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《ACTA GEODAETICA ET CARTOGRAPHIC SINICA》 1999-04
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Conversion of GPS Height by Artifical Neural Network Method

YANG Ming qing 1, JIN Fan 2, ZHU Da cheng 1, CHEN Xian chun 1 (1. Sichuan Bureau for Surveying and Mapping, Chengdu,Sichuang, 610081; 2. Southwest Jiaotong University, Chengdu,Sichuang, 610031)  
At present, the coordinate system of GPS is the World Geodetic System 84.Positions determined by GPS receiver are put in geocentric coordinate or geodetic coordinate defined by WGS 84 ellipsoid, but in engineering application, the coordinates need to be converted for local coordinate system, and ellipsoidal height need to be converted for physical height, viz. orthometric height or normal height. Ellipsoidal height conversion to physical height is difficult, because this conversion bears on determination of an unknown Geoid, which relates to the distribution of matter in earth. In this paper a conversion method of GPS geodetic height to orthometric height or normal height using artificial neural network is proposed. The method avoids puzzle for determination of Geoid, establishes mapping relation from GPS ellipsoidal height to orthometric height or normal height by dint of neural network learning function. An improved BP neural network topological architecture and algorithm are also given in this paper. Using the neural network the GPS height in a survey area is converted to test, the results show that accuracy of conversion is about the order of 2cm. This method is also compared with fitting method that simulates Geoid (or Quasi Geoid) using quadric polynomial for conversion of GPS height. The accuracy of artificial neural network method is better than that of fitting method. The known sample amount in request is also much less.
【CateGory Index】: P228
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1 CHEN Lian-cheng (Municipal Construction and Investment Ltd of Zhangzhou City of Fujian Province,Zhangzhou 363000,China);STUDY OF GPS CONTROL NETWORK FOR VERY LARGE BRIDGE[J];Geology of Anhui;2006-01
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10 WU Ying-ying,XIA Bin,LIU qiao(College of Computer Science and Engineering of Guizhou University,Guiyang 550025,China);Application of GA-based Neural Network in the AC Speed Adjustment[J];Journal of Chongqing Institute of Technology;2006-02
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