Una Aproximación Neuronal al Reconocimiento del Parámetro de Forma de la Distribución K asociada a Clutter Marino
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 probabilit...
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| Autores principales: | , , |
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| פורמט: | Online |
| שפה: | eng |
| יצא לאור: |
Universidad de Costa Rica
2017
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| נושאים: | |
| גישה מקוונת: | https://revistas.ucr.ac.cr/index.php/ingenieria/article/view/23994 |
| תגים: |
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| סיכום: | 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. |
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