Robust Adaptive Beamforming of LFM Signals Based on Interference-plus-Noise Covariance Matrix Reconstruction in Fractional Fourier Domain
ID:16 Submission ID:114 View Protection:ATTENDEE Updated Time:2023-12-16 19:04:28 Hits:604 Oral Presentation

Start Time:2020-06-08 15:00 (Asia/Shanghai)

Duration:20min

Session:[S] Special Session » [SS17] Robust Beamforming Based On Convex/Nonconvex Optimization

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Abstract
The linear frequency modulation (LFM) signal can accumulate as an impulse in the proper fractional domain, and the phase differences among the peaks on the sensors mainly depend on the incident angle of the LFM signal and the antenna structure. A novel robust adaptive beamforming is proposed by the interference-plus-noise covariance matrix (INCM) reconstruction in fractional Fourier domain. The fractional Fourier transform (FRFT) is applied to the radar echoes and the peaks in fractional domain can be extracted to reconstruct the INCM with the Capon spatial spectrum. The optimal weight vector can be obtained by solving the optimization problem. Simulation results demonstrate that the proposed method can efficiently suppress the deception jamming of false targets, and outperform the other tested beamformers across a wide range of signal-to-noise ratios.
Keywords
robust adaptive beamforming; LFM signal; fractional Fourier transform; INCM reconstruction
Speaker
Jian Lu
Rocket Force University of Engineering, China

Submission Author
Jian Lu Rocket Force University of Engineering, China
Jian Yang Xidian University, China
Xinxin Liu Rocket Force University of Engineering, China
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