[1]刘锡祥,徐晓苏,冯爱国.有限记忆量测噪声在线估计的Kalman改进算法[J].东南大学学报(自然科学版),2010,40(4):766-770.[doi:10.3969/j.issn.1001-0505.2010.04.020]
　Liu Xixiang,Xu Xiaosu,Feng Aiguo.Improved algorithm for limited memory on-line estimating Kalman filter[J].Journal of Southeast University (Natural Science Edition),2010,40(4):766-770.[doi:10.3969/j.issn.1001-0505.2010.04.020]
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有限记忆量测噪声在线估计的Kalman改进算法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
40
期数:
2010年第4期
页码:
766-770
栏目:
仪器科学与技术
出版日期:
2010-07-20

文章信息/Info

Title:
Improved algorithm for limited memory on-line estimating Kalman filter
作者:
刘锡祥1;  徐晓苏1;  冯爱国2
1 东南大学仪器科学与工程学院, 南京 210096; 2 南通航运职业技术学院航海系, 南通 226061
Author(s):
Liu Xixiang1;  Xu Xiaosu1;  Feng Aiguo2
1 School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
2 Department of Navigation, Nantong Shipping College, Nantong 226061, China
关键词:
新息残差;  新息变化率;  量测噪声;  有限记忆滤波器;  Kalman滤波器
Keywords:
innovation residual sequence;  innovation changing rate;  measurement noise;  limited memory filter;  Kalman filter
分类号:
U666.1
DOI:
10.3969/j.issn.1001-0505.2010.04.020
摘要:
针对有限记忆量测噪声在线估计算法中,新息残差序列对渐变噪声的统计滞后问题,提出了一种新息变化率构建算法.该算法利用当前统计周期内新息绝对值的均值与前一统计周期内新息均值的绝对值构造新息变化率,并在此基础上提出了利用新息变化率作为量测噪声估计阵修正因子的改进算法.仿真比较了在无噪声变化、噪声突变与噪声渐变3种不同情况下,算法改进前后的滤波效果.仿真结果表明,该算法在保留对突变噪声有效检测的同时,提高了对渐变噪声的检测速度,从而提高了有限记忆量测噪声在线估计算法对量测噪声阵的计算精度.
Abstract:
For the lag of innovation residual sequence to gradually changing noise in the limited memory filter, a changing rate construction algorithm is proposed, in which the mean of absolute innovation value in the current statistical period and the absolute mean of innovation value in the last statistical period are used to construct the innovation changing rate. An improved algorithm is presented in which the innovation changing rate is used to correct the estimated matrix of measurement noise. The filter results before and after the algorithm improvement are compared in three different conditions: no noise changing, abrupt noise changing and gradual noise changing. And the simulation results show that with the algorithm proposed the reaction rate to gradual changing noise is increased.

参考文献/References:

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备注/Memo

备注/Memo:
作者简介: 刘锡祥(1976—),男,博士,副教授,scliuseu@163.com.
基金项目: 国家自然科学基金资助项目(60874092,50575042)、总装预研基金资助项目(51309060402,51309020503)、船舶基金资助项目(09J3.8.1).
引文格式: 刘锡祥,徐晓苏,冯爱国.有限记忆量测噪声在线估计的Kalman改进算法[J].东南大学学报:自然科学版,2010,40(4):766-770. [doi:10.3969/j.issn.1001-0505.2010.04.020]
更新日期/Last Update: 2010-07-20