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Erschienen in:
2012 | OriginalPaper | Buchkapitel
3. A Novel Fuzzy Data Association Algorithm with the Heading-Angle Aided
verfasst von : Pengfei Li, Tian Qin, Li Ren
Erschienen in: Electrical, Information Engineering and Mechatronics 2011
Verlag: Springer London
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Abstract
In this chapter, a new data association method based on fuzzy logic is proposed for the multi-target tracking. Firstly, the heading-angle and distance are analyzed to be the effective parameters for separating the multi-target, the definition of heading-angle and the method of how to calculate the heading-angle have been introduced, the state including the heading-angle is updated using the cubature Kalman filter, at last the fuzzy logic inference method is used for data association. Simulation results show that the proposed method have better performance in data association than the Nearest Neighbor (NN) algorithm and Joint Probability Data Association (JPDA) algorithm.