Improved RAIM Algorithm Based on Kalman Innovation Monitoring Method

Integrity monitoring is an important means to guarantee the integrity of satellite navigation system. Receiver autonomous integrity monitoring (RAIM), as a client integrity monitoring method, has a lot of advantages such as not dependent on external equipment, low cost and easy to implement. Therefore, it is widely used in integrity monitoring. Traditional RAIM methods comprise RAIM algorithm based on Kalman filter and snapshot algorithm based on pseudorange observation. Compared with the snapshot algorithm, the Kalman filter innovation monitoring method is not limited to use the current measurement. Therefore it has advantages of independent detection and less calculation. It also can be used under the condition of few satellites. Unfortunately, the Kalman filter-based method is not sensitive to slowly varying pseudorange fault. Thus we propose an integrated algorithm combining the parity vector method based on the non-coherent accumulation with Kalman filter-based detection method. The result shows that, compared with the traditional parity vector method and the Kalman filter-based detection method, the proposed algorithm has a better result in fault detection and monitoring delay.