Particle swarm optimization for integrity monitoring in BDS/DR based railway train positioning

Satellite navigation system, especially the BeiDou Navigation Satellite System (BDS), has become a significant resource for many transport branches. It is strongly required that BDS is applied in modern railway transportation systems to support the rapid development of Chinese railway infrastructure and services. Currently, the BDS is still in the developing period, and the existing resources are not sufficient to support integrity assurance for many safety-related railway applications. The aim of this paper is therefore to develop a novel integrity monitoring method for the BDS-based train positioning with assistance from the additional dead reckoning system. In this method, the raw measurements of sensors are fused with the Bayesian filtering, and the self-weight adaptive particle swarm optimization with a combined objective function is involved to achieve an effective solution for the horizontal protection level which indicates the integrity capability. Field data are taken to validate effectiveness of the proposed solution and the advantages of the integrated particle fitness strategy. The implementation of this method will be positive for realizing fault detection and isolation for a series of safety-related railway applications based on BDS.