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INS/GPS组合导航中的病态问题及其处理方法
引用本文:金际航,常国宾,穆敬,李科.INS/GPS组合导航中的病态问题及其处理方法[J].海洋测绘,2015(4):28-32.
作者姓名:金际航  常国宾  穆敬  李科
作者单位:海军海洋测绘研究所,天津 300061;海军大连舰艇学院 海洋测绘系,辽宁 大连 116018
基金项目:国家自然科学基金(41404001)
摘    要:在地球表面附近的组合导航中,一般以经、纬度表示水平位置,单位为弧度(rad),以高程表示竖直位置,单位为米(m)。1m的定位误差仅相当于约10-7rad,从而造成定位协方差矩阵的条件数达1013量级。Kalman滤波中要对协方差矩阵求逆,过高的条件数将引起严重的病态问题,从而造成很大的数值误差,影响滤波精度,甚至造成滤波发散。提出一种直接的解决方法,即构建一种避免病态问题的组合导航滤波模型。具体过程为:引入一种尺度因子(即平均地球半径)对组合导航系统的状态量、观测量、状态方程以及观测方程进行线性变换,从而对经、纬度误差进行适当的尺度化,明显降低协方差矩阵的条件数,有效避免了滤波过程中病态问题的出现。新方法在不明显增加计算量的前提下有效解决了病态问题,并保证了Kalman滤波的最优性质。数值仿真验证了该方法的有效性。

关 键 词:INS/GPS组合导航  Kalman滤波  协方差矩阵  病态  尺度因子

Solution to Ill-posed Problems in INS / GPS Integrated Navigation
JIN Jihang,CHANG Guobin,MU Jing,LI Ke.Solution to Ill-posed Problems in INS / GPS Integrated Navigation[J].Hydrographic Surveying and Charting,2015(4):28-32.
Authors:JIN Jihang  CHANG Guobin  MU Jing  LI Ke
Institution:Naval Institute of Hydrographic Surveying and Charting,Tianjin 300061 ,China;Department of Hydrography and Cartography,Dalian Naval Academy,Dalian 116018 ,China
Abstract:In the integrated navigation near the earth surface,horizontal positions are represented by latitude andlongitude with radians as their units while vertical positions by heights with meters as units.However the positionerror of one meter is equivalent to about 10- 7.radians,resulting in a positioning error covariance with conditioningnumber being about 1013.As the inverse of the covariance matrix is necessary in the Kalman filter,a largeconditioning number may lead to serious ill-posed problems,which further cause a bad impact on the accuracy ofthe system,and sometimes make the filter diverge.In this contribution,a more direct method is proposed,i.e.thata kind of filtering model without potential ill-posed problems is constructed.A scaling factor,i.e.the averageradius of the earth,is introduced to linearly transform the state process equation and the measurement equation,hence the latitude and longitude error is enlarged in the number and the covariance matrix is properly scaled.As aresult,the conditioning number is reduced significantly to avoid the potential ill-posed problem effectively.Theproposed method can retain the optimality of Kaman filter without obviously increasing the computational load.Simulation results validate the effectiveness of the proposed method.
Keywords:
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