An Adapted RAIM Algorithm for Urban Canyon Environment

Receiver Autonomous Integrity Monitoring (RAIM) has been successfully used for fault detection and exclusion in aviation applications. For airborne environment, the Geometric Dilution Of Precision (GDOP) and pseudo-range measurement quality is good. However, for urban canyon environment the GDOP may increase much and the pseudo-range measurement may contain huge multipath error. In this case, the exclusion of any pseudo-range measurement with multipath may make the GDOP increase much more and make the user position accuracy even worse. In this work, we propose an Urban Adapted-RAIM (UA-RAIM) algorithm to adjust the particular poor satellite geometry and multipath environment of urban canyon. Exclusion Accuracy Filter (EAF) is designed to check the position accuracy before and after fault exclusion. The fault satellite which can improve the positioning accuracy is processed using weighted estimation technique. Static experiment was carried out and a reflector was set to simulate the urban canyon environment. The user position errors in North, East and Up direction are 63.70%, 55.25% and 64.52% lower compared with the RAIM algorithm. From the urban vehicle tests, the vehicle positions of UA-RAIM are more like a straight line compared with RAIM. The 95% accuracy decreases from 20.32m to 16.55m using UA-RAIM and about 81.45% compared with the original.