A Neural Network Approach to the Recognition of the K Distribution Shape Parameter associated with Sea Clutter
Guardado en:
| Autores: | , , |
|---|---|
| Formato: | artículo original |
| Estado: | Versión publicada |
| Fecha de Publicación: | 2017 |
| Descripción: | The main problem faced today by sea radars is the elimination of clutter, which is undesirable contribution that appears mixed with the target information. The unwanted signal is produced by the echo caused by the rebound of the primary emission at the sea surface. One of the most popular probability distributions in clutter modeling is the K distribution. Helpful in efficient detectors design, a system able to recognize the shape parameter of the K distribution, knowing a priori the value of the scale parameter, is proposed. The result is appropriate for real time operating conditions as it’s based on a neural networks approximation in the pattern recognition role. |
| País: | Portal de Revistas UCR |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Lenguaje: | Inglés |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/23994 |
| Acceso en línea: | https://revistas.ucr.ac.cr/index.php/ingenieria/article/view/23994 |
| Palabra clave: | Sea Clutter Artificial Neural Networks K Distribution Distribution Parameter Recognition Distribution Parameter Identification Clutter Marino Redes Neuronales Artificiales Distribución K Estimación de Parámetros de Distribuciones Probabilísticas aprendizaje por computadora modelación estadística |