自适应UKF算法在GNSS/INS深组合系统中的应用
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摘要
针对强非线性和时变噪声统计特性不明的高动态运动环境下全球卫星导航系统/惯导系统(GNSS/INS)深组合导航系统滤波精确度较差甚至发散的问题,提出一种自适应混合无迹卡尔曼滤波(UKF)算法。该算法以UKF算法为基础,采用混合滤波思想对UKF滤波算法进行简化;并根据高动态下系统量测噪声时变,且易快变、突变的特点,设计了一种基于渐消记忆指数加权的自适应量测噪声估计器,实时估计和修正噪声统计量并自适应调节估计周期。仿真结果表明,在量测噪声变化的情况下,相比于常规UKF算法,本文算法各向定位测速精确度均有所提升,水平方向精确度提升60%以上,效果明显;此外,算法耗时减少18.64%,说明本文算法能够在提升滤波精确度的同时减少部分计算量。
Aiming at the problem that the filtering accuracy is poor or even divergent in deep integrated Global Navigation Satellite System/Inertial Navigation System(GNSS/INS) in high dynamic motion environment with strong nonlinearity and inaccurate time-varying noise statistics, an adaptive hybrid filtering algorithm is proposed. In the proposed algorithm, the hybrid filtering idea is adopted to simplify the Unscented Kalman Filter(UKF) algorithm. According to the high dynamic system measurement noise time change, especially easy to change quickly and abrupt, an adaptive measurement noise estimator based on fading memory exponent is designed. It estimates and corrects the statistical characteristics in real time, and adaptively regulates the estimation cycle. The simulation results show that,in the case of variation of measurement noise, the accuracy of the algorithm is raised in comparison with the conventional UKF algorithm. The improvement effect of horizontal direction precision is obvious,which is more than 60%. In addition, the time consumption is reduced by 18.64% compared to the conventional UKF algorithm.
Aiming at the problem that the filtering accuracy is poor or even divergent in deep integrated Global Navigation Satellite System/Inertial Navigation System(GNSS/INS) in high dynamic motion environment with strong nonlinearity and inaccurate time-varying noise statistics, an adaptive hybrid filtering algorithm is proposed. In the proposed algorithm, the hybrid filtering idea is adopted to simplify the Unscented Kalman Filter(UKF) algorithm. According to the high dynamic system measurement noise time change, especially easy to change quickly and abrupt, an adaptive measurement noise estimator based on fading memory exponent is designed. It estimates and corrects the statistical characteristics in real time, and adaptively regulates the estimation cycle. The simulation results show that,in the case of variation of measurement noise, the accuracy of the algorithm is raised in comparison with the conventional UKF algorithm. The improvement effect of horizontal direction precision is obvious,which is more than 60%. In addition, the time consumption is reduced by 18.64% compared to the conventional UKF algorithm.
引文
[1]杨洋,薛晓中.简化的混合估计算法及其在GPS/SINS深组合中的应用[J].南京航天航空大学学报, 2012,44(3):360-365.(YANG Yang,XUE Xiaozhong. Hybrid estimation algorithm based on simplified UKF for ultra tight coupling GPS/SINS system[J]. Journal of Nanjing University of Aeronautics&Astronautics, 2012,44(3):360-365.)
[2]DONALD G,JOHN D,KARL F. A deeply integrated adaptive GPS-based navigator with extended range code tracking[C]//Position Location and Navigation Symposium. San Diego,California:[s.n.], 2000:118-124.
[3]YU Jie,WANG Xinlong,JI Jiaxing. Design and analysis for an innovative scheme of SINS/GPS ultra-tight integration[J].Aricraft Engineering and Aerospace Technology, 2010,82(1):4-14.
[4]陈剑,孙金海,李金海,等. GPS/INS组合导航系统中一种改进的UKF算法[C]//中国卫星导航学术年会.广州,中国:[s.n.], 2012:142-146.(CHEN Jian,SUN Jinhai,LI Jinhai,et al. An improved UKF in tightly-coupled GPS/INS system[C]//China Satellite Navigation Conference. Guangzhou,China:[s.n.], 2012:142-146.)
[5]GAUTIER J D,PARKINSON B W,GEBRE-EGZIABHER D. Using the GPS/INS Generalized Evaluation Tool(GIGET)for the comparison of loosely coupled,tightly coupled and ultra-tightly coupled integrated navigation systems[C]//Proceedings of ION 59th Annual Meeting and CIGTF 22nd Guidance Test Symposium. Manassas:[s.n.], 2003:65-76.
[6]DI Li,WANG Jinling. System design and performance analysis of extended Kalman filter-based ultra-tight GPS/INS integration[J]. Position,Location&Navigation Symposium. San Diego,California:IEEE, 2006:291-299.
[7]BABU S R,WANG J L. Ultra-tight GPS/INS/PL integration:a system concept and performance analysis[J]. GPS Solution,2009,13(1):75-82.
[8]李子月.高动态下GPS/SINS超紧组合导航系统研究[D].杭州:浙江大学, 2015.(LI Ziyue. The research of ultra-tightly coupled GPS/SINS integration system in high dynamic conditions[D]. Hangzhou,China:Zhejiang University, 2015.)
[9]丰泽斌. GPS/SINS超紧耦合组合导航系统的信息融合算法研究[D].杭州:浙江大学, 2015.(FENG Zebin. Research on the information fusion algorithm of ultra-tightly coupled integrated GPS/INS navigation system[D]. Hangzhou,China:Zhejiang University, 2015.)
[10]单童.深组合系统中惯性辅助GPS基带技术研究[D].南京:南京理工大学, 2014.(SHAN Tong. Research on inertial assisted GPS baseband technology in deep integrated system[D]. Nanjing,China:Nanjing University of Science and Technology, 2014.)
