A CIPSO-FCM-Based RAIM Algorithm for the GPS/BDS Integrated Navigation System

Abstract

The receiver integrity monitoring of a satellite navigation system directly affects positioning accuracy and train safety. The GPS/BDS (Global Positioning System/BeiDou Navigation System) integrated navigation system can meet the requirements of RAIM (Receiver Autonomous Integrity Monitoring) for the minimum number of visible satellites. However, the probability of multiple satellite simultaneous failures increases in the GPS/BDS integrated navigation system so that when the failures occur, the RAIM algorithm cannot meet the requirements of safety for the receiver when positioning trains. In response to the problem, this paper applies the CIPSO-FCM (Chaotic Immune-vaccine Particle Swarm Optimization_ Fuzzy C-means) algorithm to RAIM to establish a new algorithm. It can predict the HPL (Horizontal Protection Level) value of the GPS/BDS integrated navigation system to verify RAIM availability. It also uses the parity space vector to obtain cluster samples through a pseudo-range observation matrix. The CIPSO algorithm obtains the initial cluster centers by iteration to prevent the FCM algorithm from falling into the local optimum, leading to inconsistent classification. A test based on actual field data shows that the CIPSO-FCM-based RAIM algorithm achieves a probability of 99.98% for detecting and identifying multiple satellite failures with a gross error of 28m, which can meet the safety requirements for the receiver when positioning trains.

Keywords

• CIPSO-FCM
• GPS/BDS integrated navigation system
• RAIM
• train positioning