Research on Hierarchical Subway Positioning System Integrating Hamming Code QR Codes and Hall Sensors

Aiming at the demand for high-precision positioning through perception systems in complex metro tunnel environments, this paper proposes a hierarchical composite positioning system fusing 16-bit Hamming code extended QR codes with Hall sensors. By constructing a three-level anti-defacement mechanism (image enhancement - defacement detection - Hamming code error correction) and a Hall sensor total error model incorporating wheel slip errors and installation deviations, error compensation between visual and relative positioning is achieved via a weighted Kalman filter. Experiments show that the anti-defacement algorithm enables the QR code recognition rate to reach 95.3% in 25% defacement scenarios, while the Kalman filter reduces velocity measurement error from 0.32 m/s to 0.02 m/s (an 85% reduction). A 25-150 meter spacing experiment reveals that positioning error exhibits quadratic growth with spacing, determining the critical safe spacing as 145 meters (error ≤ 0.3 meters). This hierarchical architecture effectively suppresses cumulative errors through a nonlinear error correction mechanism, providing critical spacing design and anti-interference technical solutions for intelligent rail transit positioning systems.