Vision measurement error control and compensation of spatial coordinates based on BP neural network

Based on the fact that during the geometric variables measurement course of spatial three-dimension coordinates by bino-theodolites, system errors of vertical observing angles' reading occur at certain position by experiment data, the result of which leads to bad effects to precision, objected to spatial coordinates measurement system, the mathematic model of point coordinate and distance to be measured was established, and the cause of system error by means of space rendezvous and docking technology was analyzed. The idea was proposed of regarding system error as nonlinear component, training neural network's (NN) by samples met the condition of system error existence to approach nonlinear function, and exciting NN to efficiently control and compensate system errors. In simulation, the weights of NN were optimized according to the precision performance index, and better parameters' configurations were obtained. In experiment, consistence degree of compensated results and theoretical results validates the effectiveness of this method.