光电经纬仪不规则点阵的识别方法

在电子经纬仪测量过程中，点阵图像经常出现不规则的形状，导致识别误码率很高．基于BP神经网络技术，提出了一种适合各种形态点阵特性的识别方法，以增强对不规则点阵和图像噪声的适应能力，从而提高点阵识别的精度．实验结果表明，这种方法具有较高的抗干扰性和抗畸变能力，准确率高，满足事后数据处理要求．

A Recognition Method of Irregular Lattices in Photoelectricity Theodolite

Because of irregular shapes of lattice images produced in photoelectricity theodolite, error rate of code is high when it is recognized. A recognition method based on BP neural network is presented, which is adapted to a variety of lattice shapes. It can process irregular lattices and image noise so that a recognition precision of lattice images can be improved greatly. The experimental results show that the method has anti-noise and anti-aberration ability, making lattice recognition rate higher and meeting data post-processing requirement.