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Electronics 2017, 6(1), 20; doi:10.3390/electronics6010020

Knowledge-Aided Covariance Matrix Estimation in Spiky Radar Clutter Environments

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
*
Author to whom correspondence should be addressed.
Academic Editors: John E. Ball and Nicolas H. Younan
Received: 31 December 2016 / Revised: 17 February 2017 / Accepted: 3 March 2017 / Published: 9 March 2017
(This article belongs to the Special Issue Radio and Radar Signal Processing)
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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 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 ( P D ) for a fixed probability of false alarm ( P F A ) for the KAPE method. For example, in the spiky clutter environment considered herein, results indicate a P D of 32% for traditional STAP and in excess of 90% for KAPE at a P F 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. View Full-Text
Keywords: radar; space-time adaptive processing (STAP); knowledge-aided space-time adaptive processing (KA-STAP) radar; space-time adaptive processing (STAP); knowledge-aided space-time adaptive processing (KA-STAP)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Bang, J.H.; Melvin, W.L.; Lanterman, A.D. Knowledge-Aided Covariance Matrix Estimation in Spiky Radar Clutter Environments. Electronics 2017, 6, 20.

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