航向信息辅助的MIMU/GPS高精度组合导航方法
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摘要
为了在卫星颗数少于四颗时实现高精度低成本导航,提出了一种基于航向信息辅助的MIMU/GPS高精度组合导航方法。采用MIMU与GPS构成MIMU/GPS组合导航系统;针对GPS卫星颗数少于四颗而无法定位的问题,利用MIMU导航解算获得的位置信息与GPS星历数据信息构造等效伪距,将其与GPS输出的伪距对应相减作为组合导航量测之一;针对组合后航向精度较低甚至发散的问题,利用GPS输出的水平速度计算获得伪航向角,将MIMU导航解算获得的航向角与该伪航向角相减作为量测之二;采用卡尔曼滤波设计组合导航滤波算法。跑车实验结果表明,在多次出现卫星颗数少于四颗时,该组合导航方法的位置精度达到±10.3 m(3σ),水平姿态精度达到±20.1′(3σ),航向精度达到±19.5′(3σ)。因此,该方法有效解决了卫星颗数少于四颗时的高精度导航问题,而且显著提高了航向精度,特别是在失准角较大的情况下也能够实现滤波快速收敛。
In order to achieve high precision and low cost navigation with fewer than four satellites, MIMU/GPS precise integrated navigation method aided by heading information is proposed. The micro inertial measurement unit(MIMU) and Global Positioning System(GPS) are chosen to construct MIMU/GPS integrated navigation system. To solve the problem of being unable to realize the positioning function when with <4 satellites, the position information calculated by the output of MIMU and the ephemeris data output of GPS are utilized to construct the equivalent pseudo range, then this equivalent pseudo range and the pseudo range output from GPS are chosen as one of the observations of integrated navigation. To solve the problem that the heading error of integrated navigation is large or even divergent, the horizontal velocities of GPS are utilized to calculate the pseudo heading angle, then this pseudo heading angle and the heading angle calculated by the output of MIMU are chosen as the other observation. Kalman filter is adopted to design the integrated navigation filtering algorithm. Experimental results show that, when the number of satellites is less than four repeatedly, the position accuracy of the integrated navigation method is ?10.3 m(3σ), the horizontal attitude accuracy is ?20.1′(3σ), and the heading accuracy is ?19.5′(3σ). Therefore, this method effectively solves the problem of precise navigation when the number of satellites is less than four, and the heading accuracy is improved greatly. In particular, the navigation filtering can converge quickly in the case with large misalignment angles.
In order to achieve high precision and low cost navigation with fewer than four satellites, MIMU/GPS precise integrated navigation method aided by heading information is proposed. The micro inertial measurement unit(MIMU) and Global Positioning System(GPS) are chosen to construct MIMU/GPS integrated navigation system. To solve the problem of being unable to realize the positioning function when with <4 satellites, the position information calculated by the output of MIMU and the ephemeris data output of GPS are utilized to construct the equivalent pseudo range, then this equivalent pseudo range and the pseudo range output from GPS are chosen as one of the observations of integrated navigation. To solve the problem that the heading error of integrated navigation is large or even divergent, the horizontal velocities of GPS are utilized to calculate the pseudo heading angle, then this pseudo heading angle and the heading angle calculated by the output of MIMU are chosen as the other observation. Kalman filter is adopted to design the integrated navigation filtering algorithm. Experimental results show that, when the number of satellites is less than four repeatedly, the position accuracy of the integrated navigation method is ?10.3 m(3σ), the horizontal attitude accuracy is ?20.1′(3σ), and the heading accuracy is ?19.5′(3σ). Therefore, this method effectively solves the problem of precise navigation when the number of satellites is less than four, and the heading accuracy is improved greatly. In particular, the navigation filtering can converge quickly in the case with large misalignment angles.
引文
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[3]Yang R Y,Wang G C,Gao W,et al.An anti-interference MIMU/GPS vehicle integrated navigation algorithm based on IDNN-EKF[C]//IEEE/ION Position,Location and Navigation Symposium.Savannah,USA,2016:157-164.
[4]Zihajehzadeh S,Loh D,Lee T J,et al.A cascaded Kalman filter-based GPS/MEMS-IMU integration for sports applications[J].Measurement,2015,73:200-210.
[5]Romaniuk S,Gosiewski Z.Kalman filter realization for orientation and position estimation on dedicated processor[J].Acta Mechanica Et Automatica,2014,8(2):88-94.
[6]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 T,Zhao Z Y,Li X F,et al.Tightly-coupled integration method for multi-constellation GNSS/INS[J].Journal of Chinese Inertial Technology,2015,23(1):38-42.
[7]Chiang K W,Lin C A,Peng K Y.The performance analysis of an AKF based tightly-coupled INS/GNSSsensor fusion scheme with non-holonomic constraints for land vehicular applications[J].Applied Mechanics and Materials,2013,284:1956-1960.
[8]Amin M S,Reaz M B I,Nasir S S,et al.Low cost GPS/IMU integrated accident detection and location system[J].Indian Journal of Science&Technology,2016,9(10):221-229.
[9]Gao N,Zhao L.An integrated land vehicle navigation system based on context awareness[J].GPS Solutions,2016,20(3):509-524.
[10]Wu Z,Yao M,Ma H,et al.Low-cost attitude estimation with MIMU and two-antenna GPS for Satcom on the move[J].GPS Solutions,2013,17(1):75-87.
[11]Nassar S,Schwarz K P,El-Sheimy N,et al.Modeling inertial sensor errors using autoregressive(AR)models[J].Navigation,2004,51(4):259-268.
[12]闫捷,徐晓苏,张涛,等.舰载小型化SINS/GNSS紧组合导航系统设计[J].中国惯性技术学报,2013,21(6):775-780.Yan J,Xu X S,Zhang T,et al.Design of marine-based miniature tightly integrated SINS/GNSS navigation system[J].Journal of Chinese Inertial Technology,2013,21(6):775-780.