Space-Time Adaptive Processing (STAP) for Heterogeneous Radar Clutter Scenarios
This talk will provide an overview of radar STAP starting from the early work of Howells, Applebaum and Widrow on adaptive arrays. The sample matrix inversion (SMI) method and its variants will be discussed in some detail from the standpoint of constant false alarm rate (CFAR) and training data support for covariance matrix estimation. Candidate reduced-dimension methods will also be discussed. Problems encountered in covariance estimation on account of heterogeneous training data will be discussed from a phenomenological, systems, and statistical perspective. The resulting impact on STAP algorithm performance will be addressed. Statistical and ad hoc techniques for characterizing heterogeneous training data will be discussed. Intelligent training data selection schemes will be presented and analyzed. The performance of candidate STAP methods employing intelligent training data selection will be presented using simulated and measured data.
Dr. Muralidhar Rangaswamy
Adjunct Professor of Electrical and Computer Engineering, Purdue University
Date: April 7, 2006 at 12:00 PM
Location: Engineering Building II, Room 1230
The Department of Electrical and Computer Engineering hosts a regularly scheduled seminar series with preeminent and leading reseachers in the US and the world, to help promote North Carolina as a center of innovation and knowledge and to ensure safeguarding its place of leading research.