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Communication dans un congrès

Target detection based on morphological component analysis of HFSWR images for maritime surveillance

Alexandre Baussard 1 Samuel Grosdidier 2
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (UMR 3192), STIC - Pôle STIC [Brest]
Abstract : To supplement actual systems (like the Automatic Identification System - AIS) to monitor the maritime traffic in given areas within the Exclusive Economic Zone (EEZ - 200nm), High Fre- quency Surface Wave (HFSW) radar seem to be good candidates. Indeed recent works [1, 2] show that they can provide useful informations even if the spatial and temporal resolutions are weaks. A global surveillance system of the EEZ and harbor could also combine HFSW radar for the long range detection and X-band radar for short ranges (<30km). These last systems are more suitable for near area, which are more vulnerable, since they provide good spatial and temporal resolutions. HFSW radars have been efficiently used these last three decades to remotely measure oceano- graphic parameters. They can provide surface currents, wave spectra, wind intensities and di- rections. In this contribution, as already introduced, these systems are considered for traffic surveillance. The used system is a WEllen RAdar (WERA), with a central frequency between 12 and 13MHz, which provides Range-Doppler (RD) images to be processed for the detection part. These RD images, for the detection purpose, are strongly polluted by sea clutter and other interference leading to a challenging problem. In the paper, a short review of previous works about simulating HFSW images [3] and the validation against real data will be given. Then the image processing approach will be detailed. The proposed method is based on the Morphological Component Analysis (MCA) [5, 6]. Due to HF image features, the method had required some adaptations and some first results have been already given in a previous work [4]. In this contribution, some new modifications of the MCA algorithm are introduced in order to enhance the extraction of the target signatures. The new algorithm includes some processing during the iterative MCA process against the multiscale coefficients (this will be detailed in the full paper). Some results from simulated and real data will be display to illustrate the efficiency of the proposed method.
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Contributeur : Annick Billon-Coat <>
Soumis le : vendredi 13 avril 2012 - 12:39:03
Dernière modification le : mercredi 24 juin 2020 - 16:19:22


  • HAL Id : hal-00687505, version 1


Alexandre Baussard, Samuel Grosdidier. Target detection based on morphological component analysis of HFSWR images for maritime surveillance. PIERS 2012, Mar 2012, Kuala Lumpur, Malaysia. pp.87. ⟨hal-00687505⟩



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