电讯技术2017，Vol.57Issue(4)：457-462,6.DOI:10.3969/j.issn.1001-893x.2017.04.015
一种简化的拟蒙特卡洛-高斯粒子滤波算法
A Simplified Quasi-Monte Carlo Based Gaussian Particle Filter
摘要
Abstract
A simplified Quasi-Monte Carlo Gaussian particle filtering(QMC-GPF)(SQMC-GPF) algorithm is presented to solve the problems of high complexity and large amount of computation that QMC method is faced with when it is applied to GPF.In this algorithm,a basic set of particles which obey unit quasi-Gaussian distribution are pregenerated with the method of QMC before the successive iterative filering process,and then they are converted to the particles needed during iterative filering by means of linear transformation,without the QMC method called again.This algorithm simplifies the generation of new particles,reduces the amount of computation and filtering time,and improves the real-time performance of the QMC-GPF algorithm.Finally,the PF,GPF,QMC-GPF and SQMC-GPF algorithms are simulated with univariate nonstationary growth model(UNGM) and bearing-only tracking model(BOT).Results show that,SQMC-GPF algorithm has much higher filtering speed than QMC-GPF algorithmon on the premise of the same filtering performance,which proves that the former has important practical application value.关键词
高斯粒子滤波/拟蒙特卡洛采样/线性变换/高斯分布Key words
Gaussian particle filter/quasi-Monte Carlo sampling/linear transformation/Gaussian distribution分类
信息技术与安全科学引用本文复制引用
高国栋,林明..一种简化的拟蒙特卡洛-高斯粒子滤波算法[J].电讯技术,2017,57(4):457-462,6.基金项目
国家自然科学基金资助项目(61401179) （61401179）
