基于多重渐消因子的自适应卡尔曼滤波器

系统工程与电子技术

基于多重渐消因子的自适应卡尔曼滤波器

高伟，李敬春，奔粤阳，杨晓龙

（哈尔滨工程大学自动化学院，黑龙江哈尔滨 150001）

出版日期:2014-07-22 发布日期:2010-01-03

Adaptive Kalman filter based on multiple fading factors

GAO Wei, LI Jingchun, BEN Yueyang, YANG Xiaolong

(College of Automation, Harbin Engineering University, Harbin 150001, China)

Online:2014-07-22 Published:2010-01-03

摘要/Abstract

摘要：

现有计算渐消因子的自适应卡尔曼滤波器得到的通常是标量渐消因子，从而导致各滤波通道具有相同的调节能力，不利于提高滤波精度。针对〖JP3〗该问题，提出了一种利用估计均方误差和新息协方差估计值来计算多重渐消因子的方法，通过一组并行工作的基于限定记忆指数加权的新息协方差估值器来计算渐消因子，并根据估计均方误差把渐消因子分配给各滤波通道，从而提高自适应卡尔曼滤波器整体性能，仿真结果证明了所提方法的有效性。

Abstract:

A scalar fading factor is calculated in the existing adaptive fading Kalman filter and each filtering channel just gets the same adjustments, which is unfavorable for improving the filtering accuracy. Aimed at this issue, a new method based on the estimate covariance and the innovation covariance estimator is proposed. A set of innovation covariance estimators based on the limited memory index weighted method works in parallel to calculate the fading factors and then the factors are distributed to each filtering channel according to the estimate covariance to improve the performance of the adaptive Kalman filter. Simulation results show the effectiveness of the proposed method.

高伟，李敬春，奔粤阳，杨晓龙. 基于多重渐消因子的自适应卡尔曼滤波器[J]. 系统工程与电子技术.

GAO Wei, LI Jingchun, BEN Yueyang, YANG Xiaolong. Adaptive Kalman filter based on multiple fading factors[J]. Systems Engineering and Electronics.