Track frame approach for heading and attitude estimation in operating railways using on-board MEMS sensor and encoder. (November 2021)

• Record Type: Journal Article
• Authors: Briales, Eduardo; Urda, Pedro; Escalona, José L.
• Is Part Of: Measurement. Volume 184(2021)
• Publication Date: 2021-11
• Subjects: 3D orientation estimation -- Fusion algorithm -- Inertial sensors -- Experimental setup -- Railway mechanics -- Industrial environment; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2021.109898
• Languages: English
• ISSNs: 0263-2241

Abstract

Abstract: In this work, the orientation of a railway is estimated with a novel methodology based on multibody system kinematics using the railway-specific track frame . The proposed method improves the prediction model by considering the translational accelerations due to the track negotiation. To this end, the forward velocity of the vehicle, measured with an encoder, and the design geometry of the track are used. This algorithm has been tested on an operational underground light-metro railway with quite good results compared with other data fusion algorithms embedded in commercial Inertial Measurements Units (IMU) that contains no information about the real application whatsoever. Highlights: Railway heading and attitude with respect to the track are estimated. 3D orientation obtained from an inertial sensor, an encoder and track geometry. The proposed model improves prediction model with translational accelerations. Model implemented using GDA and EKF algorithm for results comparative. Experiments accomplished in an operational underground light-metro railway.