FACET-based SAR imaging and target detection based on YOLOv7

Qingkuan Wang; Qingfen Wang; Zhaolong Wang; Tao Song; Tong Wang

doi:10.1117/12.3005100

20 October 2023 FACET-based SAR imaging and target detection based on YOLOv7

Qingkuan Wang, Qingfen Wang, Zhaolong Wang, Tao Song, Tong Wang

Proceedings Volume 12916, Third International Conference on Signal Image Processing and Communication (ICSIPC 2023); 129160U (2023) https://doi.org/10.1117/12.3005100
Event: Third International Conference on Signal Image Processing and Communication (ICSIPC 2023), 2023, Kunming, China

Abstract

In order to improve the detection capability of typical non-cooperate targets, a facet-based synthetic aperture radar (SAR) imaging algorithm, and a SAR image target detection model are presented in this paper. At first, the shooting and bouncing ray (SBR) method was utilized to calculate the backscattering coefficient of each facet on the typical target surface. Then, based on the radar echo generation method and SAR imaging algorithm, the SAR images of the targets can be obtained by simulation. Therefore, a SAR image dataset can be established containing simulation results under different conditions. Finally, combined with the most recently proposed YOLOv7 deep learning model, the feature learning and training based on the target SAR dataset are realized. Compared with the previous original YOLOv5 and improved YOLOv5 networks, experimental results show that YOLOv7 performs better in precision and efficiency under the same conditions, which provides a concrete foundation for future research.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qingkuan Wang, Qingfen Wang, Zhaolong Wang, Tao Song, and Tong Wang "FACET-based SAR imaging and target detection based on YOLOv7", Proc. SPIE 12916, Third International Conference on Signal Image Processing and Communication (ICSIPC 2023), 129160U (20 October 2023); https://doi.org/10.1117/12.3005100

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KEYWORDS

Synthetic aperture radar

Target detection

Detection and tracking algorithms

Target recognition

Radar imaging

Computer simulations

Convolutional neural networks

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