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《Agricultural Equipment & Vehicle Engineering》 2018-12
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Research on Data Association Algorithm Based on Vehicle Tracking

Wang Jian;Cao Congcong;School of Automobile and Traffic Engineering, Hefei University of Technology;  
For tracking of road vehicle targets, due to its high maneuverability and clutter-intensive characteristics, interactive multi-model joint probability data association is a good tracking algorithm. However, its inherent disadvantage is that as the number of objects increases, its computational complexity will increase rapidly, and its fewer motion models will not be able to guarantee the tracking accuracy, while increasing the number of models will cause competition among the models. Therefore, an improved Variable Structure Multi-Model Joint Data Association Algorithm(VSMM-JPDA) is put forward. The theoretical analysis and comparison simulation show that the proposed algorithm has better tracking accuracy than the fixed structure and multi-model algorithm under non-motoring, maneuvering and linear maneuvering conditions, and the computational cost is greatly reduced.
【CateGory Index】: TP311.13
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