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Posterior Cramer-Rao lower bounds for passive bistatic radar tracking with uncertain target measurements

机译:用于不确定目标测量的被动双基地雷达跟踪的后Cramer-Rao下界

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In the context of target tracking, the Posterior Cramer-Rao Lower Bound (PCRLB) provides a powerful tool to assess the optimal achievable accuracy of target state estimation. In the bistatic configuration both geometry factors and transmitted waveform play an important role in the estimation accuracy. In this paper, we derive the PCRLB on sequential target state estimation accuracy in a bistatic radar tracking scenario, in the most general case of uncertain target measurements, i.e. when the probability of detection is less than one and the probability of false alarm is greater than zero. Then, we propose a PCRLB-based algorithm for selecting the best transmitter of opportunity for the tracking of a radar target in a multisensor Passive Coherent Location (PCL) system.
机译:在目标跟踪的情况下,后克拉默罗下界(PCRLB)提供了强大的工具来评估目标状态估计的最佳可实现精度。在双基地配置中,几何因素和传输波形在估计精度中都起着重要作用。在本文中,我们得出了双基地雷达跟踪场景中顺序目标状态估计精度的PCRLB,在最常见的目标测量不确定性情况下,即当检测概率小于1且错误警报概率大于零。然后,我们提出了一种基于PCRLB的算法,用于在多传感器无源相干定位(PCL)系统中选择最佳的机会跟踪雷达目标。

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