Abstract:When multiple gross errors exist in a multi-constellation GNSS receiver, the traditional gross error detection and exclusion(FDE) method requires frequent searching to exclude potential observations, and the efficiency of excluding gross errors is low and positioning accuracy may be drastically reduced. Therefore, we propose an inertial-aided multiple gross errors detection and exclusion method. This method introduces the inertial state model and measurement model into the receiver autonomous integrity monitoring to construct the global and local test statistic to detect the outliers, excluding the wrong observations. The results show that when there are more than two gross errors in the receiver, the traditional gross error detection and exclusion method has a high rate of false detection and missing detection, and our method can significantly improve the detection efficiency and positioning accuracy.