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首页> 外文期刊>IEEE Transactions on Signal Processing >Knowledge-Aided Range-Spread Target Detection for Distributed MIMO Radar in Nonhomogeneous Environments
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Knowledge-Aided Range-Spread Target Detection for Distributed MIMO Radar in Nonhomogeneous Environments

机译：非均匀环境中分布式MIMO雷达的知识辅助测距目标检测

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摘要

This paper deals with the problem of detecting a moving range-spread target in distributed MIMO radar. A new knowledge-aided (KA) model that takes into account the nonhomogenous characteristics of the disturbance (clutter and noise) in distributed MIMO radar is proposed. Specifically, the disturbance covariance matrices corresponding to different transmit-receive (Tx-Rx) pairs are modeled as random matrices. These covariance matrices share a prior covariance matrix structure but with different power levels to model the nonhomogeneous clutter powers across different Tx-Rx pairs. Two cases are considered, involving either no range training (i.e., when the disturbance is highly nonhomogeneous) or some range training data. For the first case, we develop a KA generalized likelihood ratio test (GLRT) for range-spread target detection, along with a simplified version of the KA-GLRT for point-like target detection. For the second case, the KA-GLRT becomes computationally intractable, a simple ad-doc KA detector is introduced to take advantage of training data for range-spread target detection. Simulation results are presented to illustrate the performance and effectiveness of the proposed detectors in nonhomogeneous environments.
机译：本文讨论了在分布式MIMO雷达中检测运动范围扩展目标的问题。提出了一种新的知识辅助（KA）模型，该模型考虑了分布式MIMO雷达中干扰（杂波和噪声）的非均匀特性。具体而言，将与不同的发射-接收（Tx-Rx）对相对应的干扰协方差矩阵建模为随机矩阵。这些协方差矩阵共享先验的协方差矩阵结构，但具有不同的功率水平，以模拟不同Tx-Rx对之间的非均匀杂波功率。考虑了两种情况，它们不涉及范围训练（即，当干扰非常不均匀时）或一些范围训练数据。对于第一种情况，我们开发了用于范围扩展目标检测的KA广义似然比测试（GLRT），以及用于点状目标检测的KA-GLRT的简化版本。对于第二种情况，KA-GLRT在计算上变得棘手，引入了一个简单的ad-doc KA检测器，以利用训练数据进行距离扩展目标检测。仿真结果表明了所提出的探测器在非均匀环境中的性能和有效性。

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