During the measurement of large space objects with the laser tracking multilateral method, the measurement accuracy is affected by a lot of factors. The accuracy of the self-calibration is one of key factors. In this paper, a self-calibration optimization method is proposed. Through introducing the cross spatial distribution model of the points for the optimized calibration, the data of the laser base stations obtained from the initial self-calibration are calibrated once again, and the optimization algorithm is used to get the more accurate data of the laser base stations, so as to reduce the error in the self-calibration process and improve the accuracy of laser tracking multilateral measurement. The distance measurement experiment on a groups of space points in the x-axis direction was carried out, the optimization effect of the data of base stations was verified through introducing calibration points. The experiment results indicate that the distances of the measured points obtained based on the data of the base stations after the optimized calibration are closer to the reference distances, and the distance difference is reduced from -2. 3 μm to -1. 6 μm after optimization at the position with the x-axis coordinate of 750 mm. So, the self-calibration optimization method proposed in this paper could improve the accuracy of the laser tracking multilateral measurements.