@inproceedings{ef128443e6af46759c391651ebe159e3,
title = "Initial alignment of Inertial Navigation System based on a predictive iterated Kalman filter",
abstract = "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.",
keywords = "Inertial Navigation System, Initial alignment, Iterative filter, Kalman filter, Predictive filter",
author = "Guanghao Cheng and Songyin Cao and Lei Guo and Wenhua Chen",
note = "Publisher Copyright: {\textcopyright} 2018 Technical Committee on Control Theory, Chinese Association of Automation.; 37th Chinese Control Conference, CCC 2018 ; Conference date: 25-07-2018 Through 27-07-2018",
year = "2018",
month = oct,
day = "5",
doi = "10.23919/ChiCC.2018.8483957",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "4655--4660",
editor = "Xin Chen and Qianchuan Zhao",
booktitle = "Proceedings of the 37th Chinese Control Conference, CCC 2018",
address = "United States",
}