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Tracking Multiple Targets from Multistatic Doppler Radar with Unknown Probability of Detection
by
Do, Cong-Thanh
, Van Nguyen, Hoa
in
Bayes recursion
/ bootstrapped detection probability
/ GLMB
/ labeled RFS
/ multistatic Doppler radar
/ multitarget tracking
/ unknown detection probability
2019
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Tracking Multiple Targets from Multistatic Doppler Radar with Unknown Probability of Detection
by
Do, Cong-Thanh
, Van Nguyen, Hoa
in
Bayes recursion
/ bootstrapped detection probability
/ GLMB
/ labeled RFS
/ multistatic Doppler radar
/ multitarget tracking
/ unknown detection probability
2019
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Tracking Multiple Targets from Multistatic Doppler Radar with Unknown Probability of Detection
Journal Article
Tracking Multiple Targets from Multistatic Doppler Radar with Unknown Probability of Detection
2019
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Overview
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.
Publisher
MDPI,MDPI AG
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