Collaborative positioning method via GPS/INS and RS/MO multi-source data fusion in multi-target navigation
Rui Liu, Klaus Greve, Pengyu Cui, Nan Jiang
Abstract
This paper aims to design a method of multi-source data fusion in multi-target collaborative navigation. First, the respective features of GPS/INS/RS/MO data in the navigation process are clarified. Then a multi-source data fusion method is designed including GPS/INS data fusion with adaptive Kalman filter, RS/MO data fusion with ranging table matching of observation targets, and joint adjustment with fused GPS/INS and RS/MO data. Finally, a simulation experiment is carried out to verify the improvement in positioning efficiency and precision. The results show that collaborative navigation based on multi-source data fusion can increase the stability and accuracy of the navigation service.
Topics & Concepts
Global Positioning SystemComputer scienceSensor fusionKalman filterGPS/INSFusionMap matchingAssisted GPSReal-time computingComputer visionArtificial intelligenceTelecommunicationsLinguisticsPhilosophyInertial Sensor and NavigationTarget Tracking and Data Fusion in Sensor NetworksIndoor and Outdoor Localization Technologies