A knowledge aided GMTI detection architecture
William L. Melvin - Georgia Tech Research Institute
Wed, 28 April 2004, 10:20 AM - 12:00 PM
Abstract?Space-time adaptive processing (STAP) plays an important role in ground moving target indication (GMTI). Heterogeneous clutter environments prevent STAP from achieving its theoretical performance bounds. The incorporation of a priori knowledge into the signal processing architecture holds the potential to greatly enhance detection performance by mitigating heterogeneous clutter effects. In this paper we propose one possible knowledge-aided STAP approach comprised of the following elements: a knowledge-aided prediction/estimation filter, a discrete matched filter, and a partially adaptive STAP applied to the clutter residual, assisted by knowledge-aided training. We focus our discussion on justifying the aforementioned elements and independently characterizing their performance potential. Using both measured and simulated data, we find the potential for substantial performance improvement.
Dr. William L. Melvin - Georgia Tech Research Institute
Dr. William Melvin is a Senior Research Engineer at the Georgia Tech Research Institute and an Adjunct Professor in Georgia Tech?s Electrical and Computer Engineering Department. He specializes in sensor signal and array processing, modeling and simulation, and aerospace radar systems engineering. He directs research efforts focused on next generation sensor systems and adaptive processing methods, holds three US patents on adaptive radar technology, and has authored numerous technical publications. He served as a guest editor for a recent special edition on STAP in the IEEE Transactions on Aerospace and Electronic Systems and acted as the Technical Co-Chair of the 2001 IEEE Radar Conference. Dr. Melvin received a ?Best Paper? award at the 1997 IEEE Radar Conference. Additionally, in 2002 he represented the US as a speaker on the NATO-sponsored ?Military Applications of Space-Time Adaptive Processing? lecture series.