Electrical & Electronics Engineering
Permanent URI for this collectionhttp://197.211.34.35:4000/handle/123456789/65
Electrical & Electronics Engineering
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Item Data association using game theory for multi-target tracking in passive bistatic radar(IEEE, 2017-06-20) Yu Gong; Abdullahi Daniyan; Abdulrazaq Aldowesh; Sangarapillai LambotharanWe 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.