A new approach to GPS integrity monitoring using prior probability models and optimal threshold search

Current methods for GPS receiver autonomous integrity monitoring are limited by the assumptions they make. Using published studies of navigation system reliability, this paper develops a prior probability model for spacecraft and receiver anomalies based on non-ideal failure models and the uncertainty present in their failure distribution parameters. With this model, the thresholds for a residuals test statistic are found to optimize an arbitrary objective function based on relative costs for false alarm and missed detection errors. The outputs of Monte Carlo simulations allow thresholds to be computed for each geometry case using trial-and-error optimization. The simulation outputs suggest that the assumptions of traditional RAIM may be partially invalid. These results are useful for both snapshot RAIM tests as well as multi-step integrity algorithms which use Bayesian updating to generate posterior failure probabilities. Multi-step algorithms may be a valuable addition to the future GIC integrity structure