《阵列信号处理与空时信号处理》课程简介

Introduction of Array Signal Processing and Space-Time Signal Processing

课程名称 (Course Name) ：Array Signal Processing and Space-Time Signal Processing

课程代码 (Course Code）：F034605

学分/学时 (Credits/Credit Hours)：2/32

开课时间 (Course Term )：春spring

开课学院（Course School）: 电子信息与电气工程学院  SEIEE

任课教师（Teacher）:  He Di (何迪)

课程讨论时数（Course Hours）:     3  小时(Hours)

课程实验数（Lab Hours）:     0   小时(Hours)

课程内容简介(Course Contents Introduction):

The main contents of this course include the array signal processing, adaptive array signal processing and space-time signal processing which are usually used in the wireless communications. The knowledge taught and discussed in this course may bring interests to the graduate students whose research areas are related. The learning of this course requires the students have intimate knowledge of wireless communications and the theory of matrices.

教学大纲(Course Outline):

There are three main parts of knowledge in the whole course which are related to each other as array signal processing, adaptive array signal processing and space-time signal processing. In each part of the knowledge, there are also many knowledge points which should be grasped through the course, as listed as follows:

1.    Array signal processing: Discuss the basic theory and models of array signal processing, introduce some beamformers including Bartlett beamformer and Capon beamformer, and some DOA estimation methods including MUSIC algorithm, ESPRIT algorithm, maximum likelihood algorithm and IQML algorithm.

2.    Adaptive array signal processing: First introduce the theory and structure of adaptive array system, analyze the influence of multi-path to the optimal spatial filtering. Then introduce the stochastic and definite blind beamforming, blind signal separation and its NN method. Discuss the theory, method and application of CM array, including LS-CMA, analytical CMA, CM-array, MT adaptive beamforming, DR-MT array. At last, the adaptive array processing based on sub-space is also introduced.

3.    Space-time signal processing: Fist discuss the disadvantages of one-dimensional signal processing, and then introduce the discrete space-time channel model and corresponding signal model to establish the space-time two-dimensional array signal processing model. Introduce the space-time MMSE receiver and MLSE receiver, and discuss their advantages compared with conventional one-dimensional array signal processing receivers.

课程进度计划(Course Schedule):

1.    Course introduction; Plane wave and array; Uniform linear array and uniform circular array (1st week)

2.    Statistical model of array signal processing; beamforming (2nd week)

3.    MUSIC algorithm; ESPRIT algorithm (3rd week)

4.    Maximum likelihood method; Iterative quadratic maximum likelihood (4th week)

5.    Theorem of adaptive antenna system; Influences of multi-path to the optimal spatial filtering (5th week)

6.    Stochastic blind beamforming; Deterministic blind beamforming (6th week)

7.    Blind signal separation; Neural networks method of blind signal separation (7th week)

8.    Least square constant modulus algorithm; Constant modulus array; Multitarget adaptive beamformer (8th week)

9.    Limitation of one-dimension process; Discrete space-time channel and signal model (9th week)

10.  Space-time MMSE receiver; Space-time MLSE receiver (10th week)

11.  Course discussion (11th week)

课程考核要求(Course Examination Requirements)：

1. A research report regarding the recent advances in array signal processing and space-time Signal processing

2. Final Examination

参考文献(Course References)：

[1] Prabhakar S. Naidu. Sensor Array Signal Processing. CRC Press, 2001.

[2] Wulf-Dieter Wirth. Radar Techniques using Array Antennas. The Institution of Electrical Engineers, London, 2001.

[3] 张贤达，保铮，《通信信号处理》，国防工业出版社，2000年