《陣列信號處理與空時二維信號處理（英文版）》是2023年上海交通大學出版社出版的圖書。
基本介紹
- 中文名：陣列信號處理與空時二維信號處理（英文版）
- 出版時間：2023年2月
- 出版社：上海交通大學出版社
- ISBN：9787313262769
內容簡介,圖書目錄,
內容簡介
本書共 ５ 章，主要內容包括信號處理簡介、陣列信號處理、自適應陣列信號處理、空時二維陣列信號處理等。 本書第 ２、３ 章重點討論了陣列信號處理的基本理論和模型、自適應陣列系統的理論和結構，以及多種自適應波束形成方法和自適應陣列信號處理方法等；第 ４ 章則重點介紹空時小均方誤差接收機和似然序列估計接收機等，並將它們與傳統一維陣列信號處理接收機對比，討論其優點。 本書可供無線通信、通信信號處理、雷達陣列信號處理等專業方向的研究生學習使用，也可作為無線通信專業從業人員的參考用書。
圖書目錄
1 Introduction
1.1 Main Contents of the Book
1.2 Some Real Examples of Array
1.3 Chapter Summary
1.4 Chapter Assignments
2 Array Signal Processing
2.1 Plane Wave and Array
2.2 Uniform Linear Array.Uniform Circular Array and Uniform
Plane Array
2.2.1 ULA(uniform linear alray)
2.2.2 Array Response and Pattern of ULA
2.2.3 UCA(uniform circular array)
2.2.4 UPA(uniform plane array)
2.3 Statistical Model of Array Signal Processing
2.3.1 Time Delay of Narrow-band Signal
2.3.2 Continuous-time Channel Model
2.3.3 Statistical Model of Array Signal Processing
2.4 Beamforming
2.4.1 Optimal Weight Vector of Beamforming
2.4.2 Bartlett Beamformer
2.4.3 Capon Beamformer
2.5 MUSIC Algorithm
2.5.1 Basic MUSIC Algorithm
2.5.2 Improvement of MUSIC Algorithm
2.5.3 Root-MUSIC Algorithm
2.6 ESPIUT Algorithm
2.6.1 Basic ESPⅪT Algorithm
2.6.2 TLS.ESPIuT Algorithm
2.7 Maximum Likefihood Method
2.7.1 Deterministic M[L
2.7.2 Stochastic MrL
2.8 Iterative Quadratic Maximum Likelihood Method
2.8.1 Sub.space Fitting
2.8.2 IQML
2.8.3 MODE Algorithm and Weighted Sub-space Fitting
Algorithm
2.9 Chapter Summary
2.10 Chapter Assignments
3 Adaptive Array Signal Processing
3.1 Theorems of Adaptive Antenna System
3.1.1 Impulse Response of Vector Channel and Spafial
Characteristics
3.1.2 Optimal Weight Vector of Adaptive Array
3.1.3 Adaptive Algorithm with Weight Vector Updating
3.2 Influences of Multipath to the Optimal Spatial Filtering
3.3 Stochastic Blind Beamforming
3.3.1 Blind Beamforming based on High-order Cumulant
3.3.2 Blind Beamforming Based on Cyclic Statistics
3.4 Deterministic Blind Beamforming
3.4.1 Homogeneous MⅣO Model of the Channel
3.4.2 Deterministic Blind Beamforming
3.5 Blind Signal Separation
3.5.1 Blind Identifiabilit、
3.5.2 Equivariant Signal Separation
3.5.3 Second.order Identification Method
3.5.4 Joint Diagonalization of Multiple Matrices
3.6 Neural Networks MethOd Of Blind Signal Separation
3.6.1 Independent Component Analysis and Principal
Component Analysis
3.6.2 Neural Network Structure of Blind Signal Separation
3.6.3 Natural Gradient Algorithm of Blind Signal Separation
3.7 Least Square Constant Modulus Algorithm
3.7.1 Steepest Descent CM Algorithm
3.7.2 Least Square CM Algorithm(LS。CMA)
3.7.3 Sub-Gaussian and Super.Gaussian Signal
3.7.4 CM Cost Function
3.8 Constant Modulus Array
3.8.1 CM Array and Adaptive Signal Canceller
3.8.2 Performance Analysis
3.8.3 CM Array to Recover Multiple Sources
3.8.4 Output S斟R and SNR
3 9 Multitarget Adaptive Beamformer
3.9.1 Multitarget LS-CMA(MT-LS-CMA)
3.9.2 Signal Classification
3.9.3 Multitarget Decision.directed Algorithm(MT-DDA)
3.10 Least Squares Despread Re-spread Multitarget Array
(LS-DRMTA)
3.10.1 LS.DRMTA
3.10.2 LS-DRMT-CMA
3.1 l Adaptive Array Signal Processing Based on Sub-space
3.11.1 Signal Model and Optimal Combination
3.1 1.2 Adaptive Array Algorithm Based OD Sub-space
3.12 Chapter Summary
3.13 Chapter Assignments
4 Space-Time Signal Processing
4.1 Limitations of One-Dimensional Processing
4.1.1 Limitations of One-Dimensional Processing in Time
Domain
4.1.2 The Limitation of One-Dimensional Processing in
Space Domain
4.2 Discrete Space.Time Channel and Signal Model
4.2.1 Discrete Space-Time Channel Model
4.2.2 Discrete Space-Time Signal Model
4.3 Space.Time M[MSE Receiver
4.3.1 Space.Time MMSE Criterion
4.3.2 Space.Time Equalizer
4.4 Space-Time MLSE Receiver
4.4.1 Space-Time MLSE Criterion
4.4.2 Space-Time MLSE Method
4.5 Space-Time Blind Equalization
4.5.1 Problem Description
4.5.2 Space-Time Blind Equalization
4.5.3 CM Algorithm Based on Weight Vector Updating
4.6 Space-Time Blind Beamforming
4.6.1 FIR MIMO Model of Space-Time Channel
4.6.2 Space-Time Blind Beamforming
4.7 Space-Time Two-Dimensional RAKE Receiver
4.7.1 Signal Model
4.7.2 Space.Time Two.dimensional RAKE Receiver Based
on Matched Filter
4.8 Chapter Summary
4.9 Chapter Assignments
5 Summary
5.1 Book Summary
5.2 Prospects
References
