基于数据质量评估的自适应序贯航迹关联算法

In order to solve the track-association problem when sensor suffers declined accuracy, an adaptive sequential track-association algorithm based on data quality assessment is proposed. Real-time data quality evaluation results are introduced into the adjustment of correlation threshold. The entropy method and the utility function method are combined to evaluate the performance of sensor and the quality of filtering, and the fuzzy control relationship between two indexes and the significance level is constructed, so as to realize the adaptive adjustment of correlation threshold. The simulation results show that the performance of the improved algorithm is better than that of compared algorithm in the situation of declined sensor accuracy, and the good correlation effect is beneficial to the improvement of fusion accuracy. It also has good adaptability in the case of maneuver target tracking.