In the measurement of subway tunnel profile parameters， it is necessary to calibrate the high-speed Lidar point cloud with high precision. In particular， the tunnel environment in large scenes has high requirements for calibration templates， complicated calibration process， and great influence on detection accuracy. To solve this problem， a novel calibration method for subway tunnel contour point cloud was proposed in this paper， and the algorithm was studied based on dual lidar measurement system. In this method， a special manual portable calibration system was designed. The objective function was established by using the calibration plate line features extracted from point cloud data， and the global optimal solution was found through the nonlinear optimization method combining genetic algorithm and Levenberg-Marquardt algorithm to realize the calibration of lidar. The experimental results show that the calibration error of the top rail is within ±1.5 mm. Static measurement accuracy X error within ±1 mm， Y error within ±4 mm； When the acquisition system performs data acquisition at a speed of 5 km/h， the dynamic measurement accuracy X error is within ±4 mm and Y error is within ±6 mm. This method can realize the high-precision calibration of lidar， the algorithm is robust， easy to operate， and has the characteristics of strong environmental adaptability.