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Xing Wang

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Proceedings Article | 30 August 2023 Paper

Detection and recognition of aircraft target in SAR image

Xing Wang, Wen Hong, Yunqing Liu

Proceedings Volume 12797, 127971V (2023) https://doi.org/10.1117/12.3007349

KEYWORDS: Synthetic aperture radar, Target detection, Target recognition, Feature extraction, Convolution, Small targets

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Synthetic aperture radar (SAR) has been widely applied in the remote sensing field. SAR compensates for the shortcomings of infrared and optics remote sensing, which can observe targets regardless of time and weather. The interpretation of SAR images has always been a research hotspot. Aircraft are an important military and transportation target. Rapid detection and recognition of aircraft targets are significant to combat decision-making and civil aviation dispatching. The research content of this paper is to detect and recognize the aircraft target in SAR image. With the rapid development of computer vision and deep learning theory, this paper proposed an improved algorithm based on YOLOv5s. Firstly, multi methods of data augmentation (Data-Aug) are used in our algorithm to enhance the diversity of the dataset and generalization of the trained model. Secondly, this paper proposed the Ghost structure to optimize the YOLOv5 network to decrease the parameters of the model and the amount of computation. Thirdly, the convolutional block attention module (CBAM) is incorporated into the backbone section of YOLOv5 to help extract useful information. Finally, a series of experiments showed that the proposed algorithm performed better without affecting the calculation speed.

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