首页> 外文会议>Geoscience and Remote Sensing, 1997. IGARSS '97. Remote Sensing - A Scientific Vision for Sustainable Development., 1997 IEEE International >Artificial neural network-based inversion technique for extracting ocean surface wave spectra from SAR images
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Artificial neural network-based inversion technique for extracting ocean surface wave spectra from SAR images

机译:基于人工神经网络的反演技术从SAR图像中提取海面波谱

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An artificial neural network (ANN) based nonlinear technique for inverting the SAR image spectrum of ocean surface waves is developed. In this technique, a multi-layer perceptron (MLP) is used to perform the inversion process. The MLP is trained using simulated SAR and wave spectra. The training process utilizes the standard error-backpropagation technique. The results indicate that the method works well over a large range of wind and wave conditions. The error in the inversion process was found to increase in the higher sea states. The technique works best if the network is used within the range over which it was trained. It is noted that this technique may be used independent of SAR imaging models, by training the network with coincident and co-located measurements of SAR and wave spectra.
机译:提出了一种基于人工神经网络的非线性技术,用于反演海面波的SAR像谱。在这种技术中,多层感知器(MLP)用于执行反演过程。使用模拟的SAR和波谱对MLP进行训练。训练过程利用标准的误差反向传播技术。结果表明,该方法在大范围的风浪条件下均能很好地工作。发现在较高海况下反演过程中的误差增加了。如果在训练范围内使用网络,则该技术效果最佳。注意,可以通过对网络进行SAR和波谱的重合和共处测量来训练网络,从而独立于SAR成像模型使用此技术。

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