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Statistical Real-time Model for Performance Prediction of Ship Detection from Microsatellite Electro-Optical Imagers

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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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Correspondence to FabianD Lapierre.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Lapierre, F., Borghgraef, A. & Vandewal, M. Statistical Real-time Model for Performance Prediction of Ship Detection from Microsatellite Electro-Optical Imagers. EURASIP J. Adv. Signal Process. 2010, 475948 (2009) doi:10.1155/2010/475948

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Keywords

  • Radar
  • Performance Prediction
  • Processing Load
  • Sensor Receiver
  • Publisher Note