火力与指挥控制2016，Vol.41Issue(10)：134-137,4.
基于改进遗传粒子滤波与SME的多目标跟踪算法
Multi-target Tracking Algorithm Based on Advanced Genetic Particle Filter and Symmetric Measurement Equation
摘要
Abstract
To investigate the non-Gaussian problem caused by symmetry transformation while tracking multiple targets with symmetric measurement equation, which could not be solved by traditional filtering methods,an improved genetic particle filter is proposed. The advanced method uses the negative correlation between the noise component and the weight of particles to improve the probability density function upon which the weight calculation is dependent in the stage of update,and avoids the calculation of the new measurement noise. Meanwhile,genetic algorithm can help increase the use efficiency and diversity of particles as well as avoid the filter divergence and local optimization. Simulation was made,and it turned out that the filtering performance of advanced Genetic Particle Filter is better than Extended Kalman Filter,Unscented Kalman Filter and Joint Probability Data Association filter in multi-target tracking based on symmetric measurement equation.关键词
多目标跟踪/对称量测方程/遗传粒子滤波/非高斯/权值计算Key words
multi-target tracking/symmetric measurement equation/genetic particle filter/non-Gaussian/weight calculation分类
信息技术与安全科学引用本文复制引用
熊志刚,黄树彩,吴潇,苑智玮..基于改进遗传粒子滤波与SME的多目标跟踪算法[J].火力与指挥控制,2016,41(10):134-137,4.基金项目
陕西省自然科学基金资助项目 （）
