Target Tracking Algorithm of Automotive Radar Based on Iterated Square-root CKF

An iterated square-root cubature Kalman filter(ISRCKF) algorithm for target tracking of automotive radar is proposed in this paper, which inherits the fast and robust advantages of SRCKF, combines with Gauss-Newton iterative theory and design a algorithm to iterate update the measurement process. Th...

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Bibliographic Details
Published inJournal of physics. Conference series Vol. 976; no. 1; pp. 12010 - 12015
Main Authors Wang, Cai-ling, Xiong, Xing, Liu, Hua-jun
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.02.2018
Subjects
Accuracy
Algorithms
Automotive radar
Kalman filters
Physics
Radar targets
Radar tracking
Tracking
Tracking problem
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Summary:An iterated square-root cubature Kalman filter(ISRCKF) algorithm for target tracking of automotive radar is proposed in this paper, which inherits the fast and robust advantages of SRCKF, combines with Gauss-Newton iterative theory and design a algorithm to iterate update the measurement process. The filtering accuracy of target tracking algorithm of automotive radar can be further improved as the newest measurement is fully utilized. Monte-Carlo simulation experiments were carried out aim at the automotive radar target tracking problem, in which used the algorithm to compare with classical algorithms such as square-root unscented Kalman filter (SRUKF) and SRCKF. The experimental results shows that the overall filtering accuracy of this algorithm is much improved compare with other classical filtering algorithms, and the filtering accuracy can be improved with the increase of iteration number.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/976/1/012010