CAJ | 학술논문

针对标准标签多伯努利（labeled multi-Bernoulli，LMB）算法只考虑了单个运动模型的问题，提出了一种适用于跳转马尔科夫系统的多模型标签多伯努利（multiple model LMB，MM-LMB）算法。首先对目标状态进行扩展，将多模型思想引入 LMB 算法得到了新的预测和更新方程，并给出了算法的序贯蒙特卡罗实现。仿真实验表明，MM-LMB 算法能对多机动目标进行有效跟踪，在复杂探测环境下跟踪精度优于多模型概率假设密度（multiple model probability hypothesis density，MM-PHD）算法和多模型势平衡多目标多伯努利（multiple model cardinality balanced multi-target multi-Bernoulli，MM-CBMeMBer）算法；所提算法计算量当目标相距较远时低于MM-PHD 和 MM-CBMeMBer，目标聚集时增长速度快于对比算法。
침대표준표첨다백노리（labeled multi-Bernoulli，LMB）산법지고필료단개운동모형적문제，제출료일충괄용우도전마이과부계통적다모형표첨다백노리（multiple model LMB，MM-LMB）산법。수선대목표상태진행확전，장다모형사상인입 LMB 산법득도료신적예측화경신방정，병급출료산법적서관몽특잡라실현。방진실험표명，MM-LMB 산법능대다궤동목표진행유효근종，재복잡탐측배경하근종정도우우다모형개솔가설밀도（multiple model probability hypothesis density，MM-PHD）산법화다모형세평형다목표다백노리（multiple model cardinality balanced multi-target multi-Bernoulli，MM-CBMeMBer）산법；소제산법계산량당목표상거교원시저우MM-PHD 화 MM-CBMeMBer，목표취집시증장속도쾌우대비산법。
For the problem that the standard labeled multi-Bernoulli (LMB)filter only considers the single motion model case,a multiple model LMB (MM-LMB)filter for maneuvering target tracking is proposed.By introducing the jump Markov (JM)system to the LMB method,the extended recursion formulations are presen-ted,and the sequential Monte Carlo implementation of the proposed method is given.Simulations show that the MM-LMB filter can track multiple maneuvering targets effectively,and has higher tracking accuracy than the multiple model probability hypothesis density (MM-PHD)filter and the multiple model cardinality balanced multi-target multi-Bernoulli (MM-CBMeMBer)filter in complex detection environment.The calculation cost of the proposed method is lower than MM-PHD and MM-CBMeMBer when the targets are not closed,while grows faster than the compared algorithms when the targets gather together.