In this paper, we consider a distributed passive radar with non-cooperative illuminators of opportunity (IOs) operating on non-overlapping frequency bands and tackle the problem of direct target localization. Assuming that each passive radar receiver employs reference channels to measure the direct-path signals from the IOs and a surveillance channel to collect the target echoes corrupted by the direct-path interference (DPI), we derive the maximum likelihood estimator of the target position through the joint estimation of unknown parameters. This estimator reveals the masking effect of DPI on the target echoes and achieves joint DPI suppression and target position estimation. To reduce the large computational complexity of this estimator caused by a lack of knowledge of the IO signals, a suboptimal estimator is then devised by separately processing the observations from the reference and surveillance channels to sequentially estimate the unknown parameters. As a benchmark, we also derive the corresponding Cramér-Rao Lower Bound (CRLB) on the estimation error of the target position. Finally, an extensive numerical analysis is provided to assess the performance of the proposed suboptimal estimator in single- and multi-target scenarios, also in comparison with other estimators that ignore the DPI at the design stage and/or assume prior knowledge of the IO signals. Remarkably, the proposed estimator is robust against the DPI and can provide a localization accuracy close to the CRLB in practical operating conditions.

中文翻译：

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具有直接路径干扰抑制功能的分布式无源雷达的直接目标定位


在本文中，我们考虑了一种分布式无源雷达，其具有在非重叠频段上运行的非合作机会照明器（IO），并解决了直接目标定位问题。假设每个无源雷达接收器使用参考通道来测量来自 IO 的直接路径信号，并使用监视通道来收集被直接路径干扰 (DPI) 破坏的目标回波，我们通过以下方式推导目标位置的最大似然估计：未知参数的联合估计。该估计器揭示了DPI对目标回波的掩蔽效应，实现了DPI抑制和目标位置的联合估计。为了减少由于缺乏 IO 信号知识而导致的估计器的巨大计算复杂性，通过分别处理来自参考通道和监视通道的观测值来设计次优估计器，以顺序估计未知参数。作为基准，我们还推导了目标位置估计误差相应的 Cramér-Rao Lower Bound (CRLB)。最后，提供了广泛的数值分析，以评估所提出的次优估计器在单目标和多目标场景中的性能，并与在设计阶段忽略 DPI 和/或假设 IO 信号先验知识的其他估计器进行比较。值得注意的是，所提出的估计器对于 DPI 具有鲁棒性，并且可以在实际操作条件下提供接近 CRLB 的定位精度。