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Communication Dans Un Congrès Année : 2020

Sea Target Classification Based On An A Priori Motion Model

Jimmy Bondu
  • Fonction : Auteur
  • PersonId : 1071912
Vincent Corretja
  • Fonction : Auteur
  • PersonId : 1071913
Marie Pommier
  • Fonction : Auteur
  • PersonId : 1071914

Résumé

Target classification can be of real interest for sea surveillance in both civil and military contexts. To address this issue, we present two approaches based on the Singer model. The latter has the advantage of covering a wide range of motions depending on the values of its parameters. Given noisy observations, the first method aims at estimating the motion model parameters by taking advantage of the properties of the correlation function of the estimated acceleration. It is based on a genetic algorithm. The second approach is on-line and consists in deriving a joint tracking and classification (JTC) method. Based on various simulations, we study their respective relevance in different operational settings. The proposed JTC corresponds to the best compromise in terms of performance and number of samples required.
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Dates et versions

hal-02716100 , version 1 (01-06-2020)

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Citer

Jimmy Bondu, Eric Grivel, Audrey Giremus, Pierrick Legrand, Vincent Corretja, et al.. Sea Target Classification Based On An A Priori Motion Model. EUSIPCO 2020 - 28th European Signal Processing Conference, Aug 2020, Amsterdam / Virtual, Netherlands. ⟨10.23919/Eusipco47968.2020.9287480⟩. ⟨hal-02716100⟩
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