Precise Forecast and Application of Time Delay Receiving Schedule for a New Generation of Polar Orbit Meteorological Satellite

HTML  XML Download Download as PDF (Size: 229KB)  PP. 142-149  
DOI: 10.4236/jgis.2018.101006    885 Downloads   1,595 Views  

ABSTRACT

In order to finely predict the receiving schedule of the new generation of polar orbit meteorological satellite time-delay data and solve the problem of rapid positioning of lost data, this paper studies and proposes the satellite data recording and satellite program-controlled program, and designs the delay data receiving timeline precision forecasting method. It is concluded that the detection load of polar orbit meteorological satellite in our country has developed from single load to multiple loads, and the detection data need to be downloaded to the ground for processing and application. And as the satellite load increases and the accuracy of each payload detection and channel increases, the amount of probing data will further increase, which in turn will require further increase of the speed of data transmission in the earth. Due to the limitation of the space data transmission frequency band, under the prior art system, the increase of the satellite data transmission rate is limited. On the basis of understanding the working principle of Fengyun-3, the new transmission system will be implemented in terms of data source compression, channel coding, modulation and polarization multiplexing by exploring new weather transmission systems for meteorological satellites in the future upgrade and at the same time analyze ways to avoid inter-satellite interference in order to solve the contradiction between the increase of data volume and the resource of terrestrial data transmission in the existing system.

Share and Cite:

Cheng, Z. , Lin, M. and Fan, C. (2018) Precise Forecast and Application of Time Delay Receiving Schedule for a New Generation of Polar Orbit Meteorological Satellite. Journal of Geographic Information System, 10, 142-149. doi: 10.4236/jgis.2018.101006.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.