image Upsampling Reconstruction Filters

    Part II: Frequency Domain Processing

    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

    Spectral Density
    Spectral Density Derivation
    Statistical Metrics of Spectral Bins
    Transfer Functions and Spectral Coherence
    Intensity Field Theory
    Intensity Display and Measurement Techniques

    Wavenumber Transforms
    Spatial Transforms
    Spatial Filtering and Beamforming
    Image Enhancement Techniques
    JPEG and MPEG Compression Techniques
    Computer-Aided Tomography
    Magnetic Resonance Imaging

    Part III: Adaptive System Identification and Filtering

    Linear Least-Squared Error Modeling
    Block Least Squares
    Projection-Based Least Squares
    General Basis System Identification

    Recursive Least-Squares Techniques
    RLS Algorithm and Matrix Inversion Lemma
    LMS Convergence Properties
    Lattice and Schur Techniques
    Adaptive Least-Squares Lattice Algorithm

    Recursive Adaptive Filtering
    Adaptive Kalman Filtering
    IIR Forms for LMS and Lattice Filters
    Frequency Domain Adaptive Filters

    Part IV: Wavenumber Sensor Systems

    Signal Detection Techniques
    Rician PDF
    RMS, CFAR Detection, and ROC Curves
    Statistical Modeling of Multipath

    Wavenumber and Bearing Estimation
    Cramer–Rao Lower Bound
    Bearing Estimation and Beam Steering
    Field Reconstruction Techniques
    Wave Propagation Modeling

    Adaptive Beamforming and Localization
    Array "Null-Forming"
    Eigenvector Methods of MUSIC and MVDR
    Coherent Multipath Resolution Techniques
    FMCW and Synthetic Aperture Processing

    Part V: Signal Processing Applications

    Noise Reduction Techniques
    Electronic Noise
    Noise Cancellation Techniques
    Active Noise Attenuation

    Sensors and Transducers
    Simple Transducer Signals
    Acoustic and Vibration Sensors
    Chemical and Biological Sensors
    Nuclear Radiation Sensors

    Intelligent Sensor Systems
    Automatic Target Recognition Algorithms
    Signal and Image Features
    Dynamic Feature Tracking and Prediction
    Intelligent Sensor Agents

    Biography

    David C. Swanson