基于RBF神经网络的GPS对流层延迟插值模型

摘要

为提高对流层延迟的内插精度,构建了一种基于RBF神经网络的GPS对流层延迟内插模型.以安徽省电力系统6个CORS基站的坐标和对流层延迟作为建模数据,4个CORS基站的坐标和对流层延迟作为测试数据,验证了该模型的可靠性.试验表明:所提模型的对流层延迟插值精度可达毫米级.%In order to improve the accuracy of tropospheric delay interpolation,a model of delay tropospheric delay inter-polation based on RBF neural network is established. Taking the coordinates and tropospheric delay of ten CORS base stations in Anhui Province as the modeling data,among them,the coordinates and tropospheric delay of the six CORS stations are taken as the modeling data,the coordinates and tropospheric delay of the other four CORS stations are used as test data to verify the reliability of the model. The experimental results show that the tropospheric interpolation accuracy of the test data reaches the millimeter level.