基于改进自适应滤波的SINS/DVL组合导航算法研究

作者:魏延辉;刘静;郝晟功; 刊名:自动化与仪表 上传者:马帅

【摘要】针对水下长航时捷联惯性导航系统(SINS)与多普勒计程仪(DVL)组合定位精度问题进行研究,提出了一种改进的自适应滤波的方法。建立了SINS/DVL组合导航模型,通过对比经典Kalman滤波和Sage-Husa自适应滤波在SINS/DVL组合导航系统应用时存在的问题,利用失准时的新息对先验状态均方误差矩阵进行自适应调节,解决DVL数据突变后新息协方差严重偏离实际的问题。进行了约10 h仿真试验,结果表明:当DVL噪声突然增加到原来的10倍时,改进的自适应滤波算法相对于经典Kalman滤波提高了精度,且性能优于改进的Sage-Husa自适应滤波。

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自动化与仪表 2019,34(5) 基于改进自适应滤波的 SINS/DVL 组合导航算法研究 DOI:10.19557/j.cnki.1001-9944.2019.05.023 魏延辉,刘 静,郝晟功 (哈尔滨工程大学 自动化学院,哈尔滨 150001) 摘要:针对水下长航时捷联惯性导航系统(SINS)与多普勒计程仪(DVL)组合定位精度问题进行研究,提出了一种改进的自适应滤波的方法。 建立了SINS/DVL组合导航模型,通过对比经典Kalman滤波和Sage-Husa自适应滤波在SINS/DVL组合导航系统应用时存在的问题,利用失准时的新息对先验状态均方误差矩阵进行自适应调节,解决DVL数据突变后新息协方差严重偏离实际的问题。 进行了约10 h仿真试验,结果表明:当DVL噪声突然增加到原来的10倍时,改进的自适应滤波算法相对于经典Kalman滤波提高了精度,且性能优于改进的Sage-Husa自适应滤波。 关键词:组合导航;改进的自适应滤波算法;多普勒计程仪; χ2故障检测中图分类号:TP273 文献标志码:A 文章编号:1001-9944(2019)05-0095-06 SINS/DVL Integrated Navigation System Based on Improved Adaptive Filtering Algorithm WEI Yan-hui,LIU Jing,HAO Sheng-gong (College of Automation,Harbin Engineering University,Harbin 150001,China) Abstract:Aiming at the accuracy problem of the long-haul positioning of the strapdown inertial navigation system (SINS) and the doppler velocity log(DVL) combination navigation system,an improved adaptive filtering method is proposed. The SINS/DVL integrated navigation model is established. By comparing the problems of classical Kalman filtering and Sage-Husa adaptive filtering in the application of SINS/DVL integrated navigation system,the prior-squared mean square error matrix is self-utilized by using the new information at the time of misalignment. Adaptation adjustment solves the problem that the new interest covariance seriously deviates from the actual situation after the DVL data mutation. The simulation experiment was carried out for about 10 hours. The results show that the improved adaptiv

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