MIMU/GNSS紧组合精密单点定位协方差成形自适应滤波方法
|
摘要
针对精密单点定位应用需求,研究了MIMU/GNSS紧组合协方差成形自适应滤波方法。给出了"位臵滤波器+速度滤波器"的分布式滤波器设计方案以降低计算复杂度;推导了地理系紧组合导航系统模型,并把伪距测量不一致性偏差扩展至系统状态向量中予以估计,从而提高系统对于动态环境下伪距测量偏差抖动的适应能力。协方差成形自适应滤波算法利用Frobenius范数来衡量系统残差噪声水平建模状态与实际状态的匹配程度,并以最小化Frobenius范数作为优化指标,动态调节滤波增益,以此来提高状态估计精度、平稳性与鲁棒性。地面静态试验表明:紧组合协方差成形自适应滤波器定位误差均值与均值稳定性均优于标准卡尔曼滤波器,定位精度提高了约50%,能够提供亚米级单点定位导航服务。相较于集中式滤波器设计方案,分布式滤波器方案计算复杂度降低了63.5%。
According to the application requirement of the precision single-point positioning, the adaptive filtering method for MIMU/GNSS tightly-coupled system based on covariance shaping is studied. The distributed filter design of the "position filter + speed filter" is given to reduce the computational complexity. The model of MIMU/GNSS tightly-coupled system in geography system is deduced, and the pseudo-range measurement inconsistency is extended into the system state vector to improve the system's ability to suppress the pseudo-range deviation jitter in dynamic environments. The covariance shaping adaptive filtering algorithm utilizes the Frobenius norm to measure the matching degree between the modeling and actuality of residual noise, and dynamically adjust the filter gain to minimize the Frobenius norm which is taken as the optimization index, in order to improve the state estimation accuracy, stability and robustness. The ground static test shows that the positioning error's mean values and the mean-value's stability of the covariance shaping adaptive filter are both better than those of the standard Kalman filter, and the positioning accuracy is increased by approximately 50%, and the sub-level single-point positioning navigation services can be provided. Compared with the centralized filter design scheme, the computational complexity of the distributed filter scheme is reduced by 63.5%.
According to the application requirement of the precision single-point positioning, the adaptive filtering method for MIMU/GNSS tightly-coupled system based on covariance shaping is studied. The distributed filter design of the "position filter + speed filter" is given to reduce the computational complexity. The model of MIMU/GNSS tightly-coupled system in geography system is deduced, and the pseudo-range measurement inconsistency is extended into the system state vector to improve the system's ability to suppress the pseudo-range deviation jitter in dynamic environments. The covariance shaping adaptive filtering algorithm utilizes the Frobenius norm to measure the matching degree between the modeling and actuality of residual noise, and dynamically adjust the filter gain to minimize the Frobenius norm which is taken as the optimization index, in order to improve the state estimation accuracy, stability and robustness. The ground static test shows that the positioning error's mean values and the mean-value's stability of the covariance shaping adaptive filter are both better than those of the standard Kalman filter, and the positioning accuracy is increased by approximately 50%, and the sub-level single-point positioning navigation services can be provided. Compared with the centralized filter design scheme, the computational complexity of the distributed filter scheme is reduced by 63.5%.
引文
[1]Rabbou M A,El-Rabbany A.Tightly coupled integration of GPS precise point positioning and MEMS-based inertial systems[J].GPS Solutions,2015,19(4):601-609.
[2]Montillet J P,Yu K.Modified leaky LMS algorithms applied to satellite positioning[C]//2014 IEEE 80th Vehicular Technology Conference(VTC2014-Fall).2014:1-5.
[3]Nguyen T T T,Ta T H,Nguyen H L T,et al.An adaptive bandwidth notch filter for GNSS narrowband interference mitigation[J].REV Journal on Electronics and Communications,2015,4(3-4):59-68.
[4]Chiang K W,Lin C A,Peng K Y.The performance analysis of an AKF based tightly-coupled INS/GNSS sensor fusion scheme with non-holonomic constraints for land vehicular applications[C]//Applied Mechanics and Materials.Trans Tech Publications,2013,284:1956-1960.
[5]杨涛,赵子阳,李醒飞,等.多星座GNSS/INS紧耦合方法[J].中国惯性技术学报,2015,23(1):38-42.Yang Tao,Zhao Zi-yang,Li Xing-fei,et al.Tightly-cou pled integration method for multi-constellation GNSS/INS[J].Journal of Chinese Inertial Technology,2015,23(1):38-42.
[6]Jiang F,Swindlehurst A L.Dynamic UAV relay positioning for the ground-to-air uplink[C]//2010 IEEE Globecom Workshops.2010:1766-1770.
[7]Caliskan F,Hacizade C.Sensor and actuator FDI applied to an UAV dynamic model[J].IFAC Proceedings Volumes,2014,47(3):12220-12225.
[8]Rahimi A M,Ruschel R,Manjunath B S.UAV Sensor fusion with latent-dynamic conditional random fields in coronal plane estimation[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2016:4527-4534.
[9]Falco G,Einicke G A,Malos J T,et al.Performance analysis of constrained loosely coupled GPS/INS integration solutions[J].Sensors,2012,12(11):15983-16007.
