This paper presents an integrated measurement technique based on DC methods (vertical electrical sounding, electrical resistivity tomography) which was used to identify faults and determine their geoelectric parameters in the western part of the Chuya basin. New information on the structure of the Chagan River valley located in the zone of the disastrous 27 September 2003 Chuya earthquake has been obtained from the results of these methods. Geoelectric cross-sections of the sedimentary sequence and the upper part of the basement were obtained from VES data, showing the block structure of the study area. Electrical resistivity tomography sections confirm the presence of a major fault between basement blocks of different heights and indicate the presence of faults bounding the valley on its right side and in the southwestern part. 相似文献
It is an objective fact that there exists error in the satellite dynamic model and it will be transferred to satellite orbit determination algorithm, forming a part of the connotative model error. Mixed with the systematic error and random error of the measurements, they form the unitive model error and badly restrict the precision of the orbit determination. We deduce in detail the equations of orbit improvement for a system with dynamic model error, construct the parametric model for the explicit part of the model and nonparametric model for the error that can not be explicitly described. We also construct the partially linear orbit determination model, estimate and fit the model error using a two-stage estimation and a kernel function estimation, and finally make the corresponding compensation in the orbit determination. Beginning from the data depth theory, a data depth weight kernel estimator for model error is proposed for the sake of promoting the steadiness of model error estimation. Simulation experiments of SBSS are performed. The results show clearly that the model error is one of the most important effects that will influence the precision of the orbit determination. The kernel function method can effectively estimate the model error, with the window width as a major restrict parameter. A data depth-weight-kernel estimation, however, can improve largely the robustness of the kernel function and therefore improve the precision of orbit determination. 相似文献