DNCNet: Deep radar signal denoising and recognition
… propose an efficient denoising and classification network (DNCNet) for radar signals. The
DNCNet consists of denoising and classification subnetworks. First, a radar signal detection …
DNCNet consists of denoising and classification subnetworks. First, a radar signal detection …
A time-frequency image denoising method via neural networks for radar waveform recognition
Z Hu, J Huang, D Hu, Z Wang - IEEE Communications Letters, 2022 - ieeexplore.ieee.org
… denoising method to improve the accuracy of radar waveform recognition under low SNR.
The proposed method … transform time-domain signals into denoised spectrums. Then the DFT …
The proposed method … transform time-domain signals into denoised spectrums. Then the DFT …
Radar image series denoising of space targets based on Gaussian process regression
X Bai, X Peng - IEEE Transactions on Geoscience and Remote …, 2019 - ieeexplore.ieee.org
… , this paper proposes a novel method for image series denoising based on Gaussian process
… Finally, we obtain the denoised inverse synthetic aperture radar (ISAR) image series by …
… Finally, we obtain the denoised inverse synthetic aperture radar (ISAR) image series by …
MST radar signal processing using wavelet-based denoising
SR Thatiparthi, RR Gudheti… - IEEE Geoscience and …, 2009 - ieeexplore.ieee.org
… (FFT) technique for power spectral estimation and “adaptive estimates technique” for
estimating the moments of radar data has been proposed in [3]. This method considers a certain …
estimating the moments of radar data has been proposed in [3]. This method considers a certain …
Detrending technique for denoising in CW radar
… technique that can compensate for the effect of DC drift is proposed to improve the phase-detection
accuracy of the circle fitting method in CW radars. The proposed technique models …
accuracy of the circle fitting method in CW radars. The proposed technique models …
Application of denoising CNN for noise suppression and weak signal extraction of lunar penetrating radar data
H Zhou, X Feng, Z Dong, C Liu, W Liang - Remote Sensing, 2021 - mdpi.com
… The denoising CNN model … , the denoising CNN framework is applied to CE-4 LPR data
filtering. The low-frequency clutters used in the CNN training are extracted from CE-3 LPR data …
filtering. The low-frequency clutters used in the CNN training are extracted from CE-3 LPR data …
Survey and Fundamental Implementation of Denoising Techniques for Radar Signal Processing
D Chande, A Manale, D Jangale, R Yerram - … for Intelligent Systems, 2024 - Springer
… In conclusion, this survey of denoising techniques for radar signal processing highlights
three key methods: Complex Wavelets (CWT), Multi-Band Wavelet Transform with Improved …
three key methods: Complex Wavelets (CWT), Multi-Band Wavelet Transform with Improved …
Inpainting Radar Missing Data via Denoising Iterative Restoration
W Zhang, X Zhang, Z Jin, Y Wen… - IEEE Journal of Selected …, 2024 - ieeexplore.ieee.org
… a method for radar data … radar data in various scenarios. We performed experiments in the
central region of the United States using seamlessly blended scanning reflectivity radar data …
central region of the United States using seamlessly blended scanning reflectivity radar data …
Denoising complex background radar signals based on wavelet decomposition thresholding
F Qiu, K Yuan - Applied Mathematics and Nonlinear Sciences, 2024 - sciendo.com
… wavelet threshold denoising methods are applied to denoise the … The denoising methods
for radar signals using the properties … threshold denoising methods have wide adaptability. …
for radar signals using the properties … threshold denoising methods have wide adaptability. …
Two-stage Denoising of Ground Penetrating Radar Data based on Deep Learning.
M Hu, X Liu, Q Lu, S Liu - IEEE Geoscience and Remote …, 2024 - ieeexplore.ieee.org
… In this letter, we propose a two-stage denoising method for GPR data based on the super-resolution
concept of convolutional neural networks, aiming to suppress noise and enhance …
concept of convolutional neural networks, aiming to suppress noise and enhance …
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