Open AccessFeature PaperArticle
Knowledge-Aided Covariance Matrix Estimation in Spiky Radar Clutter Environments
by
Jeong H. Bang 1, William L. Melvin 2,* and Aaron D. Lanterman 1
1
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
2
Georgia Tech Research Institute, Georgia Institute of Technology, Atlanta, GA 30332, USA
Cited by 3 | Viewed by 5530
Abstract
Space-time adaptive processing (STAP) is an important airborne radar technique used to improve target detection in clutter-limited environments. Effective STAP implementation is dependent on accurate space-time covariance matrix estimation. Heterogeneous clutter, including spiky, spatial clutter variation, violates underlying STAP training assumptions and can
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Space-time adaptive processing (STAP) is an important airborne radar technique used to improve target detection in clutter-limited environments. Effective STAP implementation is dependent on accurate space-time covariance matrix estimation. Heterogeneous clutter, including spiky, spatial clutter variation, violates underlying STAP training assumptions and can significantly degrade corresponding detection performance. This paper develops a spiky, space-time clutter model based on the K-distribution, assesses the resulting impact on STAP performance using traditional methods, and then proposes and evaluates the utility of the knowledge-aided parametric covariance matrix estimation (KAPE) method, a model-based scheme that rapidly converges to better represent spatial variation in clutter properties. Via numerical simulation of an airborne radar scenario operating in a spiky clutter environment, we find substantial improvement in probability of detection (
) for a fixed probability of false alarm (
) for the KAPE method. For example, in the spiky clutter environment considered herein, results indicate a
of 32% for traditional STAP and in excess of 90% for KAPE at a
of 1E-4, with a corresponding difference of 11.5 dB in threshold observed from exceedance analysis. The proposed K-distributed spiky clutter model, and application and assessment of KAPE as an ameliorating STAP technique, contribute to an improved understanding of radar detection in complex clutter environments.
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