现代雷达2012，Vol.34Issue(7)：44-50,58,8.
改进高斯混合粒子滤波被动目标跟踪算法
Passive Target Tracking Algorithm Based on Improved Gaussian Mixture Particle Filter
孔云波 1冯新喜 1鹿传国1
作者信息
- 1. 空军工程大学电讯工程学院, 西安710077
- 折叠
摘要
Abstract
An improved Gaussian mixture particle filter algorithm was proposed for the highly non-linear passive tracking system,the limited Gaussian mixture model was used to approximate the posterior density of states,system noise and measurement noise in the algorithm,which based on the characteristics of SPKF and particle filter.Then the genetic based EM algorithm was used to obtain the reduction of model order,which overcooked the disadvantage of the standard EM algorithm that assumed the number of the mixture components is a known priori,the performance of the overall parameter estimation process depends on the given good initial settings,and the estimated parameter can be resulted from some local optimum points.The effects caused by sampling depletion were lessened.Simulation results show that the algorithm outperforms the one based on PF,the one based on EM-GMPF and the one based on GEM-GMPF in tracking accuracy,and stability.Therefore it is more suitable to the nonlinear state estimation.关键词
被动传感器/遗传EM算法/粒子滤波/混合高斯模型/模型降阶/纯方位跟踪Key words
passive sensor/genetic based EM algorithm/particle filter/Gaussian mixture modeling/model order reduction/bearing-only tracking分类
信息技术与安全科学引用本文复制引用
孔云波,冯新喜,鹿传国..改进高斯混合粒子滤波被动目标跟踪算法[J].现代雷达,2012,34(7):44-50,58,8.
