多目标跟踪中自适应时间资源调度

为了提高雷达的工作效率,在改进交瓦多模型-概率数据关联(IMMPDA)跟踪算法的基础上,提出了基于灰色关联度和粒子群优化理论的自适应多目标跟踪的时间资源凋度(ATRS)算法.首先对每个跟踪目标设置不同的期望跟踪精度;然后以灰色关联度作为资源管理模型中的度冒函数和粒子群算法中的适应度甬数,来衡量各种情况下预测跟踪精度与期...

Adaptive Time Resource Scheduling for Multiple Target Tracking

In order to improve the efficiency of the radar, the interacting multiple models-probability data association (IMMPDA) is modified in foundation, and a novel adaptive time resource scheduling (ATRS) algorithm for multi-target tracking is proposed based on grey relational grade and particle swarm optimization. First, the IMMPDA algorithm of target tracking is improved. Then different tracking accuracy is configured according to different targets respectively. During the particle optimization for obtaining the best sampling period and dwell time, the grey relational grade between the desired and estimated tracking accuracies is supposed to be the measurement function in the resource management model and the fitness value in the optimization process. Finally, the algorithm selects the target with the utmost urgency of being tracked as the one that will be tracked. Experimental results show that the proposed ATRS algorithm not only has a better tracking accuracy, but also saves time resource for the phased-array radar.