A traditional interpolation algorithm with the linear interpolation method (LIM) using a fixed number of reference stations is widely used in network RTK to obtain the ionospheric delays for the users. In low-latitude regions, where the ionosphere is relatively active, however, large interpolation errors exist, especially for satellites at low elevation angles. Considering the characteristics of “coinciding ionospheric pierce points (CIPPs)” with a similar nature of ionospheric delays, an improved interpolation algorithm is proposed. In this algorithm, all stations with CIPPs are used to establish the interpolation model; thus, more precise interpolation model is achieved. To validate the performance of the proposed algorithm, data from some reference stations in Guangdong Province of China were used, and the results are compared with those with the traditional interpolation algorithm. Numerical analysis shows that the interpolation accuracy of the proposed algorithm increases by 10–30% compared with the traditional one. Since the number of reference stations is flexible, the proposed algorithm can also balance the model accuracy with the computation burdens. In addition, the proposed algorithm is less affected by the selection of master reference station. In terms of network RTK on-the-fly positioning, the time-to-first-fix is reduced when replacing the traditional interpolation algorithm with the proposed one. 相似文献
???FG5???????????????????????2008??1?????й??????????о?????3053????????????????????????о?????????????????FG5-214??FG5-232???н???????????????????????????????????????н????????????????????????????????????2~3????10 -8 ms -2?? 相似文献
Urban agglomeration is caused by the continuous acceleration of the urbanization process in China. Studying the expansion of construction land can not only know the changes and development of urban agglomeration in time, but also obtain the great significance of the future management. In this study, taking Changsha-Zhuzhou-Xiangtan (Chang-Zhu-Tan) urban agglomeration in Hunan province as a study area, Landsat images from 1995 to 2014 and Autologistic-CLUE-S model simulation data were used. Moreover, several factors including gravity center, direction, distance and landscape index were considered in the analysis of the expansion. The results revealed that the construction area increased by 132.18%, from 372.28 km2 in 1995 to 864.37 km2 in 2014. And it might even reach 1327.23 km2 in 2023. Before 2014, three cities had their own respective and discrete development directions. However, because of the integration policy implementation in 2008, the Chang-Zhu-Tan began to gather, the gravity center moved southward after 2014, and the distance between cities decreased, which was in line with the development plan of urban expansion. The research methods and results were relatively reliable, and these results could provide some reference for the future land use planning and spatial allocation in the urbanization process of Chang-Zhu-Tan urban agglomeration.
As a cold and dry planet, Mars contains water resources in the form of water ice, so that the electromagnetic waves can be transmitted to the deep underground to get the information of the topography and subsurface geological structure. Subsurface penetrating radar(SPR) can be widely used in deep space exploration for a long time because of its non-destructive detection mode and its working characteristics not limited by visible light. It is an important type of equipment for detecting the subsurface structure of planets. Orbiter radar is mainly used in Mars exploration. However, because of its low resolution, it is difficult to describe the near surface structure, so there is a lack of radar data which can reflect the shallow information. In this paper, a three-dimensional near surface model of Utopia Planitia on Mars is established. In order to make the simulation results more reasonable, the key factors such as topographic relief, subsurface rocks and water ice, and the variation of dielectric constant in different layers are taken into account. Then the full polarization forward modeling is carried out by using the three-dimensional finite-difference time-domain method. The acquired full polarimetric subsurface penetrating radar(FP-SPR) data with noise is preprocessed and further processed by Pauli decomposition. The underground reflection can be picked up more clearly from the Pauli decomposition results. This work is helpful to identify more details of subsurface structures and provides a reference for the measured data in the future. 相似文献