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Statistical real-time model for performance prediction of ship detection from microsatellite electro-optical imagers
Lapierre, F.D.; Borghgraef, A.; Vandewal, M. (2010). Statistical real-time model for performance prediction of ship detection from microsatellite electro-optical imagers. Eurasip Journal on Advances in Signal Processing 2010: 475948. https://hdl.handle.net/10.1155/2010/475948
In: Eurasip Journal on Advances in Signal Processing: Cham. ISSN 1687-6180, more
Peer reviewed article  

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Keyword
    Marine

Authors  Top 
  • Lapierre, F.D., more
  • Borghgraef, A., more
  • Vandewal, M., more

Abstract
    For locating maritime vessels longer than 45 meters, such vessels are required to set up an Automatic Identification System (AIS) used by vessel traffic services. However, when a boat is shutting down its AIS, there are no means to detect it in open sea. In this paper, we use Electro-Optical (EO) imagers for noncooperative vessel detection when the AIS is not operational. As compared to radar sensors, EO sensors have lower cost, lower payload, and better computational processing load. EO sensors are mounted on LEO microsatellites. We propose a real-time statistical methodology to estimate sensor Receiver Operating Characteristic (ROC) curves. It does not require the computation of the entire image received at the sensor. We then illustrate the use of this methodology to design a simple simulator that can help sensor manufacturers in optimizing the design of EO sensors for maritime applications.

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