Research on radar target radial length extraction algorithm based on U-Net

Bo Li; Huan Liu; Jihao Yang; Hongmei Ren

doi:10.1117/12.3025913

1 April 2024 Research on radar target radial length extraction algorithm based on U-Net

Bo Li, Huan Liu, Jihao Yang, Hongmei Ren

Proceedings Volume 13081, Third International Conference on Advanced Manufacturing Technology and Electronic Information (AMTEI 2023); 1308110 (2024) https://doi.org/10.1117/12.3025913
Event: 2023 3rd International Conference on Advanced Manufacturing Technology and Electronic Information (AMTEI 2023), 2023, Tianjin, China

Abstract

The main problem with the current radar target radial length extraction algorithm is its susceptibility to interference signals, which makes it difficult to optimize the boundaries of the target support area, especially the impact of noise at positions that tend to be farther away from the target support. Therefore, based on deep learning networks, this article trains and analyzes different pixel points, completes the segmentation of the target support area and background area through image semantic segmentation algorithms, obtains the target support area, and estimates the radial length of the target based on the boundary of the target support area. Finally, validate the effectiveness of the algorithm using simulation data.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Bo Li, Huan Liu, Jihao Yang, and Hongmei Ren "Research on radar target radial length extraction algorithm based on U-Net", Proc. SPIE 13081, Third International Conference on Advanced Manufacturing Technology and Electronic Information (AMTEI 2023), 1308110 (1 April 2024); https://doi.org/10.1117/12.3025913

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