Optimum Array Processing (Detection, Estimation...

This file contains Matlab scripts for most of the figures in Chapters 2-7 and selected solutions in Chapters 2-6 of Optimum Array Processing by Harry L. Van Trees, Wiley, 2002. ISBN-13: 978-0471093909.

Optimum Array Processing gives an integrated presentation of classical and statistical array processing. Classical analysis and synthesis techniques for linear and planar arrays are developed. A statistical characterization of space-time random processes is provided. Many different aspects of optimum array processing are covered, including waveform estimation, adaptive beamforming, parameter estimation, and signal detection. Both plane-wave signals and spatially spread signals are studied, and all results are developed in a pedagogically sound manner.

Detection, Estimation, and Modulation Theory provides a fundamental understanding of array processing suitable for research or implementation of actual array processing systems. The book includes a variety of models and criteria for study and comparison, practical application examples of optimum algorithms, and numerous problems that expand the book's material.

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In 1987, Van Trees joined George Mason University (GMU) as a Distinguished Professor of Information Technology, and Electrical and Systems Engineering. Van Trees was also the founding director of Mason's Center of Excellence in Command, Control, Communications and Intelligence (C3I).[8][9] In 2002, Van Trees published the fourth volume of his textbook titled Optimum Array Processing. This textbook provided a more comprehensive look at optimum array processing. In 2013, Van Trees worked with Dr. Kristine L. Bell and Dr. Zhi Tian, both of GMU, to publish a second edition of the first volume.[10] This version was revised and expanded.[8]

In theory, one can design a perfect uniform linear array (ULA) to perform all sorts of processing such as beamforming or direction of arrival estimation. Typically this array will be calibrated in a controlled environment before being deployed. However, uncertainties may arise in the system during operation indicating that the array needs recalibrating. For instance, environmental effects may cause array element positions to become perturbed, introducing array shape uncertainties. The presence of these uncertainties causes rapid degradation in the detection, resolution and estimation performance of array processing algorithms. It is therefore critical to remove these array uncertainties as soon as possible.

The previous section shows the difference between the deployed array and an array which has undergone perturbations while in operation. If one blindly uses the processing designed for the deployed array, the performance of the array reduces. For example, consider a beamscan estimator is used to estimate the directions of 3 unknown sources at -20, 40 and 85 degrees azimuth.

Course Contents:

This project-seminar addresses new trends in sensor array and multichannel processing with multidimensional tensor data representations.

The specific thematic focus of the seminar will be adapted from year to year according to the latest trends in the research field. The topics will be announced on the course website well in advance.

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