Yu GongAbdullahi DaniyanAbdulrazaq AldoweshSangarapillai Lambotharan2025-04-252017-06-202017-05-012019-03-27DOI: 10.1109/RADAR.2017.7944168http://repository.futminna.edu.ng:4000/handle/123456789/984We investigate a game theoretic data association technique for multi-target tracking (MTT) with varying number of targets in a real passive bi-static radar (PBR) environment. The radar measurements were obtained through a PBR developed using National Instrument (NI) Universal Software Radio Peripheral (USRP). We considered the problem of associating target state-estimates-to-tracks for varying number of targets. We use the sequential Monte Carlo probability hypothesis density (SMC-PHD) filter to perform the multi-target tracking in order to obtain the target state estimates and model the interaction between target tracks as a game. Experimental results using this real radar data demonstrate effectiveness of the game theoretic data association for multiple target tracking.Game theorydata associationmulti-target trackingpassive bi-static radar PBRparticle filtersequential Monte Carlo (SMC)PHD filter.Other