Initial alignment of Inertial Navigation System based on a predictive iterated Kalman filter
Initial alignment of Inertial Navigation System based on a predictive iterated Kalman filter
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DOI：
10.23919/chicc.2018.8483957
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发表时间：
2018-07
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影响因子：
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通讯作者：
Guanghao Cheng;Songyin Cao;Lei Guo;Wenhua Chen
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文献类型：
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作者：
Guanghao Cheng;Songyin Cao;Lei Guo;Wenhua Chen
惯性导航系统（INS）在实际应用中得到广泛应用。本文考虑惯性导航系统的初始对准问题。由于INS的建模误差难以准确测量，会降低初始对准的精度。本文针对一类具有建模误差和高斯噪声的 INS，提出了一种预测迭代卡尔曼滤波器（PIKF）。首先，通过预测滤波器估计建模误差。然后，为了减小卡尔曼滤波器的一步预测与真实值之间的误差，采用预测滤波器与迭代卡尔曼滤波器相结合的新滤波方法来提高对准精度。最后，对 INS 的静止对准进行了仿真，以显示所提出方法的效率。
Inertial navigation systems (INSs) are widely used in practical applications. This paper considers the problem of initial alignment for an inertial navigation system. As the modeling error of an INS is difficult to be measured accurately, it will decrease the accuracy of the initial alignment. In this paper, a predictive iterated Kalman filter (PIKF) is proposed for a class of INSs with the modeling error and Gaussian noise. Firstly, the modeling error is estimated by a predictive filter. Then, in order to reduce the error between the one step prediction of Kalman filter and the true value, a new filtering method combining a predictive filter with an iterative Kalman filter is used to improve the alignment accuracy. Finally, simulations for the stationary alignment of an INS are given to show the efficiency of the proposed approach.