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Moving target detection for polarimetric multiple-input multiple-output radar in Gaussian clutter

机译:高斯杂波中偏振多输入多输出雷达的运动目标检测

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This study deals with the problem of moving target detection (MTD) for polarimetric multiple-input multiple-output (MIMO) radar in the presence of Gaussian clutter. The authors extend the framework for MTD with MIMO radar to a generic number polarisation channels case. Within the polarimetric framework, the new generalised likelihood ratio test for moving target is first proposed. Then, the target velocity estimation problem is investigated. The maximum-likelihood (ML) estimator for target velocity is developed, and the corresponding Cramer-Rao bound is derived which serves as a benchmark of the estimation performance. Next, the adaptive version of the new polarimetric detector is considered. The covariance matrix is estimated using the sample covariance matrix and the model-based strategies based on the secondary data. Finally, several numerical simulations of the proposed polarimetric detector and ML estimator with typical parameters are obtained and discussed.
机译:这项研究解决了在存在高斯杂波的情况下极化多输入多输出(MIMO)雷达的运动目标检测(MTD)问题。作者将带有MIMO雷达的MTD框架扩展到通用数极化信道情况。在极化框架内,首先提出了针对运动目标的新型广义似然比检验。然后,研究目标速度估计问题。开发了目标速度的最大似然(ML)估计器,并推导了相应的Cramer-Rao界,作为估计性能的基准。接下来,考虑新的偏振检测器的自适应版本。使用样本协方差矩阵和基于辅助数据的基于模型的策略来估计协方差矩阵。最后,获得并讨论了所提出的具有典型参数的偏振检测器和ML估计器的数值模拟。

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