摘要
针对北斗/捷联惯导系统(SINS)组合导航系统中存在的噪声信号导致系统状态估计精度降低以及波动较大的问题,提出一种基于平稳小波变换的改进Kalman滤波算法。该算法首先通过平稳小波变换对北斗信号数据进行降噪处理,以降低观测数据的误差波动;然后将标准Kalman滤波与H∞滤波结合以增强滤波结果的稳定性而形成改进Kalman滤波,并用改进Kalman滤波对SINS数据和已降噪处理的北斗数据进行信息融合来估算系统状态。实验研究表明,与Kalman滤波算法相比,基于平稳小波变换的改进Kalman滤波算法可以有效剔除噪声并降低误差波动,且解算精度提高20%~30%。
Aiming at the problems that the noise single of the Beidou/SINS integrated navigation system leads to the decrease of system state estimation accuracy and large fluctuation,an improved Kalman filtering algorithm based on stationary wavelet transform is proposed.The algorithm firstly denoises the Beidou signal data by stationary wavelet transform to reduce the error fluctuation of the observation data.Then,the improved Kalman filter is formed by combining standard Kalman filter with H∞filter to enhance the stability of the filter.The information fusion of SINS data and Beidou data processed by noise reduction is used to estimate the system state.Experimental results show that compared with Kalman filtering algorithm,the improved Kalman filtering algorithm based on stationary wavelet transform can effectively eliminate noise and reduce error fluctuation,and the solution accuracy is improved by 20%~30%.
作者
张国强
鲁昌华
李燕
章梦阳
Zhang Guoqiang;Lu Changhua;Li Yan;Zhang Mengyang(School of Computer Science and Information Engineering,Hefei University of Technology,Hefei 230601,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2019年第7期65-71,共7页
Journal of Electronic Measurement and Instrumentation
基金
合肥市北斗卫星导航重大应用示范(发改办高技(2014)2564)资助项目
作者简介
张国强,2015年于合肥师范学院获得学士学位,现为合肥工业大学硕士研究生,主要研究方向为信号检测与处理。E-mail:ahzhangguoqiang@163.com;通信作者:鲁昌华,1983年于合肥工业大学获学士学位,1988年于哈尔滨工程大学获硕士学位,2001年于中国科学院获博士学位,现为合肥工业大学教授,主要研究方向为智能信息处理等。E-mail:lch6208@163.com
