A comprehensive guide to the theory and practice of signal enhancement and array signal processing, including matlab codes, exercises and instructor and solution manuals Systematically introduces the fundamental principles, theory and applications of signal enhancement and array signal processing in an accessible manner Offers an updated and relevant treatment of array signal processing with rigor and concision Features a companion website that includes presentation files with lecture notes, homework exercises, course projects, solution manuals, instructor manuals, and Matlab codes for the examples in the book

A comprehensive guide to the theory and practice of signal enhancement and array signal processing, including matlab codes, exercises and instructor and solution manuals* Systematically introduces the fundamental principles, theory and applications of signal enhancement and array signal processing in an accessible manner* Offers an updated and relevant treatment of array signal processing with rigor and concision* Features a companion website that includes presentation files with lecture notes, homework exercises, course projects, solution manuals, instructor manuals, and Matlab codes for the examples in the book

Preface vii1 Introduction 11.1 Signal Enhancement 11.2 Approaches to Signal Enhancement 91.3 Array Signal Processing 111.4 Organization of the Book 141.5 How to Use the Book 162 Single-Channel Signal Enhancement in the Time Domain 212.1 Signal Model and Problem Formulation 212.2 Wiener Method 222.3 Spectral Method 402.4 Problems 553 Single-Channel Signal Enhancement in the Frequency Domain 613.1 Signal Model and Problem Formulation 613.2 Noise Reduction with Gains 623.3 Performance Measures 633.4 Optimal Gains 663.5 Constraint Wiener Gains 813.6 Implementation with the Short-Time Fourier Transform 873.7 Problems 954 Multichannel Signal Enhancement in the Time Domain 1014.1 Signal Model and Problem Formulation 1014.2 Conventional Method 1024.3 Spectral Method 1164.4 Case of a Rank Deficient Noise Correlation Matrix 1314.5 Problems 1365 Multichannel Signal Enhancement in the Frequency Domain 1435.1 Signal Model and Problem Formulation 1435.2 Linear Filtering 1465.3 Performance Measures 1475.4 Optimal Filters 1525.5 Generalized Sidelobe Canceller Structure 1715.6 A Signal Subspace Perspective 1735.7 Implementation with the STFT 1825.8 Problems 1886 An Exhaustive Class of Linear Filters 1976.1 Signal Model and Problem Formulation 1976.2 Linear Filtering for Signal Enhancement 1996.3 Performance Measures 2006.4 Optimal Filters 2026.5 Filling the Gap Between the Maximum SINR and Wiener Filters 2146.6 Problems 2217 Fixed Beamforming 2277.1 Signal Model and Problem Formulation 2277.2 Linear Array Model 2287.3 Performance Measures 2297.4 Spatial Aliasing 2327.5 Fixed Beamformers 2337.6 A Signal Subspace Perspective 2537.7 Problems 2618 Adaptive Beamforming 2718.1 Signal Model, Problem Formulation, and Array Model 2718.2 Performance Measures 2728.3 Adaptive Beamformers 2748.4 SNR Estimation 2878.5 DOA Estimation 2908.6 A Spectral Coherence Perspective 2948.7 Problems 3029 Differential Beamforming 3099.1 Signal Model, Problem Formulation, and Array Model 3099.2 Beampatterns 3109.3 Front-to-Back Ratios 3119.4 Array Gains 3139.5 Examples of Theoretical Differential Beamformers 3149.6 First-Order Design 3179.7 Second-Order Design 3209.8 Third-Order Design 3289.9 Minimum-Norm Beamformers 3359.10 Problems 34110 Beampattern Design 34910.1 Beampatterns Revisited 34910.2 Nonrobust Approach 35310.3 Robust Approach 35510.4 Frequency-Invariant Beampattern Design 35810.5 Least-Squares Method 36110.6 Joint Optimization 36710.7 Problems 37811 Beamforming in the Time Domain 38311.1 Signal Model and Problem Formulation 38311.2 Broadband Beamforming 38611.3 Performance Measures 38711.4 Fixed Beamformers 39111.5 Adaptive Beamformers 40111.6 Differential Beamformers 41311.7 Problems 423Index 429