基于新的采样更新方法的粒子滤波算法  

Particle filter algorithm based on a new sampling method

作　　者：王健[1] 金永镐[2] 董华春[1] 权太范[1] 

机构地区：[1]哈尔滨工业大学电子工程技术研究所338信箱,黑龙江哈尔滨150001 [2]延边大学电子信息工程系,吉林延边133002

出　　处：《系统工程与电子技术》2008年第6期1148-1150,共3页Systems Engineering and Electronics

基　　金：国家自然科学基金资助课题(60572038)

摘　　要：以往的粒子滤波采用由初始先验概率密度产生一组粒子,然后通过重要性密度函数去更新粒子,但会产生粒子退化的问题,因此引入了各种各样的重采样算法,但这样做又产生了粒子多样性丧失的问题。针对粒子滤波的粒子退化现象,提出基于新的采样更新方法的粒子滤波算法,新方法从滤波值和滤波误差协方差矩阵上产生粒子。仿真试验表明,新方法在非线性非高斯情况下要远远好于EKF。Former particle filters sample a set of particles generated from me initial probability density function and update them through the importance density function, which result in particle degeneracy. Thus various resample algorithms are introduced while these cause the loss of particle diversification. Aiming at the particle degeneracy problem, a different particle filter with a new sample method is proposed, and the particles are sampled based on the filtering results and filtering error covariance matrix. Simulations show that the new filter is far better than EKF in nonlinear and non-Gaussian systems.

关 键 词：粒子滤波 粒子匮乏 粒子采样方法 

分 类 号：TN953[电子电信—信号与信息处理]