Radar Main-Lobe Jamming Suppression Based on Adaptive Opposite Fireworks Algorithm

In the presence of the main lobe jamming, the performance of the modern radar system would degrade significantly. In this study, a blind source separation (BSS) method based on an Adaptive Opposite Fireworks Algorithm (AOFWA) is proposed to address the problem of ineffective target echo detection wh...

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Bibliographic Details
Published in:IEEE Open Journal of Antennas and Propagation 2021, Vol.2, p.138-150
Main Authors: Luo, Weilin, Jin, Hongbin, Li, Hao, Duan, Keqing
Format: Article
Language:English
Subjects:
adaptive opposite operator
blind source separation
Brain modeling
Covariance matrices
firework algorithm
Fireworks algorithm
Interference
Jamming
Main-lobe jamming suppression
Radar
Radar antennas
swarm intelligence
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Summary:In the presence of the main lobe jamming, the performance of the modern radar system would degrade significantly. In this study, a blind source separation (BSS) method based on an Adaptive Opposite Fireworks Algorithm (AOFWA) is proposed to address the problem of ineffective target echo detection when the radar is subjected to main lobe jamming. First, a signal model for BSS applied in the anti-main lobe jamming is provided, and the number of source signals is estimated. Then, an adaptive opposite learning operator is designed to improve the optimization capability and convergence speed of the basic Fireworks Algorithm (FWA). Finally, pulse compression is performed for separated signals to achieve peak detection. The simulation result shows that the proposed algorithm can effectively extract target echo under suppression jamming and deception jamming, and the separation precision is relatively high, and its convergence speed is superior.
ISSN:2637-6431
2637-6431
DOI:10.1109/OJAP.2020.3036878