基于QS-ML-PMHT的多目标无源协同定位方法

针对目标个数未知时无源协同定位系统低可观测目标的航迹起始及维持问题，提出一种基于拟蒙特卡罗模拟退火极大似然概率多假设的双基站多目标无源协同定位方法。首先，建立双基站无源协同定位系统数学模型。其次，提出基于极大似然概率多假设的多目标无源协同定位航迹起始算法，通过假设法确定目标个数，并首次利用拟蒙特卡罗模拟退火算法解决极大似然概率多假设中多目标的优化求解问题，以提高多目标检测跟踪性能。最后，通过滑窗法实现航迹维持。仿真结果表明，所提方法能够有效解决目标个数未知时双基站无源协同定位系统低可观测目标的航迹起始及维持问题。

A QS-ML-PMHT Based Multitarget Passive Coherent Location Method

In order to track very low observable targets with a bistatic passive coherent location system ,where the number of targets is unknown,a quasi-Monte Carlo simulated annealing maximum likelihood probabilistic multi-hy?pothesis algorithm is proposed. The contributions consist of three aspects. First,the mathematical model for target detection and tracking is established. Second,a maximum likelihood probabilistic multi-hypothesis method is pre?sented for multitarget track initialization and determining the number of targets. In addition,the quasi-Monte Carlo simulated annealing algorithm is used for optimization and hence improving the estimation performance. Last,the track maintenance is achieved in a sliding window manner. Simulation results show the effectiveness of the pro?posed algorithm.