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Interference Estimation and Mitigation for STAP Using the Two- Dimensional Wold Decomposition Parametric Model

机译：基于二维Wold分解参数模型的sTap干扰估计与缓解

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摘要

The goal of space-time adaptive processing (STAP) is to manipulate the available data to achieve high gain at the target angle and Doppler and maximal mitigation along both the jamming and clutter lines. Because the interference covariance matrix is unknown a priori, it is typically estimated using sample covariances obtained from averaging over a few range gates. The authors propose a new approach for parametric modeling and estimation of STAP data, based on the two-dimensional, Wold-like decomposition of random fields. The proposed parametric estimation algorithms of the interference components simplify and improve existing STAP methods. The resulting modeling and processing methods provide new parametric tools to estimate and mitigate the Doppler ambiguous clutter. The estimation algorithms the authors propose enable the estimation of the interference signals using the observations in only a single range gate. The proposed method is particularly suitable for non- stationary clutter and jamming environments. The approach provides a new analytical insight into the STAP problem.

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