Robust LOS Identification for Passive Multi-Target Localization in Multipath Obstructed Environments

This paper considers passive target localization using multiple spatially distributed sensors, each transmitting distinct waveforms to measure line-of-sight (LOS) and non-line-of-sight (NLOS) delays from the passive targets. Since LOS and NLOS measurements are not directly distinguishable, the problem is to identify the LOS measurements when certain sensors are blocked from some targets—without prior knowledge of which sensors or targets are affected—and the total number of targets present in the scene is unknown a priori. Leveraging the fact that targets can be categorized into different levels according to the number of sensors obstructed from them, we propose a hierarchical type-based clustering algorithm (HiTCA), which employs a multi-level search strategy, with each designed to identify one specific level of targets. These searches can be performed in parallel across levels to efficiently identify targets with different extents of LOS blockage. Moreover, we exploit a spread difference among the multi-level search results, which enables us to obtain a reliable inference of the total target number. Extensive computer simulations show that the proposed technique obtains superior performance compared to existing methods in multi-target multipath environments with blockage.