In this paper, an integrated calibration method for position sensitive detector (PSD) of moving support mechanism in vacuum plasma environment is proposed. That is, the PSD is used to track the laser spot to restore the coordinate information of the signal. Firstly, a PSD integrated calibration principle is proposed to reduce the position error of the signaler by tracking laser points with PSD. Then on this basis, due to the spatial declination angle in the PSD imaging model, a spatial declination correction model was established to compensate the spatial declination error. Finally, there are errors occurred in the measurement because of the nonlinearity of PSD, and the improved backpropagation (BP) neural network calibration algorithm is adopted to further correct the errors through the Fletcher–Reeves linear search method to obtain the accurate coordinate information of the annunciator. MATLAB is used to verify the convergence of the calibration algorithm error. Simulation results show that 951 epochs need to be trained by using the traditional BP algorithm to make the position error converge to 0.001 mm. But when using the improved BP algorithm, only 44 epochs are needed.

提出了一种在真空等离子体环境下移动支撑机构位置敏感检测器（PSD）的集成标定方法。即，PSD用于跟踪激光光斑以恢复信号的坐标信息。首先，提出了PSD集成校准原理，以通过跟踪带有PSD的激光点来减少信号器的位置误差。然后在此基础上，由于PSD成像模型中的空间偏角，建立了空间偏角校正模型以补偿空间偏角误差。最后，由于PSD的非线性，在测量中会出现误差，并采用改进的反向传播（BP）神经网络校准算法，通过Fletcher-Reeves线性搜索方法进一步校正误差，以获得信号器的准确坐标信息。MATLAB用于验证校准算法误差的收敛性。仿真结果表明，采用传统的BP算法需要训练951个历元，以使位置误差收敛到0.001 mm。但是，当使用改进的BP算法时，仅需要44个纪元。