A kind of SAR image ship target recognition method and system

Abstract

The invention relates to a method for recognizing a ship target in a SAR image. This SAR image ship target recognition method preprocesses the training data through the proposed inter-category sample imbalance processing technology (including upsampling processing based on data enhancement and proportional generation batch method), while improving the diversity of training data, Keep the training data sent to the network balanced between categories; through the proposed dense residual network for ship target recognition in SAR images, the original features can be reused while learning more new features; through the proposed The loss function of the center loss adjusts the parameters of the network model to realize the simultaneous optimization of intra-class compactness and inter-class separability. The recognition results on OpenSARShip show that the designed dense residual network has higher accuracy, smaller model size and less calculation than the existing neural network.

Description

technical field [0001] The invention relates to the technical field of target recognition and radar remote sensing, in particular to a method and system for SAR image ship target recognition. Background technique [0002] Synthetic Aperture Radar (SAR) uses the movement of the remote sensing platform to install a small-aperture antenna on the side of the platform, and forms an equivalent large-aperture antenna through movement to achieve the purpose of improving azimuth resolution. It is an all-weather, all-weather sensor that can generate high-resolution SAR images and is widely used in military and civilian fields. With the increase of available SAR images, the automatic and intelligent interpretation of SAR images has become more and more important, and ships, as important military and civilian targets, are the objects that need to be paid attention. Object recognition has received a lot of research, and many results have emerged. At present, most of the ship target rec...

AI Technical Summary

Problems solved by technology

The currently public dataset for SAR image target recognition is only available in OpenSARShip, but this dataset has the problem of unbalanced samples between categories, which leads to a serious decline in recognition performance

Moreover, the existing classic CNN is specially designed for three-channel natural images, but when applied to SAR images, there are problems of model parameter redundancy and large amount of calculation.

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