An innovation-based cycle-slip, multipath estimation, detection and mitigation method for tightly coupled GNSS/INS/Vision navigation in urban areas

Abstract

Abstract Accurate, continuous and reliable positioning is crucial in various applications. The multi-sensor fusion technique, for example, Global Navigation Satellite System (GNSS)/Inertial navigation system (INS)/Vision integration system, which leverages the strengths of different sensors to achieve high precision positioning services, has been widely applied in mass-market, which could provide global positioning information, is indispensable in localization with multi-sensor fusion. Nevertheless, the positioning performance of GNSS degrades in urban areas due to the frequent signal deteriorating and blocking, which further has a negative effect on the multi-sensor integration positioning. To alleviate the impact of multipath effects and cycle slips on positioning caused by obstructions in urban situations, we propose an innovation-based cycle slip/multipath estimation, detection and mitigation (I-EDM) method for GNSS pseudorange and carrier phase observations. The method obtains the innovations of GNSS observations with cluster analysis method, and then the innovations are used to detect the cycle slips and multipath. Compared with the residual-based preprocessing method, the innovation-based method avoids the residual overfitting caused by the least square method, resulting in better detection of outliers within the observations. The proposed method is validated by the vehicle experiments conducted in urban areas. Experimental results indicates that the accuracy of 0.23, 0.11, 0.31 m in the east, north and up components can be achieved by the GNSS/INS/Vision integration system with I-EDM method, which has a maximum of 21.6% improvement compared with that with residual-based EDM (R-EDM) method.