多目标跟踪中基于目标威胁度评估的传感器控制方法

Threat Assessment Based Sensor Control for Multi-target Tracking

该文基于随机有限集的多目标滤波器提出一种基于目标威胁度评估的传感器控制策略。首先,在部分可观测马尔科夫决策过程(POMDP)的理论框架下,给出基于信息论的传感器控制一般方法。其次,结合目标运动态势对影响目标威胁度的因素进行分析。然后,基于粒子多目标滤波器估计多目标状态,依据多目标运动态势的评估研究建立多目标威胁水平,并从多目标分布特性中深入分析并提取出当前时刻最大威胁度目标的分布特性。最后,利用Rényi散度作为传感器控制的评价指标,以最大威胁度目标的信息增益最大化为准则进行最终控制方案的求解。仿真实验验证了该方法的实用性和有效性。

This paper proposes a threat assessment based sensor control by using multi-target filter with random finite set. First, the general sensor control approach based on information theory is presented in the framework of Partially Observable Markov Decision Process （POMDP）. Meanwhile, combined with target movement situation, the factors that affect the target threat degree are analyzed. Then, the multi-target state is estimated based on the particle multi-target filter, the multi-target threat level is established according to the multi-target motion situation, and the maximum threat target distribution characteristic is analyzed and extracted from the multi-target distribution characteristic. Finally, the Renyi divergence is used as the evaluation index in sensor control, and the final control policy is solved with the maximum information gain as the criterion, The simulation results verify the feasibility and effectiveness of the proposed method.