Clutter covariance matrix estimation using weight vectors in knowledge‐aided STAP. Issue 8 (1st April 2017)

• Record Type: Journal Article
• Authors: Jeon, H.; Chung, Y.; Chung, W.; Kim, J.; Yang, H.
• Is Part Of: Electronics letters. Volume 53:Issue 8(2017)
• Page Start: 560
• Page End: 562
• Publication Date: 2017-04-01
• Subjects: space‐time adaptive processing -- radar clutter -- radar signal processing -- covariance matrices -- estimation theory -- numerical analysis; target detection -- bistatic radar -- numerical simulation -- clutter‐to‐noise ratio -- nonstationary clutter suppression -- heterogeneous clutter suppression -- knowledge‐aided space–time adaptive processing -- knowledge‐aided STAP -- weight vectors -- clutter covariance matrix estimation; Electronics -- Periodicals; 621.381
• DOI: 10.1049/el.2016.4631
• Languages: English
• ISSNs: 0013-5194

Abstract

Abstract : A knowledge‐aided space–time adaptive processing (STAP) is a quite useful technique to suppress non‐stationary and heterogeneous clutter. It estimates a covariance matrix by combining a conventional covariance matrix based on secondary data with a synthesised one by prior information. A new combining method is presented, where weight vectors, rather than constant weights, are used to combine two covariance matrices. In this method, the weight vectors are derived in a way to maximise clutter‐to‐noise ratio of the combined covariance matrix. A numerical simulation is conducted for a bistatic radar scenario where clutter non‐stationarity and heterogeneity can be assumed and the performance of the proposed method is demonstrated in terms of clutter suppression and target detection.