自动化学报Issue(4)：785-798,14.DOI:10.16383/j.aas.2015.c140222
基于箱式粒子滤波的群目标跟踪算法
Group Targets Tracking Algorithm Based on Box Particle Filter
摘要
Abstract
Particle filter (PF) algorithm is often used to solve the nonlinear filtering problem for point measurements in the existing group targets tracking algorithms. However, the traditional PF algorithm cannot be directly applied to the case where the point measurements should be converted to interval measurements when the measurements are affected by biases or bounds errors of unknown distributions. Therefore, this work presents an improved PF algorithm based on the generalized likelihood (GL) weighting method. The GL-PF algorithm uses the definite integral solution of generalized likelihood function to calculate the weighting of particles under interval measurements. For the sake of reducing computational burden, this work presents another group tracking algorithm based on box particle filter (Box-PF). Firstly, the rectangular box particles are sampled in the target state space. Then, the ratio between the contracted and the predicted box particle volumes is used to calculate the weighting of particles based on the interval analysis and constraints propagation method. Lastly, the group structure is estimated based on the estimation results of group target state and the evolving network model. Computer simulations show that compared with the GL-PF algorithm, the Box-PF algorithm can achieve a greater computational efficiency and reduce the peak error of the estimation results.关键词
群目标/跟踪/箱式粒子滤波/广义似然函数/演化网络模型/区间分析/峰值误差Key words
Group targets/tracking/box particle filter (Box-PF)/generalized likelihood (GL) function/evolving network model/interval analysis/peak error引用本文复制引用
李振兴,刘进忙,李松,白东颖,倪鹏..基于箱式粒子滤波的群目标跟踪算法[J].自动化学报,2015,(4):785-798,14.基金项目
Manuscript received April 3,2014 （）
accepted October 27,2014国家自然科学基金青年基金(61102109),航空科学基金项目(20120196003),空军工程大学防空反导学院“研究生科技创新基金”项目(HX1112)资助Supported by National Natural Science Foundation of Youth Fund of China (61102109), Aviation Science Foundation Project (20120196003), and Postgraduate Scientific Innovation Founda-tion Project of Air and Missile Defense College, Air Force Engi-neering University (HX1112) （61102109）
