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Characteristics of Multipath Effects in GPS Dynamic Deformation Monitoring
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作者 HUANG Shengxiang JIN Xiangsheng YANG Baocen 《Geo-Spatial Information Science》 2006年第2期79-83,共5页
ABSTRACT The multipath has long been considered a major error source in GPS applications .The characteristics 0f the GPS signal multipath effects are analyzed. based on which an experiment that considers the characte... ABSTRACT The multipath has long been considered a major error source in GPS applications .The characteristics 0f the GPS signal multipath effects are analyzed. based on which an experiment that considers the characteristics of dynamic deformation monitoring has been carried out. The solution results of observation data in two successive days are processed by a method,which combines the wavelet filtering and the differential correction betweentwo successive days. The research demonstrates that the multipath errors have stronger repeatability on successive days;after significantly mitigating the influence of multipath effects,the accuracy of three-dimensional positioning for GPS dynamic deformation monitoring can attain the mm level,an obvious accuracy improving particularly invertical component.The characteristics of GPS signal multipath,th eexperimental scheme and the qualitative and quantitative analysis of results are detailed. 展开更多
关键词 GPS dynamic deformation monitoring multipath effects error characteristic
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An improved computation scheme of strapdown inertial navigation system using rotation technique 被引量:8
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作者 张伦东 练军想 +1 位作者 吴美平 胡小平 《Journal of Central South University》 SCIE EI CAS 2012年第5期1258-1266,共9页
To improve the accuracy of strapdown inertial navigation system(SINS) for long term applications,the rotation technique is employed to modulate the errors of the inertial sensors into periodically varied signals,and,a... To improve the accuracy of strapdown inertial navigation system(SINS) for long term applications,the rotation technique is employed to modulate the errors of the inertial sensors into periodically varied signals,and,as a result,to suppress the divergence of SINS errors.However,the errors of rotation platform will be introduced into SINS and might affect the final navigation accuracy.Considering the disadvantages of the conventional navigation computation scheme,an improved computation scheme of the SINS using rotation technique is proposed which can reduce the effects of the rotation platform errors.And,the error characteristics of the SINS with this navigation computation scheme are analyzed.Theoretical analysis,simulations and real test results show that the proposed navigation computation scheme outperforms the conventional navigation computation scheme,meanwhile reduces the requirement to the measurement accuracy of rotation angles. 展开更多
关键词 strapdown inertial navigation system rotation technique navigation computation scheme error characteristic
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Nonlinear Systems Identification via an Input-Output Model Based on a Feedforward Neural Network
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作者 O. L. Shuai South China University of Technology, Gungzhou, 510641, P.R. China S. C. Zhou S. K. Tso T. T. Wong T.P. Leung The Hong Kong Polytechnic University, HungHom, Kowloon, HK 《International Journal of Plant Engineering and Management》 1997年第4期45-50,共6页
This paper develops a feedforward neural network based input output model for a general unknown nonlinear dynamic system identification when only the inputs and outputs are accessible observations. In the developed m... This paper develops a feedforward neural network based input output model for a general unknown nonlinear dynamic system identification when only the inputs and outputs are accessible observations. In the developed model, the size of the input space is directly related to the system order. By monitoring the identification error characteristic curve, we are able to determine the system order and subsequently an appropriate network structure for systems identification. Simulation results are promising and show that generic nonlinear systems can be identified, different cases of the same system can also be discriminated by our model. 展开更多
关键词 nonlinear dynamic systems identification neural networks based Input Output Model identification error characteristic curve
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