Skip to main content
Log in

A novel algorithm for satellite data transmission

  • Published:
Science in China Series E: Technological Sciences Aims and scope Submit manuscript

Abstract

For remote sensing satellite data transmission, a novel algorithm is proposed in this paper. It integrates different type feature descriptors into multistage recognizers. In the first level, the dynamic clustering algorithm is used. In the second level, the improved support vector machines algorithm demonstrates its validity. In the third level, the shape matrices similarity comparison algorithm shows its excellent performance. The single child recognizers are connected in series, but they are independent of each other. Objects which are not recognized correctly by the lower level recognizers are then put into the higher level recognizers. Experimental results show that the multistage recognition algorithm improves the accuracy greatly with higher level feature descriptors and higher level recognizers. The algorithm may offer a new methodology for high speed satellite data transmission.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Gao W B, Ran C Q. The analysis on technology development of data transmission in remote sensing satellites. Chin Space Sci Tech, 2005, 25(6): 30–36

    Google Scholar 

  2. Gao X B, Yang Z X, Xu C Y. Several new kind advanced space broad band data transmission techniques. In: Chinese Society of Space Research Space Exploration Professional Committee 16th Academic Conference Memoir. Beijing: Chinese Society of Space Research, 2003. 539–542

    Google Scholar 

  3. Lionel B, Marek B. Joint friction identification for robots using TSK fuzzy system based on subtractive clustering. In: Annual Meeting of the North American Fuzzy Information Processing Society. Missouri: IEEE, 2008. 1–6

    Google Scholar 

  4. Keerthi S, Lin C J. Asymptotic behaviors of support vector machines with gaussian kernel. Neural Comput, 2003, 15(7): 1667–1689

    Article  MATH  Google Scholar 

  5. Zheng C H, Jiao L C. Automatic parameters selection for SVM based on GA. In: Fifth World Congress on Intelligent Control and Automation. Missouri: IEEE, 2004. 1869–1872

    Chapter  Google Scholar 

  6. Zhang Z H, Pan C H, Ma S D. An automatic method of coarse registration between multi-source satellite images. In: Sensor Networks and Information Processing Conference. Missouri: IEEE, 2004. 205–209

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to ShouJuan Zhang.

Additional information

Supported by the State Key Laboratory Basic Research Program of China (Grant No. 9140C5305020706)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhang, S., Zhou, Q. A novel algorithm for satellite data transmission. Sci. China Ser. E-Technol. Sci. 52, 1429–1434 (2009). https://doi.org/10.1007/s11431-009-0139-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11431-009-0139-8

Keywords

Navigation