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[e002] MEMS IMU/ZUPT Based Cubature Kalman Filter Applied to Pedestrian Navigation System

1 International Institute for Advanced Aerospace Technologies of St Petersburg State University of Aerospace Instrumentation - SET Laboratory, Electronic Department of Saad Dahlab University of Blida-Soumaa-Algeria
2 International Institute for Advanced Aerospace Technologies of Saint Petersburg State University of Aerospace Instrumentation
3 Centre Tecnol`ogic de Telecomunicacions de Catalunya (CTTC) Av. Carl Friedrich Gauss 7, 08860 Castelldefels, Spain.
* Author to whom correspondence should be addressed.
2 June 2014
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Abstract

The Extended Kalman Filter (EKF) has been the state of the art in integrated navigation systems and especially in Pedestrian Dead-Reckoning PDR for foot-mounted Inertial Measurements Units. However in most related work with PDR, indirect filtering approach is used based on linear error Kalman Filter (KF). In this work, it is proposed to outperform this approach by the use of Direct filtering approach, which involves the non-linearity in the propagation of the orientation, velocity and in some models, in position coordinates, where the EKF can not achieve optimal estimation. We propose then, the usage of the most recent algorithms developed in the last decade; Sigma Point Kalman Filters (SPKF), especially based on Cubature rule, called Cubature Kalman Filter (CKF) as the integration algorithm for the inertial measurements. The CKF improves the mean and covariance propagation consequently comparing with EKF and previous SPKF (UKF, CDKF). Although the CKF provides a better estimate of the orientation, velocity and position with Zero velocity UPdaTes (ZUPT) measurements and Zero Angular Rate UpdaTes (ZARUT), additional sensors are necessary to measure other states such as yaw angle and to estimate properly the gyroscope bias. We studied then the possibility to integrate electronic compass as additional measure and also Map street data base or Map building data base depending on the type of navigation "Indoor", "Outdoor". In order to get much better estimation based on the Cubature rule, it is proposed to synthesize CKF in order to get robust estimation against nonlinearity of the process and the multiple measurement sensors.

Keywords

GNSS, accelerometers, gyroscopes, Kalman filter, UKF, CDKF, CKF

Cite this article as

Benzerrouk, H.; Nebylov, A.; Closas, P. MEMS IMU/ZUPT Based Cubature Kalman Filter Applied to Pedestrian Navigation System. In Proceedings of the 1st Int. Electron. Conf. Sens. Appl., 1–16 June 2014; Sciforum Electronic Conference Series, Vol. 1, 2014 , e002; doi:10.3390/ecsa-1-e002

Copyright & Licensing

Copyright by the author(s). This is an open access article distributed under the Creative Commons Attribution License (CC-BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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