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Remote Sensing
Volume 17
Issue 3
10.3390/rs17030475
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Fast Generalized Radon–Fourier Transform Based on Blind Speed Sidelobe Traction

by
Difeng Sun
1,2,
He Xu
3,
Jin Li
2,
Zutang Wu
2,
Jun Yang
2,
Youcao Wu
1,
Baoguo Zhang
2,
Qianqian Cheng
2 and
Jianbing Li
1,*
1
State Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System, College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China
2
National Key Laboratory of Intense Pulsed Radiation Simulation and Effect, Northwest Institute of Nuclear Technology, Xi’an 710024, China
3
National Innovation Institute of Defense Technology (NIIDT), Beijing 100080, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(3), 475; https://doi.org/10.3390/rs17030475
Submission received: 30 November 2024 / Revised: 24 January 2025 / Accepted: 27 January 2025 / Published: 30 January 2025
(This article belongs to the Special Issue Advances in Radar Systems for Target Detection and Tracking (Second Edition))
Versions Notes

Abstract

The generalized Radon–Fourier transform (GRFT) is a well-established coherent accumulation technique for high-speed and high-mobility target detection. However, this method tends to suffer from the difficulty of identifying the main lobe from multiple blind speed sidelobes (BSSLs) and the computational complexity is generally high. To address these challenges, we propose a new method, namely the BSSL Traction Particle Swarm Optimization (BTPSO), to robustly and accurately extract the main lobe. In the method, the relationship between the main lobe and the BSSLs is used to attract particles to potential positions of the main lobe in the group when trapped in local optimal, and a new termination criterion in which multiple particles should converge to the same optimal value is proposed to avoid local convergence. Simulation examples show that the proposed method can improve the probability of converging to the main lobe peak while reducing cost time, and its good adaptability to low signal-to-noise ratio (SNR) cases is well verified.
Keywords: generalized Radon–Fourier transform; blind speed sidelobe; Particle Swarm Optimization; high-speed; high-mobility; coherent accumulation; fast implementation generalized Radon–Fourier transform; blind speed sidelobe; Particle Swarm Optimization; high-speed; high-mobility; coherent accumulation; fast implementation

Share and Cite

MDPI and ACS Style

Sun, D.; Xu, H.; Li, J.; Wu, Z.; Yang, J.; Wu, Y.; Zhang, B.; Cheng, Q.; Li, J. Fast Generalized Radon–Fourier Transform Based on Blind Speed Sidelobe Traction. Remote Sens. 2025, 17, 475. https://doi.org/10.3390/rs17030475

AMA Style

Sun D, Xu H, Li J, Wu Z, Yang J, Wu Y, Zhang B, Cheng Q, Li J. Fast Generalized Radon–Fourier Transform Based on Blind Speed Sidelobe Traction. Remote Sensing. 2025; 17(3):475. https://doi.org/10.3390/rs17030475

Chicago/Turabian Style

Sun, Difeng, He Xu, Jin Li, Zutang Wu, Jun Yang, Youcao Wu, Baoguo Zhang, Qianqian Cheng, and Jianbing Li. 2025. "Fast Generalized Radon–Fourier Transform Based on Blind Speed Sidelobe Traction" Remote Sensing 17, no. 3: 475. https://doi.org/10.3390/rs17030475

APA Style

Sun, D., Xu, H., Li, J., Wu, Z., Yang, J., Wu, Y., Zhang, B., Cheng, Q., & Li, J. (2025). Fast Generalized Radon–Fourier Transform Based on Blind Speed Sidelobe Traction. Remote Sensing, 17(3), 475. https://doi.org/10.3390/rs17030475

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