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Research on SAR Image Target Recognition Based on Convolutional Neural Network
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Abstract
A synthetic aperture radar (SAR) automatic target recognition can effectively improve the utilization efficiency of SAR image data. In order to improve the generalization and accuracy of SAR image target recognition, a convolutional neural network model is proposed to be applied to SAR image target recognition. Firstly, the network structure is designed for the characteristics of SAR image. Secondly, the introduction of dense block network structure improves the generalization performance of the model. Finally, Dropout reduced the computational complexity of the network and improved the generalization performance of the model. Experimental data were obtained from the United States Moving and Stationary Target Acquisition and recognition database. Experimental results of 10 types of target recognition showed that the overall recognition rate of the improved convolutional neural network is 99.18%. The convolutional neural network model proposed in this study improves the accuracy and generalization of the network, and is an effective method for target recognition of SAR images.
Title: Research on SAR Image Target Recognition Based on Convolutional Neural Network
Description:
Abstract
A synthetic aperture radar (SAR) automatic target recognition can effectively improve the utilization efficiency of SAR image data.
In order to improve the generalization and accuracy of SAR image target recognition, a convolutional neural network model is proposed to be applied to SAR image target recognition.
Firstly, the network structure is designed for the characteristics of SAR image.
Secondly, the introduction of dense block network structure improves the generalization performance of the model.
Finally, Dropout reduced the computational complexity of the network and improved the generalization performance of the model.
Experimental data were obtained from the United States Moving and Stationary Target Acquisition and recognition database.
Experimental results of 10 types of target recognition showed that the overall recognition rate of the improved convolutional neural network is 99.
18%.
The convolutional neural network model proposed in this study improves the accuracy and generalization of the network, and is an effective method for target recognition of SAR images.
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