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Target detection in distributed MIMO radar with registration errors

机译:具有配准误差的分布式MIMO雷达中的目标检测

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摘要

In this paper, we consider a target detection problem in a distributed multiple-input multiple-output radar with registration errors. Registration errors mean the alignment errors when observation data from different distributed radars are transformed in a common coordinate system. Our study is motivated by the fact that the perfect registration condition is unavailable in practice, even after a registration process. A model for the imperfect registration is introduced where an uncertainty window centered on the cell being tested along range and azimuth in each spatial diversity channel is employed. A generalized likelihood ratio test (GLRT) detector and a Bayesian likelihood ratio test detector are developed based on the uncertainty windows. The probability of false alarm of the proposed GLRT detector is derived. For convenience of comparison, we also analyze the detection performance of the conventional likelihood ratio test (LRT) detector with registration errors. Simulation results demonstrate that the detection performance of the two proposed detectors outperform the conventional LRT detector in the imperfect registration case.
机译:在本文中,我们考虑了具有配准误差的分布式多输入多输出雷达中的目标检测问题。配准误差是指将来自不同分布式雷达的观测数据转换为公共坐标系时的对准误差。我们的研究是基于这样的事实,即即使在注册过程之后,在实践中也无法获得完美的注册条件。引入了用于不完美配准的模型,其中采用了一个不确定窗口,该窗口以每个空间分集通道中沿距离和方位角为中心的被测单元为中心。基于不确定性窗口,开发了广义似然比检验(GLRT)检测器和贝叶斯似然比检验检测器。推导了所提出的GLRT检测器误报的可能性。为了便于比较,我们还分析了带有配准误差的常规似然比测试(LRT)检测器的检测性能。仿真结果表明,在不完善的配准情况下,两个提出的检测器的检测性能均优于传统的LRT检测器。

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