第33卷第12期 系统工程与电子技术 V01．33 No．12

2011年12月 Systems Engineering and Electronics ‘December 2011

文章编号：i001—506X(2011)12—2696—04

基于新息协方差的自适应渐消卡尔曼滤波器

徐定杰，贺 瑞，沈锋，盖 猛

(哈尔滨_T-程大学自动化学院，黑龙江哈尔滨150001)

摘要：自适应渐消卡尔曼滤波采用渐消因子抑制滤波器的记忆长度，当系统模型和噪声模型建立不准确时，

能够有效地抑制滤波器的发散。但是现有计算渐消因子的方法公式表达复杂，计算过程繁琐，不利于组合导航等

一些实时的应用。针对这种情况，提出了一种利用新息协方差计算渐消因子的方法，通过渐消因子自适应地调整

误差协方差，补偿不完整信息的影响。该方法计算量小，提高了滤波算法的可靠性。最后，仿真结果证明了该方

法的有效性。

关键词：卡尔曼滤波；渐消因子；新息协方差}自适应算法

中图分类号：TP 273 文献标志码：A DOI：10．3969／j．issn．1001—506X．2011．12．23

Adaptive fading Kalman filter based on innovation covariance

XU Ding-jie，HE Rui，SHEN Feng，GAI Meng

(College of Automation，Har颤n Engineering University，Harbin 1 50001，China)

Abstract：The adaptive fading Kalman filter adopts a fading factor to restrain the Inemory length of the

Kalman filter．which can effectively restrain divergence of filtering when the system model and noise model are

established inaccurately．But the existing formulas of calculating fading factors are complex，and the solving

process is complicated。which is unfavourable for integrated navigation and some real time applications．In order

to solve this problem．a new method of calculating fading factors based on innovation covariance is presented，

which compensates the effect of inaccuracy information by rescaling of the error covariance through the fading

factor．The proposed method has the little computation burden and improves the reliability of the filter

arithmetic．Finally，the simulation results show the effectiveness of the new method．

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