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Gaussian mixture PHD filter for multi-target tracking using passive Doppler-only measurements

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3 Author(s)
Mehmet B. Guldogan ; Division of Automatic Control, Department of Electrical Engineering, Linköping University, Sweden ; Umut Orguner ; Fredrik Gustafsson

In this paper, we analyze the performance of the Gaussian mixture probability hypothesis density (GM-PHD) filter in tracking multiple non-cooperative targets using a passive sensor network. Non-cooperative transmissions from illuminators of opportunity like GSM base stations, FM radio transmitters or digital broadcasters are exploited by non-directional separately located Doppler measuring sensors. Clutter, missed detections and multi-static Doppler variances are incorporated into a realistic multi-target scenario. Simulation results show that the GM-PHD filter success fully tracks multiple targets using only Doppler shift measurements in a passive multi-static scenario.

Published in:

Data Fusion & Target Tracking Conference (DF&TT 2012): Algorithms & Applications, 9th IET

Date of Conference:

16-17 May 2012