一种新的机载STAP杂波协方差矩阵重构方法

Mingxin Liu, L. Zou, Xue-gang Wang
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引用次数: 0

摘要

在空时自适应处理(STAP)中,通常由训练快照估计的杂波加噪声协方差矩阵(CNCM)是获得权向量的关键。然而,CNCM在小样本情况下难以准确估计,严重影响了目标估计。为了解决这一问题,提出了一种新的CNCM重构方法。该方法利用Toeplitz结构对CNCM进行重构,并推导出估计的CNCM的封闭表达式。最后,建立了权重向量,便于对目标信号进行检测和分析。仿真结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Clutter Covariance Matrix Reconstruction Method for Airborne STAP
The clutter plus noise covariance matrix (CNCM) usually estimated by the training snapshots is the key to obtain the weight vector in space-time adaptive processing (STAP). However, the CNCM is difficult to estimate accurately in small samples, which affects the target estimation seriously. To solve this problem, a novel CNCM reconstruction method is developed. The proposed method reconstructs the CNCM with Toeplitz structure and then derives closed-form expression for the estimated CNCM. Finally, the weight vector is built, which is convenient to detect and analyze the target signals. The effectiveness of the proposed approach is shown in simulated results.
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