[10]Nguyen V H.Loosely coupled GPS/INS integration with Kalman filtering for land vehicle applications[C]//2012International Conference on Control,Automation and Information Sciences.2012:90-95.
[11]Hirokawa R,Ebinuma T.A low-cost tightly coupled GPS/INS for small UAVs augmented with multiple GPS antennas[J].Navigation,2009,56(1):35-44.
[12]Custódio A L,Rocha H,Vicente L N.Incorporating minimum Frobenius norm models in direct search[J].Computational Optimization and Applications,2010,46(2):265-278.
[13]李增科,高井祥,姚一飞,等.GPS/INS紧耦合导航中多路径效应改正算法及应用[J].中国惯性技术学报,2014,22(6):782-787.Li Zeng-ke,Gao Jing-xiang,Yao Yi-fei,et al.GPS/INS tightly-coupled navigation with multipath correction algorithm[J].Journal of Chinese Inertial Technology,2014,22(6):782-787.
[14]王琰,张传定,胡小工,等.卫星分群的抗差Kalman滤波在GPS/BDS融合精密单点定位中的应用[J].中国惯性技术学报,2016,24(6):769-774.Wang Yan,Zhang Chuan-ding,Hu Xiao-gong,et al.Robust Kalman filtering based on different satellite types and it's application in GPS/BDS precise point positioning[J].Journal of Chinese Inertial Technology,2016,24(6):769-774.
[15]郑辛,付梦印.SINS/GPS紧耦合组合导航[J].中国惯性技术学报,2011,19(1):33-37.Zheng Xin,Fu Meng-yin.SINS GPS tightly-coupled integrated navigation[J].Journal of Chinese Inertial Technology,2011,19(1):33-37.
[2]Montillet J P,Yu K.Modified leaky LMS algorithms applied to satellite positioning[C]//2014 IEEE 80th Vehicular Technology Conference(VTC2014-Fall).2014:1-5.
[3]Nguyen T T T,Ta T H,Nguyen H L T,et al.An adaptive bandwidth notch filter for GNSS narrowband interference mitigation[J].REV Journal on Electronics and Communications,2015,4(3-4):59-68.
[4]Chiang K W,Lin C A,Peng K Y.The performance analysis of an AKF based tightly-coupled INS/GNSS sensor fusion scheme with non-holonomic constraints for land vehicular applications[C]//Applied Mechanics and Materials.Trans Tech Publications,2013,284:1956-1960.
[5]杨涛,赵子阳,李醒飞,等.多星座GNSS/INS紧耦合方法[J].中国惯性技术学报,2015,23(1):38-42.Yang Tao,Zhao Zi-yang,Li Xing-fei,et al.Tightly-cou pled integration method for multi-constellation GNSS/INS[J].Journal of Chinese Inertial Technology,2015,23(1):38-42.
[6]Jiang F,Swindlehurst A L.Dynamic UAV relay positioning for the ground-to-air uplink[C]//2010 IEEE Globecom Workshops.2010:1766-1770.
[7]Caliskan F,Hacizade C.Sensor and actuator FDI applied to an UAV dynamic model[J].IFAC Proceedings Volumes,2014,47(3):12220-12225.
[8]Rahimi A M,Ruschel R,Manjunath B S.UAV Sensor fusion with latent-dynamic conditional random fields in coronal plane estimation[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2016:4527-4534.
[9]Falco G,Einicke G A,Malos J T,et al.Performance analysis of constrained loosely coupled GPS/INS integration solutions[J].Sensors,2012,12(11):15983-16007.
[10]Nguyen V H.Loosely coupled GPS/INS integration with Kalman filtering for land vehicle applications[C]//2012International Conference on Control,Automation and Information Sciences.2012:90-95.
[11]Hirokawa R,Ebinuma T.A low-cost tightly coupled GPS/INS for small UAVs augmented with multiple GPS antennas[J].Navigation,2009,56(1):35-44.
[12]Custódio A L,Rocha H,Vicente L N.Incorporating minimum Frobenius norm models in direct search[J].Computational Optimization and Applications,2010,46(2):265-278.
[13]李增科,高井祥,姚一飞,等.GPS/INS紧耦合导航中多路径效应改正算法及应用[J].中国惯性技术学报,2014,22(6):782-787.Li Zeng-ke,Gao Jing-xiang,Yao Yi-fei,et al.GPS/INS tightly-coupled navigation with multipath correction algorithm[J].Journal of Chinese Inertial Technology,2014,22(6):782-787.
[14]王琰,张传定,胡小工,等.卫星分群的抗差Kalman滤波在GPS/BDS融合精密单点定位中的应用[J].中国惯性技术学报,2016,24(6):769-774.Wang Yan,Zhang Chuan-ding,Hu Xiao-gong,et al.Robust Kalman filtering based on different satellite types and it's application in GPS/BDS precise point positioning[J].Journal of Chinese Inertial Technology,2016,24(6):769-774.
[15]郑辛,付梦印.SINS/GPS紧耦合组合导航[J].中国惯性技术学报,2011,19(1):33-37.Zheng Xin,Fu Meng-yin.SINS GPS tightly-coupled integrated navigation[J].Journal of Chinese Inertial Technology,2011,19(1):33-37.