A Neural Network Approach to Weibull Distributed Sea Clutter Parameter's Estimation

• Autores: José Raúl Machado Fernández, Jesus de la Concepción Bacallao Vidal, Nelson Chávez Ferry
• Localización: Inteligencia artificial: Revista Iberoamericana de Inteligencia Artificial, ISSN-e 1988-3064, ISSN 1137-3601, Vol. 18, Nº. 56, 2015, págs. 3-13
• Idioma: inglés
• Enlaces
  • Texto completo
• Resumen

  • The main problem faced by sea radars is the elimination of an undesirable signal that appears mixed with target information: sea clutter. The clutter results from the echo caused by the rebound of the primary emission at sea surface. One of the most popular probability distributions in clutter modelling is the Weibull distribution. Helpful in efficient detectors’ design, a system able to recognize the Weibull shape parameter knowing a priori that the mean of the distribution is equal to zero is proposed. The result is appropriate for real time operating conditions as it is based on a neural networks approximation in the estimator role.