一种基于多伯努利模型的被动多传感器多目标轨迹关联性能分析新方法

A Performance Analysis Method of Passive Multisensor Multitarget Track Association Based on MultiBernoulli Model

多目标轨迹关联算法的性能分析问题是天基光学被动测角跟踪系统中的核心和难点之一。该文针对具有代表性的基于最邻近准则的轨迹关联算法,提出了一种基于多伯努利模型的被动多传感器多目标轨迹关联性能分析新方法。首先,对关联倾角差统计量的概率分布进行准确建模。接着,分析最邻近轨迹关联算法在多目标情况下的等价条件,求解出每一个目标在多目标情况下的正确关联概率。最后,通过将每一个目标的正确关联概率类比为伯努利试验的成功率,从而将多目标情况下的整体关联性能问题建模为多伯努利问题,在此基础上实现对多目标轨迹关联性能的理论推导。密集目标场景下的Monte Carlo仿真结果验证了该理论分析方法的有效性,分析结论可以为传感器调度等工程应用提供参考。

The performance analysis of multiple tracks association is one of the key and difficult issues in the space-based optical passive angle tracking system.For the typical nearest nerghbor track association algorithm,this paper proposes a novel performance analysis method of passive multisensor multitarget track association based on multiple Bernoulli model.Firstly,the probability distribution of the association hinge angle difference statistic is modeled exactly.Secondly,the equivalent condition of the nearest neighbor track association algorithm in multiple targets situation is analyzed;the correct association probability of each target in multiple targets sitation is calculated.Finally,each correct association probability is treated as the succesful rate of a Bernoulli trial,and then the problem of the holistic association performance about all targets is modeled as the multiple Bernoulli process.On this basis,the association performance in multiple targets situation is derived theoreticly.A Monte Carlo simulation in dense targets scenario is used to analyze the performance analysis method,the efficiency of this performance analysis method is verified by the simulation results.It seems that some analysis results can provide references to engineering applications,such as multiple sensors management.