Trust Region Based Sequential Quasi-Monte Carlo Filter

XU Li-zhong; DING Xiao-feng; WANG Xin; LV Guo-fang; HUANG Feng-chen

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Trust Region Based Sequential Quasi-Monte Carlo Filter

更新时间：2025-07-16

- Trust Region Based Sequential Quasi-Monte Carlo Filter
- Acta Electronica Sinica Vol. 39, Issue 3A, Pages: 24-30(2011)
- 作者机构：
  
  1. 河海大学计算机与信息学院,江苏,南京,210098
  2. 河海大学通信与信息系统研究所,江苏,南京,210098
  3. 河海大学计算机与信息学院江苏南京,210098
  4. 河海大学通信与信息系统研究所江苏南京,210098
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391
- Published：2011
- 稿件说明：
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XU Li-zhong, DING Xiao-feng, WANG Xin, et al. Trust Region Based Sequential Quasi-Monte Carlo Filter[J]. Acta Electronica Sinica, 2011, 39(3A): 24-30.
DOI：

XU Li-zhong, DING Xiao-feng, WANG Xin, et al. Trust Region Based Sequential Quasi-Monte Carlo Filter[J]. Acta Electronica Sinica, 2011, 39(3A): 24-30. DOI：

摘要

针对系统状态估计、目标跟踪等是包含多源不确定性信息的非线性非高斯随机过程

提出了一种基于信赖域的序贯拟蒙特卡洛(Sequential Quasi-Monte Carlo

SQMC)滤波算法.该算法利用拟蒙特卡洛积分技术优化采样粒子在状态空间的分布特性

降低了滤波过程中的积分误差

提高了状态估计精度;同时

利用信赖域(Trust Region

TR)方法将采样粒子向高似然区域移动

减少了所需采样粒子的数目

降低了算法复杂度.实验结果表明:该算法有效克服了粒子贫乏和拟蒙特卡洛滤波计算复杂度高的问题

且在非线性系统状态估计精度以及目标跟踪的准确性上要优于粒子滤波和拟蒙特卡洛滤波等现有算法.

Abstract

A trust region based sequential quasi-Monte Carlo filter is proposed for system state estimation and object tracking which are the non-linear and non-Gaussian random procedures with multi-source uncertain information.In the proposed algorithm

the quasi-Monte Carlo (QMC) technique is used to optimize the distribution of the sampling particles in the state space

which can obtain a small error of the integration in the filtering process and a better accuracy of the state estimation.Furthermore

a trust region (TR) procedure is used to move particles to regions of high likelihood

which results in a fewer particle selection and lower computational cost.Experimental results show that the proposed algorithm overcomes the particle impoverishment

reduces the computational complexity of the QMC filter

and gets a more accuracy estimation than existing algorithms such as particle filter and QMC filter in system state estimation and object tracking.

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