A New Data Association Approach for Automotive Rader Tracking
نویسندگان
چکیده
Abstract: Correct data association between the measurements for the objects and the known tracks is an important content for vehicle tracking study, and is also the base for enhancing the precision of the state estimation for targets in road situation. Based on the evidence theory and fuzzy mathematics, a new data association method between the tracks and the measurements is proposed in the paper. The mass function is determined by using fuzzy mathematics, and a belief matrix is produced according to the evidence combination rule, then the decision is made by means of the maximum belief. The Monte Carlo simulation results indicate that the new method has a good association capacity. Compared with NN (nearest-neighbor) method and the cheap JPDAF method, the tracking accuracy has been improved.
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