SA-TWG Webinar: Mathematical Models vs. Reality in Array Signal Processing

Date: 25 October 2023
Time: 11:00 AM ET (New York Time)
Speaker(s): Dr. Benjamin Friedlander


Mathematical models play a key role in array signal processing, providing the basis for system development, derivation of new algorithms and doing performance analysis. The usefulness of these models depends, among other things, on how well they represent the behavior of real arrays. This talk presents the basic mathematical models used in the array signal processing literature and their differences from the behavior of real arrays as predicted by electromagnetic theory. To discuss these differences, we use the widely popular uniform linear antenna array (ULA) as a convenient starting point. We address in some detail the correct modeling of mutual coupling and its effect on array calibration. We discuss the use of the manifold and covariance structures on the development of array processing algorithms, and the effects of element spacing and signal polarization. We briefly discuss the use of these models in studying near field effects, sparse arrays and the number of signals which can be estimated by an array. Finally, we present some suggestions for handling the problems identified in this talk.

The talk attempts to bridge the gap between the array processing work done in the signal processing community and the corresponding work done in the electromagnetic community. The intended audience are researchers familiar with the work on array processing from the signal processing perspective, who would like to know more about how this work is related to real array systems. The talk is at a descriptive / overview level and should be easy to follow.


Benjamin Friedlander is a professor emeritus in the department of electrical and computer engineering at the University of California at Santa Cruz. His research is in the area of statistical signal processing theory: detection, estimation, filtering; algorithm development and performance analysis. He has extensive experience in applications of statistical signal processing to various engineering problems, including: Array processing for radar, acoustic/sonar, and communications systems; Direction finding and Geo-location; Wireless communications systems; Digital signal processing; and Adaptive systems.