Target Tracking Using Kalman Filter Based Algorithms
2021 ◽
Vol 2078
(1)
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pp. 012020
Keyword(s):
Abstract Kalman filter and its families have played an important role in information gathering, such as target tracking. Data association techniques have also been developed to allow the Kalman filter to track multiple targets simultaneously. This paper revisits the principle and applications of the Kalman filter for single target tracking and multiple hypothesis tracking (MHT) for multiple target tracking. We present the brief review of the Bayes filter family and introduce a brief derivation of the Kalman filter and MHT. We show examples for both single and multiple targets tracking in simulation to illustrate the efficacy of Kalman filter-based algorithms in target tracking scenarios.
2014 ◽
Vol 496-500
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pp. 1564-1567
2017 ◽
Vol 27
(3)
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pp. 454-469
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2004 ◽
Vol 19
(1)
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pp. 5-18
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2016 ◽
Vol 31
(3)
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pp. 90-96
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2013 ◽
Vol 753-755
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pp. 2015-2019
Keyword(s):
2019 ◽
Vol 55
(6)
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pp. 3080-3089
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