Issue |
E3S Web Conf.
Volume 94, 2019
International Symposium on Global Navigation Satellite System 2018 (ISGNSS 2018)
|
|
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Article Number | 01013 | |
Number of page(s) | 4 | |
Section | Positioning Technology and Applications | |
DOI | https://doi.org/10.1051/e3sconf/20199401013 | |
Published online | 08 May 2019 |
Integration of Inertial Navigation System with EM-log Using H-infinity Filter
1
Department of Mechanical and Aerospace Engineering, Seoul National University, 08826 Seoul, Korea
2
Automoation and Systems Research Institute, Seoul National University, 08826 Seoul, Korea
3
Agency for Defense Development, 34186 Daejeon, Korea
* Corresponding author: chanpark@snu.ac.kr
This paper presents the integration of inertial navigation system (INS) with electromagnetic-log (EM-log) as an underwater navigation system using H-infinity filter for robustness from the uncertainty of the sea current model. In underwater environments, the electromagnetic signals are attenuated rapidly, so that the global navigation satellite system is not available in general. Thus, INS is usually chosen for underwater navigation, and other aiding sensors are also used to complement its accumulative errors, one of which is EM-log. Since an EM-log provides the relative velocity to seawater, the integrated navigation cannot be performed accurately unless the sea current speed is compensated properly. Generally, the INS and EM-log can be integrated using extended Kalman filter (EKF). However, EKF guarantees its performance when the stochastic properties of the system’s process and measurement noises are perfectly known. In other words, in the presence of sea current modelling errors, the integration using the EKF is not expected to show good performance. On the other hand, H-infinity filter is a robust filter which can tolerate such uncertainties. In this paper, the integration of INS and EM-log using H-infinity filter is studied. The performance is compared with that of the EKF case by proper computer simulation.
© The Authors, published by EDP Sciences, 2019
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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