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神经网络在海洋雷达系统中的海杂波抑制和目标增强。

Sea clutter reduction and target enhancement by neural networks in a marine radar system.

机构信息

Signal Theory and Communications Department, Superior Politechnic School, University of Alcalá, Alcalá de Henares, 28805, Madrid, Spain.

出版信息

Sensors (Basel). 2009;9(3):1913-36. doi: 10.3390/s90301913. Epub 2009 Mar 16.

Abstract

The presence of sea clutter in marine radar signals is sometimes not desired. So, efficient radar signal processing techniques are needed to reduce it. In this way, nonlinear signal processing techniques based on neural networks (NNs) are used in the proposed clutter reduction system. The developed experiments show promising results characterized by different subjective (visual analysis of the processed radar images) and objective (clutter reduction, target enhancement and signal-to-clutter ratio improvement) criteria. Moreover, a deep study of the NN structure is done, where the low computational cost and the high processing speed of the proposed NN structure are emphasized.

摘要

海杂波的存在有时是不希望出现在海洋雷达信号中的。因此,需要有效的雷达信号处理技术来减少它。在这种情况下,所提出的杂波减少系统中使用了基于神经网络 (NN) 的非线性信号处理技术。所开发的实验显示了有前途的结果,其特点是不同的主观(处理后的雷达图像的视觉分析)和客观(杂波减少、目标增强和信杂比改善)标准。此外,还对神经网络结构进行了深入研究,强调了所提出的神经网络结构的低计算成本和高处理速度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a42c/3345818/61eb6242bfa9/sensors-09-01913f1.jpg

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