基于QMC-IPF-JPDA的多目标无源协同定位算法

Multiple Target Passive Coherent Location Algorithm Based on QMC-IPF-JPDA

针对杂波环境中多目标的检测跟踪问题,提出一种基于拟蒙特卡罗智能粒子滤波联合概率数据关联的无源协同定位算法。该算法建立双基站无源协同定位系统目标检测跟踪的数学模型。通过拟蒙特卡罗技术使粒子分布更加均匀,并对更新阶段的粒子进行交叉变异以提高粒子多样性。结合测量信息,利用联合概率数据关联算法实现多目标检测跟踪。仿真结果表明,所提算法能有效解决杂波环境下多目标检测跟踪问题,提高跟踪性能。

For the problem of detecting and tracking multiple target in heavy clutter with a bistatic passive coherent location radar, a quasi Monte Carlo intelligent particle filter joint probabilistic data association algorithm is proposed. First,the mathematical model of bistatic radarfor targets detection and tracking is established. Second,the quasi Monte Carlo technique is used toimprove the distribution of particles,the crossover and mutation operations are invoked to improve the particle diversity at the update stage. Last,the joint probabilistic data association algorithm based on measurement is used to track multiple target. Simulation results verify the proposed algorithm can solve the problem of tracking multiple target and improve the tracking performance effectively.