Multiple signal classification algorithm compensated by Extended Kalman Particle Filtering for Wi-Fi through wall multi-target tracking

In this work, a multiple-target tracking problem for a Wi-Fi through wall system is formulated and a new Direction Of Arrival (DOA) angle estimation technique is investigated to solve the tracking problem in the presence of clutter. The DOA estimation from objects behind walls is investigated utilizing the MUltiple SIgnal Classification (MUSIC) algorithm compensated by Extended Kalman Particle Filtering (EKPF) technique for the first time. Simulation results show that the stand-alone MUSIC algorithm fails to identify two distinct objects having close DOAs and fails to track targets when they are moving close to each other. The results also reveal that the EKPF algorithm in conjunction with MIMO nulling technique correctly identifies close and overshadowed moving objects and improves the tracking success rate.

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