Evaluation on loosely and tightly coupled GNSS/INS vehicle navigation system

2017 ◽  
Author(s):  
Jian Wang ◽  
Dan Liu ◽  
Wei Jiang ◽  
Debiao Lu
Keyword(s):  
Navigation System ◽  
Vehicle Navigation ◽  
Vehicle Navigation System ◽  
Tightly Coupled

A Fault-Tolerant Tightly Coupled GNSS/INS/OVS Integration Vehicle Navigation System Based on an FDP Algorithm

2019 ◽  
Vol 68 (7) ◽  
pp. 6365-6378 ◽  
Author(s):  
Wei Jiang ◽  
Dan Liu ◽  
Baigen Cai ◽  
Chris Rizos ◽  
Jian Wang ◽  
...  
Keyword(s):  
Navigation System ◽  
Fault Tolerant ◽  
Vehicle Navigation ◽  
Vehicle Navigation System ◽  
Tightly Coupled

scholarly journals A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2551 ◽  
Author(s):  
Qifeng Lai ◽  
Hong Yuan ◽  
Dongyan Wei ◽  
Ningbo Wang ◽  
Zishen Li ◽  
...  
Keyword(s):  
Navigation System ◽  
Rapid Development ◽  
Satellite System ◽  
Urban Environments ◽  
Sensor Technology ◽  
Vehicle Navigation ◽  
Noise Compensation ◽  
Vehicle Navigation System ◽  
Tightly Coupled ◽  
Global Navigation Satellite

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.

Self-localization and positioning vehicle navigation system based on computer vision and PID control

2019 ◽  
Author(s):  
Christian Quintanar-Sotelo ◽  
Ernesto Bernal-Ortega ◽  
Adrian Navarro-Carranza ◽  
Alan J. Romo-Munoz ◽  
Jorge A. de la Cruz Morales ◽  
...  
Keyword(s):  
Computer Vision ◽  
Pid Control ◽  
Navigation System ◽  
Vehicle Navigation ◽  
Vehicle Navigation System

Research on Improvement Road Impedance Function Based on Vehicle Navigation System

2013 ◽  
Vol 659 ◽  
pp. 45-48
Author(s):  
Rui Wang ◽  
Zai Tang Wang
Keyword(s):  
Path Planning ◽  
Navigation System ◽  
Vehicle Navigation ◽  
Impedance Function ◽  
Vehicle Navigation System ◽  
Navigation Path ◽  
Planning Algorithm ◽  
Improved Model ◽  
Path Planning Algorithm ◽  
Impedance Functions

Comparing with some widely used road impedance functions, this paper choose BPR model as base model of improvement, and determine the parameter of BPR model. We apply the improved model to vehicle navigation system in the path planning algorithm, and experiments proved that the model satisfies navigation path planning requirement and have universal performance.

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