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Prediction of inverse covariance matrix (PICM) sequences for STAP

机译:STAP逆协方差矩阵(PICM)序列的预测

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In this letter, we study issues associated with applying least-squares estimation to predict the inverse covariance matrix in bistatic airborne radar systems. For the bistatic ground moving target indication radar, the clutter Doppler frequency depends on the range for all array geometries. This range dependency leads to problems in clutter suppression through space-time adaptive processing (STAP) techniques. This paper proposes a new method of obtaining an estimate of the inverse covariance matrix using linear prediction techniques. Simulation results show a significant improvement in processor performance as compared to conventional STAP methods.
机译:在这封信中,我们研究了与应用最小二乘估计来预测双基地机载雷达系统中逆协方差矩阵有关的问题。对于双基地地面移动目标指示雷达,杂波多普勒频率取决于所有阵列几何形状的范围。这种距离依赖性导致通过时空自适应处理(STAP)技术抑制杂波的问题。本文提出了一种使用线性预测技术获得逆协方差矩阵估计的新方法。仿真结果表明,与传统的STAP方法相比,处理器性能有了显着提高。

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