Knowledge-Based Control for Space Time Adaptive Processing
Abstract
The major impact of the research reported herein is the development of an adaptive algorithm that specifically addresses the rejection of discretes in the cell under test competing with all targets; and the rejection of distributed clutter competing with slow moving targets. Discretes can include large fixed clutter returns and multiple moving objects in the sidelobes. This report discusses the development of space-time adaptive processing (STAP) technology for ground moving target indication (GMTI) applications. Current GMTI systems, e.g. the E-8 Joint STARS, use nonadaptive displaced phase center antenna (DPCA) techniques. The Joint STARS platform has been very successful in certain deployments, such as the Gulf War. So the question naturally arises, why is STAP needed for GMTI? STAP has demonstrated much better clutter rejection than DPCA for high velocity targets. The objective of this research is to extend the advantages of STAP in the high velocity region to lower velocity targets. This requires some fundamental redesign of the STAP process. This report summarizes past, present and proposed future STAP research. The theme of this research has been to move from AMTI STAP theory to GMTI STAP for real systems. Our ongoing research moves towards the Knowledge Based STAP (KB-STAP) concept where the adaptive algorithm and its associated training is chosen "intelligently" to best detect weak and slow moving targets. Here we present the use of terrain maps to determine the sample support for the adaptive process. The use of maps allows the adaptive process to choose the best representative sample support to estimate the clutter covariance matrix. This approach is a first step to the development of practical KB-STAP.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2006
- Accession Number
- ADA472794
Entities
People
- Michael C. Wicks
Organizations
- Rome Laboratory