GNSS Pseudorange Differencing for Relative Train Positioning: Performance Assessment in a Railway Environment

Capillary railway lines, though vital for regional development, face economic challenges due to high infrastructure costs. Replacing trackside sensors with onboard GNSS-based positioning offers a cost-effective solution, but standard GNSS methods struggle to meet stringent railway safety standards. This study explores GNSS pseudorange differencing—a relative positioning technique that mitigates common GNSS errors and enables its application in train collision avoidance systems without necessitating full system certification. We present mathematical formulations for several differencing methods and validate them through real-world experiments on a capillary railway line using a light train. Results confirm that horizontal differencing improves accuracy, robustness, and relative speed estimation, supporting its potential for infrastructure-light, safety-critical rail applications.