摘要
针对卡尔曼及其扩展算法在滤波中噪声矩阵与实际偏差过大时出现滤波发散的情况,本文提出利用无偏有限冲击响应滤波器(UFIR)实现该背景下的状态估计。但将UFIR滤波器应用于GPS/INS组合系统存在2个问题:1)在线估计最佳滤波窗长的方法还有待改善;2)导航精度较低。本文设计了一种级联式滤波算法,主滤波器对UFIR滤波算法进行改进,设计在线估计窗口大小方法的同时,改进了现有的UFIR算法;从滤波器引入GPS的航向信息,设计一种自适应卡尔曼滤波以提高导航精度。通过仿真和实测对所提滤波算法进行了验证,实验结果表明该算法可以有效提高导航精度和系统的鲁棒性。
In view of the filtering divergence of the Kalman filter and its extended filter when the noise matrix in the filtering is too large to adapt to the actual deviation,the unbiased finite impulse response filter(UFIR)is proposed to realize the state estimation under these conditions.However,there are two problems in the application of UFIR filter to the GPS/INS-integrated system:one is that the method of estimating the optimal filter window length online needs to be improved;the other is that the navigation accuracy is relatively low.In this paper,a cascade filtering algorithm is designed.The main filter improves the UFIR filtering algorithm.The method estimates window size online while improving the existing UFIR algorithm.An adaptive Kalman filter is designed to improve the navigation accuracy by introducing GPS course information from the filter.The proposed filtering algorithm is verified by simulation and actual measurement.The experimental results show that the proposed algorithm can effectively improve the navigation accuracy and robustness of the system.
作者
王伟
丛宁
邬佳
WANG Wei;CONG Ning;WU Jia(College of Intelligent Science and Engineering, Harbin Engineering University, Harbin 150001, China)
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2021年第2期240-245,共6页
Journal of Harbin Engineering University
基金
国家自然科学基金项目(61571148,61871143).
关键词
组合导航
卡尔曼滤波器
无偏有限冲击响应滤波器
窗口滤波
级联滤波器
噪声统计特性
自适应滤波
批处理过程
integrated navigation
Kalman filter
unbiased finite impulse response filter
window filtering
cascaded filter
noise statistical characteristics
adaptive filtering
batch process
