Adaptive and Array Signal Processing - 2023.2

Objectives:

The objective of the course is to introduce the fundamentals of adaptive and array signal processing using linear algebra, optimisation and intuition. The main focus is on filtering and estimation techniques and beamforming and direction finding methods and their application in several areas of electrical engineering (communications, control, time-series analysis, sensing, defence systems, etc).

Syllabus:

I. Mathematical fundamentals

II. Adaptive signal processing and applications

III. Optimal filters

IV. The Steepest Descent Method

V. LMS Type Algorithms

VI. LS Type Algorithms

VII. Sensor Array Processing

VIII. Beamforming Techniques

IX. Direction finding

Assessment:

The assessment is based on lists of tutorial questions (L), an exam paper (E) and a project (P) . The final grade is given by FG = (P + E+ L)/3.

Tutorial questions:

List 1

List 2

List 3

List 4

List 5

List 6

List 7

List 8

Matlab codes:

System identification with LMS - code

Distributed LMS using diffusion - code

Echo cancellation - code

MVDR beamforming - code

Direction finding - code

References:

1. HAYKIN, S., Adaptive Filter Theory. 4a Ed. Prentice Hall, 2002.

2. VAN TREES, H. L., Optimum Array Processing. Wiley, 2002.

3. DINIZ, P. S. R., Adaptive Filtering: Algorithms and Practical Implementation, 2nd Edition, Kluwer, 2002.

4. SAYED, A. H., Adaptive Filters. Wiley, 2008.

5. JOHNSON, D.H., DUDGEON, D. E., Array Signal Processing. Prentice Hall, 1993.