[11]罗勇. GNSS/INS深组合导航系统信息匹配问题与跟踪算法研究[D].长沙:国防科学技术大学, 2012.(LUO Yong.Research on the information matching problem and tracking algorithm in GNSS/INS deeply integrated navigation system[D].Changsha,China:National University of Defense Technology, 2012.)
[12]GEBRE-EGZIABHER D. What is the difference between ‘loose’,‘tight’,‘ultra-tight’,and ‘deep’ integration strategies for INS and GNSS[J]. Inside GNSS, 2007,2(1):28-33.
[13]杨洋,薛晓中.遗传散发辅助下的粒子滤波及其在GPS/SINS深组合中的应用[J].解放军理工大学学报(自然科学版), 2011,12(4):322-327.(YANG Yang,XUE Xiaozhong. Application of GA-aided particle filter in tight coupling GPS/SINS system[J]. Journal of PLA University of Science and Technology(Natural Science Edition), 2011,12(4):322-327.)
[14]秦永元,张洪钺,汪叔华.卡尔曼滤波与组合导航原理[M].西安:西北工业大学出版社, 2012.(QIN Yongyuan,ZHANG Hongyue,WANG Shuhua. Kalman filter and integrated navigation theory[M]. Xi’an,China:Northwest Polytechnic University Press, 2012.)
[15]崔留争. MEMS-SINS/GPS组合导航关键技术研究[D].长春:中国科学院长春光学精密机械与物理研究所, 2014.(CUI Liuzheng. Research on the key technologies of MEMS-SINS/GPS integration navigation system[D]. Changchun,China:Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences, 2014.)
[2]DONALD G,JOHN D,KARL F. A deeply integrated adaptive GPS-based navigator with extended range code tracking[C]//Position Location and Navigation Symposium. San Diego,California:[s.n.], 2000:118-124.
[3]YU Jie,WANG Xinlong,JI Jiaxing. Design and analysis for an innovative scheme of SINS/GPS ultra-tight integration[J].Aricraft Engineering and Aerospace Technology, 2010,82(1):4-14.
[4]陈剑,孙金海,李金海,等. GPS/INS组合导航系统中一种改进的UKF算法[C]//中国卫星导航学术年会.广州,中国:[s.n.], 2012:142-146.(CHEN Jian,SUN Jinhai,LI Jinhai,et al. An improved UKF in tightly-coupled GPS/INS system[C]//China Satellite Navigation Conference. Guangzhou,China:[s.n.], 2012:142-146.)
[5]GAUTIER J D,PARKINSON B W,GEBRE-EGZIABHER D. Using the GPS/INS Generalized Evaluation Tool(GIGET)for the comparison of loosely coupled,tightly coupled and ultra-tightly coupled integrated navigation systems[C]//Proceedings of ION 59th Annual Meeting and CIGTF 22nd Guidance Test Symposium. Manassas:[s.n.], 2003:65-76.
[6]DI Li,WANG Jinling. System design and performance analysis of extended Kalman filter-based ultra-tight GPS/INS integration[J]. Position,Location&Navigation Symposium. San Diego,California:IEEE, 2006:291-299.
[7]BABU S R,WANG J L. Ultra-tight GPS/INS/PL integration:a system concept and performance analysis[J]. GPS Solution,2009,13(1):75-82.
[8]李子月.高动态下GPS/SINS超紧组合导航系统研究[D].杭州:浙江大学, 2015.(LI Ziyue. The research of ultra-tightly coupled GPS/SINS integration system in high dynamic conditions[D]. Hangzhou,China:Zhejiang University, 2015.)
[9]丰泽斌. GPS/SINS超紧耦合组合导航系统的信息融合算法研究[D].杭州:浙江大学, 2015.(FENG Zebin. Research on the information fusion algorithm of ultra-tightly coupled integrated GPS/INS navigation system[D]. Hangzhou,China:Zhejiang University, 2015.)
[10]单童.深组合系统中惯性辅助GPS基带技术研究[D].南京:南京理工大学, 2014.(SHAN Tong. Research on inertial assisted GPS baseband technology in deep integrated system[D]. Nanjing,China:Nanjing University of Science and Technology, 2014.)
[11]罗勇. GNSS/INS深组合导航系统信息匹配问题与跟踪算法研究[D].长沙:国防科学技术大学, 2012.(LUO Yong.Research on the information matching problem and tracking algorithm in GNSS/INS deeply integrated navigation system[D].Changsha,China:National University of Defense Technology, 2012.)
[12]GEBRE-EGZIABHER D. What is the difference between ‘loose’,‘tight’,‘ultra-tight’,and ‘deep’ integration strategies for INS and GNSS[J]. Inside GNSS, 2007,2(1):28-33.
[13]杨洋,薛晓中.遗传散发辅助下的粒子滤波及其在GPS/SINS深组合中的应用[J].解放军理工大学学报(自然科学版), 2011,12(4):322-327.(YANG Yang,XUE Xiaozhong. Application of GA-aided particle filter in tight coupling GPS/SINS system[J]. Journal of PLA University of Science and Technology(Natural Science Edition), 2011,12(4):322-327.)
[14]秦永元,张洪钺,汪叔华.卡尔曼滤波与组合导航原理[M].西安:西北工业大学出版社, 2012.(QIN Yongyuan,ZHANG Hongyue,WANG Shuhua. Kalman filter and integrated navigation theory[M]. Xi’an,China:Northwest Polytechnic University Press, 2012.)
[15]崔留争. MEMS-SINS/GPS组合导航关键技术研究[D].长春:中国科学院长春光学精密机械与物理研究所, 2014.(CUI Liuzheng. Research on the key technologies of MEMS-SINS/GPS integration navigation system[D]. Changchun,China:Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences, 2014.)