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Statistical Analysis of the Detection Probability of the TianTuo-3 Space-based AIS

Published online by Cambridge University Press:  14 September 2017

Shiyou Li ,
Lihu Chen ,
Xiaoqian Chen ,
Yong Zhao  and
Lei Yang
Shiyou Li*
Affiliation:
(College of Aerospace Science and Engineering, National University of Defense Technology, Changsha, 410073, China)
Lihu Chen
Affiliation:
(College of Aerospace Science and Engineering, National University of Defense Technology, Changsha, 410073, China)
Xiaoqian Chen
Affiliation:
(College of Aerospace Science and Engineering, National University of Defense Technology, Changsha, 410073, China)
Yong Zhao
Affiliation:
(College of Aerospace Science and Engineering, National University of Defense Technology, Changsha, 410073, China)
Lei Yang
Affiliation:
(College of Aerospace Science and Engineering, National University of Defense Technology, Changsha, 410073, China)
*
(E-mail: toneylab@163.com)
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Abstract

The Micro-Nano satellite TianTuo-3 (TT-3) developed by the National University of Defense Technology (NUDT) was successfully launched on 20 September 2015. The space-based Automatic Identification System (AIS) on board TT-3 works well and stably receives AIS signals from global vessels. In this work, we perform statistical analysis on the detection probability of the vessels in the concerned areas by using the TT-3 AIS data. The results suggest that the detection probability of vessels decreases as the distribution density increases, especially in the offshore areas of dense traffic and the TT3-AIS vessel detection probability in the oceans can be higher than 40%, indicating that the TT-3 AIS has achieved a high probability of coverage of vessels for a single receiving antenna. The analysis results will present helpful references both in evaluating the potential application of satellite-based AIS and for designing the next generation space-based AIS which might greatly improve the detection probability of ocean-going vessels.

Keywords

TianTuo-3Space-based AISDetection probabilitySignal confliction

Information

Type
Research Article
Information
The Journal of Navigation , Volume 71 , Issue 2 , March 2018 , pp. 467 - 481
Copyright
Copyright © The Royal Institute of Navigation 2017 

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References

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