Evaluation of GNSS Receiver Autonomous Integrity Monitoring for multiple outliers with a smart random sample consensus strategy

Receiver Autonomous Integrity Monitoring (RAIM) procedures for Global Navigation Satellite Systems (GNSS) are critical for the applications requiring safety and reliability. The existing RAM algorithms, usually based on the single outlier assumption model, are not adequate for the next generation GNSS. A RAM scheme based on a random sample consensus is presented as an alternative for multiple outlier detection and isolation. Instead of selecting the initial hypothetical inlier subset completely randomly, the RAIM scheme uses the information of a residual sensitivity matrix to make “smart” selections and speed up the algorithm. Detailed simulations and analysis have been performed to evaluate the performance of the new “smart” strategy. Results have shown that the strategy is capable of isolating outliers and can get a comparable solution to the optimal in theory.