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A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation

Authors
  • Lai, Qifeng1, 2
  • Yuan, Hong1
  • Wei, Dongyan1
  • Wang, Ningbo1
  • Li, Zishen1
  • Ji, Xinchun1
  • 1 (X.J.)
  • 2 School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100864, China
Type
Published Article
Journal
Sensors
Publisher
MDPI AG
Publication Date
Apr 30, 2020
Volume
20
Issue
9
Identifiers
DOI: 10.3390/s20092551
PMID: 32365805
PMCID: PMC7249057
Source
PubMed Central
Keywords
Disciplines
  • Article
License
Green

Abstract

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 of the method can be close to that in the open-sky context. In the satellite outage context, the error divergence of the MTF is obviously slower than the traditional GNSS/INS tightly coupled integration, as seen by odometer and barometric altimeter assisting.

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