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Tracking Multiple Targets from Multistatic Doppler Radar with Unknown Probability of Detection
Cong-Thanh Do1, Hoa Van Nguyen2
1School of Electrical Engineering, Computing, and Mathematical Sciences, Curtin University, Bentley, WA 6102, Australia 2 School of Computer Science, The University of Adelaide, Adelaide, SA 5005, Australia. thanh.docong@student.curtin.edu.au.
Abstract:
The measurements from multistatic radar systems are typically subjected to complicated data association, noise corruption, missed detection, and false alarms. Moreover, most of the current multistatic Doppler radar-based approaches in multitarget tracking are based on the assumption of known detection probability. This assumption can lead to biased or even complete corruption of estimation results. This paper proposes a method for tracking multiple targets from multistatic Doppler radar with unknown detection probability. A closed form labeled multitarget Bayes filter was used to track unknown and time-varying targets with unknown probability of detection in the presence of clutter, misdetection, and association uncertainty. The efficiency of the proposed algorithm was illustrated via numerical simulation examples.
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