摘要
针对非线性非Gaussian系统的状态估计问题,提出一种基于信息融合的多传感器分布式粒子滤波算法。该算法首先利用粒子滤波方法分别计算局部传感器的状态估值,再应用分布式标量加权融合准则对状态估值进行信息融合。仿真结果表明和单传感器情形相比可提高滤波的精度。
A new multi-sensor distributed particle filter based on information fusion is proposed for state estimation problem of nonlinear and non-Gaussian systems.It uses particle filter to calculate state estimated values of local sensors respectively,and then the system fusion estimation is obtained by applying the distributed fusion rule weighted by scales.The simulation results show that compared with the single sensor,the proposed algorithm improves the accuracy of filter.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第12期118-119,共2页
Computer Engineering and Applications
基金
国家自然科学基金No.60874063
黑龙江大学自动控制重点实验室项目~~
关键词
信息融合
粒子滤波器
状态估计
information fusion
particle filter
state estimation
