Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
Online ISSN : 2188-4749
Print ISSN : 2188-4730
The 48th ISCIE International Symposium on Stochastic Systems Theory and Its Applications (Nov. 2016, FUKUOKA)
INS/GNSS/Vehicle Speed Integration for Land Vehicles with Utilizing Zero-Velocity Information
Toma OnishiRyo SugiuraYukihiro KuboSueo Sugimoto
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2017 Volume 2017 Pages 63-69

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Abstract

For highly precise positioning of land vehicles, in this paper, we present an integration method of the low-cost MEMS (Micro Electro Mechanical Systems) INS (Inertial Navigation System), GNSS (Global Navigation Satellite Systems) and vehicle speed information. In this paper, we develop the MEMS INS/GNSS/Vehicle Speed (VS) integration system by extending and refining our previous works [1] [2]. The VS is the vehicle speed obtained by counting the wheel rotation of the land vehicle. In the system, so-called the loosely coupled mechanization is applied. Thus, the three dimensional position, velocity, attitude of the vehicle and the three-dimensional accelerometer and gyro biases are estimated by the Kalman filter by using the measurement of GNSS and VS. And the estimated (predicted) INS errors are fed back to the INS calculations. In the previously presented method [2], once the system starts to calculate its navigation states (position, velocity, attitude and sensor errors), they are updated by the Kalman filter by using all the available measurements. However, the general GNSS point positioning method [3] is applied in the system, so the coordinate output by the receiver can move (jump) about several meters even if the vehicle is stopping. This can cause estimation errors in the Kalman filter, and consequently the performance of the system can be degraded. In this paper, therefore, we propose methods to improve the position accuracy by efficiently utilizing the zero velocity information [4]. The experiments have been carried out on country roads. Throughout the experiments, the proposed method can effectively fix the GPS position and provide accurate navigation consequently.

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