A Higher-Order Singular Value Decomposition-Based Radio Frequency Interference Mitigation Method on High-Frequency Surface Wave Radar

2020 ◽  
Vol 58 (4) ◽  
pp. 2770-2781 ◽  
Author(s):  
Yuhuan Li ◽  
Xianchang Yue ◽  
Xiongbin Wu ◽  
Lan Zhang ◽  
Qing Zhou ◽  
...  
Keyword(s):  
Surface Wave ◽  
Singular Value Decomposition ◽  
Radio Frequency ◽  
High Frequency ◽  
Interference Mitigation ◽  
Higher Order ◽  
Singular Value ◽  
Radio Frequency Interference ◽  
Wave Radar ◽  
Value Decomposition

scholarly journals Fractional Fourier Transform-Based Radio Frequency Interference Suppression for High-Frequency Surface Wave Radar

2019 ◽  
Vol 12 (1) ◽  
pp. 75
Author(s):  
Qing Zhou ◽  
Hong Zheng ◽  
Xiongbin Wu ◽  
Xianchang Yue ◽  
Zhangyou Chen ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Surface Wave ◽  
Radio Frequency ◽  
Orthogonal Projection ◽  
Carrier Frequency ◽  
High Frequency ◽  
Fractional Fourier Transform ◽  
Fourier Domain ◽  
Radio Frequency Interference ◽  
Wave Radar

High-frequency surface wave radar (HF SWR) plays an important role in marine stereoscopic monitoring system. Nevertheless, the congestion of external radio frequency interference (RFI) in HF band degrades its performance seriously. In this article, two novel fractional Fourier transform (FRFT)-based RFI suppression approaches are proposed. One is based on the orthogonal projection of sequences from fractional Fourier domain, and the other is based on singular value decomposition (SVD) of Hankel matrix of sequences from fractional inverse-Fourier domain. Simulation and experimental data collected by HF SWR from Wuhan University were used to test the effectiveness as well as the application condition of the proposed RFI suppression algorithms. The FRFT-based orthogonal projection algorithm is practicable for suppressing stationary RFI with unvaried carrier frequency, while the FRFT-based SVD algorithm is applicable equally for mitigating nonstationary RFI with time-varying carrier frequency or occasional duration time. The processing results may provide useful guidelines for interference suppression of HF SWR, and inspiring the further application of the FRFT-based methods for signal processing.

scholarly journals An Image Denoising Method with Enhancement of the Directional Features Based on Wavelet and SVD Transforms

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Min Wang ◽  
Zhen Li ◽  
Xiangjun Duan ◽  
Wei Li
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Image Denoising ◽  
High Frequency ◽  
Low Frequency ◽  
Singular Value ◽  
Denoising Method ◽  
Diagonal Part ◽  
Value Decomposition ◽  
Image Part

This paper proposes an image denoising method, using the wavelet transform and the singular value decomposition (SVD), with the enhancement of the directional features. First, use the single-level discrete 2D wavelet transform to decompose the noised image into the low-frequency image part and the high-frequency parts (the horizontal, vertical, and diagonal parts), with the edge extracted and retained to avoid edge loss. Then, use the SVD to filter the noise of the high-frequency parts with image rotations and the enhancement of the directional features: to filter the diagonal part, one needs first to rotate it 45 degrees and rotate it back after filtering. Finally, reconstruct the image from the low-frequency part and the filtered high-frequency parts by the inverse wavelet transform to get the final denoising image. Experiments show the effectiveness of this method, compared with relevant methods.

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