摘要
在AHRS/GPS导航定位中,系统包含有非线性观测量,需要建立实时的EKF(推广卡尔曼滤波器),以通过当前状态Taylor展开来近似非线性。以低成本陆用AHRS(航姿参考系统)/GPS紧耦合导航系统为研究对象,构建了基于伪距、伪距率、航向角组合观测数学模型。作为滤波算法的改进,文中采用了迭代EKF,逼近导航参数的非线性函数,从而得到了自适应的载体参数线性模型。仿真结果表明,该算法模型可使姿态角、速度、位置误差均方差分别控制在120^(?)、0.01m/s和4m以内,导航参数的精度有显著提高。
In the field of AHRS （Attitude and heading reference system）/GPS integration, the measurement model of this system contains nonlinear observations, and need to establish an real-time EKF（extended Kalman filter）, so as to approximate nonlinear components by Taylor Expansion. Taking low cost tightly-coupled AHRS/GPS land vehicular integration as study object, the parameter model for is established that combines the pseudo-range, pseudo-range-rate ＆ heading measurements. As an improvement for the filter algorithms, the iterated EKF（1EKF） is adopted to approach the nonlinear functions, thus getting the adaptive linear parameter model. Simulation results indicate that the mean-square deviations of attitude, velocity and position errors don＇t exceed 120＂, 0.01 m/s, and 4 m respectively using IEKF with the combined measurements model, remarkably improving the accuracy of the navigation parameters.
出处
《中国惯性技术学报》
EI
CSCD
2007年第6期707-712,共6页
Journal of Chinese Inertial Technology
基金
国家自然科学基金(60474046)
