Multi-Sensor System for Vehicle Positioning in Dense Urban Areas

Popović, Željko; Soloviev, Andrey; Mochizuki, Yutaka

doi:10.4271/2011-01-1035

Cited by 6 publications

(1 citation statement)

References 16 publications

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“…2,integrated positioning algorithm to output the inertial navigation system used as reference data to inertial positioning system as the filter state equation, the output of each independent positioning algorithm as the difference of the input filter. Then, introduces the dead reckoning algorithm, the inertial navigation system independent positioning algorithm and calculating the position independent GPS coordinates conversion algorithm [10].…”

Section: Independent Location Algorithmmentioning

confidence: 99%

Research on Localization Vehicle Based on Multiple Sensors Fusion System

Zhu

Tian

Guizhong

et al. 2017

2017 International Conference on Computer Network, Electronic and Automation (ICCNEA)

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In the implementation and verification of multi sensor fusion of vehicle positioning, we built a verification platform positioning algorithm combined simulation of Car Sim-Simulink to Car Sim, the vehicle model and the sensor output as the data source, and the noise, then in the simulink environment to build the fusion localization algorithm, and the real vehicle experiment using inertial laboratory navigation equipment, to the actual sensor data validation algorithm. Simulation and experimental verification results show that the effectiveness of the fusion location algorithm, the GPS is invalid; the error is effectively reduced to rely solely on dead reckoning positioning inertial navigation system, to achieve effective positioning all the time.

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Section: Independent Location Algorithmmentioning

confidence: 99%