DocumentCode :
2577775
Title :
Optimal removal of out-of-sequence measurements from tracks using the IF-equivalent measurement
Author :
Zhang, Shuo ; Bar-Shalom, Yaakov
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Connecticut, Storrs, CT, USA
fYear :
2010
fDate :
15-17 Dec. 2010
Firstpage :
1312
Lastpage :
1317
Abstract :
In real-world tracking systems some earlier measurements that have been used to update a track might be reassigned to some other tracks and then there is a need to remove such measurements from that track under consideration. Recently, this problem of removal of measurements from multiple steps prior to the current time, was solved in one step by using an equivalent measurement. This one-step solution is shown to be optimal only when the system is deterministic, that is, the process noise is zero. However, in reality, most systems are non-deterministic and in this case, this one-step solution is unreliable due to its suboptimality unless the target maneuvering index is small (<;0.3). This paper presents the optimal solution to the problem of removing earlier measurements from tracks. The optimal removal is obtained using an Information Filter (IF) equivalent measurement. Comparisons are given to show the superiority of the proposed optimal solution. In particular, when the measurement to be removed is (nearly) an outlier, the optimal removal yields significantly better results than the one-step algorithm.
Keywords :
Kalman filters; target tracking; IF-equivalent measurement; information filter equivalent measurement; optimal removal; out-of-sequence measurements; Covariance matrix; Current measurement; Mathematical model; Noise; Noise measurement; Target tracking; Time measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location :
Atlanta, GA
ISSN :
0743-1546
Print_ISBN :
978-1-4244-7745-6
Type :
conf
DOI :
10.1109/CDC.2010.5717770
Filename :
5717770
Link To Document :
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