Before revision:  Our experiments on simulated and real-world data show that Particle RAIM achieves smaller positioning errors as well as smaller probability of false alarm and probability of missed-identification in determining system availability than existing urban localization and IM approachesin challenging environments with a relatively small computation overhead .
After revision:  From the inferred particle distribution and GMM, we determine the navigation system availability based on specified integrity requirements. Unlike traditional residual-based integrity monitoring algorithms that analyze measurement residuals from an estimated receiver position, we incorporate measurement residuals from multiple particles to estimate the receiver position and monitor integrity. Our method achieves small horizontal positioning errors compared to existing filter-based state estimation techniques on challenging simulated and real urban driving scenarios with multiple erroneous measurements. Through multiple simulations, we also show that our method determines system availability with comparable false alarms and missed identifications to best-performing existing integrity monitoring approaches .