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A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation by Lai, Qifeng; Yuan, Hong; Wei, Dongyan; Wang, Ningbo; Li, Zishen; Ji, Xinchun is a Engineering article available to read on EtoBox.

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Using the Global Navigation Satellite System (GNSS), it is difficult to provide continuous and reliable position service for vehicle navigation in complex urban environments, due to the natural vulnerability of the GNSS signal. With the rapid development of the sensor technology and the reduction in their costs, the positioning performance of GNSS is expected to be significantly improved by fusing multi-sensors. In order to improve the continuity and reliability of the vehicle navigation system, we proposed a multi-sensor tight fusion (MTF) method by combining the inertial navigation system (INS), odometer, and barometric altimeter with the GNSS technique. Different fusion strategies were presented in the open-sky, insufficient satellite, and satellite outage environments to check the performance improvement of the proposed method. The simulation and real-device tests demonstrate that in the open-sky context, the error of sensors can be estimated correctly. This is useful for sensor noise compensation and position accuracy improvement, when GNSS is unavailable. In the insufficient satellite context (6 min), with the help of the barometric altimeter and a clock model, the accuracy o

Who reads A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation?

Author

Lai, Qifeng; Yuan, Hong; Wei, Dongyan; Wang, Ningbo; Li, Zishen; Ji, Xinchun

Publisher

Molecular Diversity Preservation International; MDPI AG; Multidisciplinary Digital Publishing Institute (MDPI); Basel: Molecular Diversity Preservation International (MDPI), 2001-; Publons (ISSN 1424-8220)

Published

2020

Language

EN

Field

Engineering (Physical Sciences)