Optimizing RAIM algorithm of GNSS receiver based on UKF

Minor faults or variations in GNSS satellites can lead to a decline in the quality of received data, affecting the accuracy, continuity, and availability of navigation and positioning. Traditional snapshot algorithms struggle to effectively detect such faults. In response, an improved GNSS receiver autonomous integrity monitoring (RAIM) algorithm is proposed. This algorithm first employs the unscented Kalman filter (UKF) to reduce pseudorange observation noise and then detects and excludes faults using UKF-RAIM algorithm test results. Experimental results demonstrate that compared to the least squares (LS) based RAIM algorithm, the proposed UKF-RAIM algorithm improves positioning accuracy by 83.27%, 75.24%, and 58.45% in the east, north, and up directions, respectively, under conditions of minor pseudorange bias. Under conditions of micro and slowly growing pseudorange bias, the positioning accuracy in the east, north, and up directions improves by 58.29%, 63.56%, and 7.30%, respectively. Therefore, the UKF-RAIM algorithm exhibits superior performance in detecting minor or slight faults in GNSS, with navigation positioning accuracy significantly better than that of the traditional LS-RAIM algorithm.