测绘通报 ›› 2019, Vol. 0 ›› Issue (3): 1-5.doi: 10.13474/j.cnki.11-2246.2019.0067

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GPS coordinates transformation based on convolutional neural network

CUI Fang, ZHAO Shuxu   

  1. School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
  • Received:2018-03-13 Online:2019-03-25 Published:2019-04-02

Abstract: The GPS coordinate conversion method is crucial for GPS space location system.In the past,many methods have been proposed to convert GPS coordinates,but the effect is not very significant.The reason is that most of the models have model errors and projection errors.In view of the shortcomings of the current methods,this paper proposes a GPS coordinate transformation based on convolution neural network (CNN) by using the advantages of deep learning on unstructured data processing method.This method transforms GPS data into unstructured image data and uses these unstructured image data as the input layer of CNN to train the GPS coordinate transformation model so as to minimize the requirement of data preprocessing and to learn from the data without supervision out of effective features.Experimental results show that this method has higher conversion accuracy than the traditional coordinate transformation method.

Key words: deep learning, neural networks, convolutional neural networks, coordinate transformation, GPS

CLC Number: