高斯过程回归下的多机动扩展目标跟踪

doi:10.3969/j.issn.1001-2400.2017.06.006

Abstract

Abstract:

In view of the complexity of estimating the shape of the extended target and the low accuracy in multiple maneuvering extended targets tracking in the clutters, a multiple maneuvering extended targets tracking algorithm with Gaussian Process Regression is proposed. First, the extension of targets is modeled as a star-convex model. Then, the concept of weights used in the multiple targets tracking algorithm is introduced to the single maneuvering extended target tracking algorithm to realize multi-targets tracking. Finally, the Gaussian Process Regression is used to estimate the shape for the extended target. Simulation shows that the proposed algorithm is capable of tracking multiple maneuvering extended targets in the same scene with different shapes, and outperforms the traditional non-ellipsoidal extended target tracking algorithm in the estimation precision and computing speed.

Key words: multiple maneuvering extended targets, star-convex models, Gaussian processes regression, shape estimation

LI Cuiyun;WANG Jingyi;JI Hongbing. Multiple maneuvering extended targets tracking with Gaussian process regression[J].Journal of Xidian University, 2017, 44(6): 31-36.

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Multiple maneuvering extended targets tracking with Gaussian process regression

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