A comparative performance study of extended kalman filter, unscented kalman filter and least square approaches in receiver autonomous integrity monitoring based global navigation satellite system integrity

Global Navigation Satellite System (GNSS) positioning accuracy and trust in this system are of great importance in sectors such as the aviation and defense industry, especially in life-critical applications. One of the different methods used to increase positioning accuracy and improve trust in the system is the Receiver Autonomous Integrity Monitoring (RAIM) method. With this method, fault detection and integrity assurance can be achieved without relying on any external source. Within the scope of this study, 3 different RAIM algorithms based on Least Square (LS), Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) methods were compared and performance analyses were conducted under stationary and dynamic scenarios exposed to different error models. This comparison, made using both real data and simulator-based data, is a remarkable contribution of the study to the GNSS and integrity monitoring literature. As a result of the study, the success of the LS RAIM method in both fault detection exclusion and protection level calculations stands out compared to other methods.