Saima Yasmeen¹, Muhammad Usman Yaseen^1,*, Syed Sohaib Ali², Moustafa M. Nasralla³, Sohaib Bin Altaf Khattak³

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3671-3689, 2023, DOI:10.32604/cmc.2023.041195 - 08 October 2023

Abstract SAR images commonly suffer from speckle noise, posing a significant challenge in their analysis and interpretation. Existing convolutional neural network (CNN) based despeckling methods have shown great performance in removing speckle noise. However, these CNN-based methods have a few limitations. They do not decouple complex background information in a multi-resolution manner. Moreover, they have deep network structures that may result in many parameters, limiting their applicability to mobile devices. Furthermore, extracting key speckle information in the presence of complex background is also a major problem with SAR. The proposed study addresses these limitations by introducing… More >

Liguo Zhang^1,2, Zilin Tian¹, Yan Zhang^3,*, Tong Shuai⁴, Shuo Liang⁴, Zhuofei Wu⁵

Journal of New Media, Vol.4, No.2, pp. 59-71, 2022, DOI:10.32604/jnm.2022.029360 - 13 June 2022

Abstract In recent years, deep learning algorithms have been popular in recognizing targets in synthetic aperture radar (SAR) images. However, due to the problem of overfitting, the performance of these models tends to worsen when just a small number of training data are available. In order to solve the problems of overfitting and an unsatisfied performance of the network model in the small sample remote sensing image target recognition, in this paper, we uses a deep residual network to autonomously acquire image features and proposes the Deep Feature Bayesian Classifier model (RBnet) for SAR image target… More >

Qi Chen, Wei Cui^*, Jianqiu Sun, Xingguang Li, Xuyu Tian

Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 115-126, 2021, DOI:10.32604/iasc.2021.011617 - 07 January 2021

Abstract The existing range-Doppler algorithms for SAR imaging are affected by a fast-time Doppler effect so they cannot be directly applied to FMCW SAR. Moreover, range migration is more evident in squint mode. To reveal the influence of the continuous motion of FMCW SAR in the squint mode on the echo signal and optimize the imaging process, an improved range-Doppler algorithm is based on squint FMCW SAR imaging is proposed in this paper. Firstly, the imaging geometry model and echo signal model of FMCW SAR are analyzed and deduced. The problem of Doppler center offset under… More >

Zhenli Wang^{1, *}, Qun Wang¹, Jiayin Liu¹, Zheng Liang¹, Jingsong Xu²

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2351-2363, 2020, DOI:10.32604/cmc.2020.011909 - 16 September 2020

Abstract To address the low-resolution imaging problem in relation to traditional Range Doppler (RD) algorithm, this paper intends to propose a new algorithm based on Fractional Fourier Transform (FrFT), which proves highly advantageous in the acquisition of high-resolution Synthetic Aperture Radar (SAR) images. The expression of the optimal order of SAR range signals using FrFT is deduced in detail, and the corresponding expression of the azimuth signal is also given. Theoretical analysis shows that, the optimal order in range (azimuth) direction, which turns out to be very unique, depends on the known imaging parameters of SAR, More >

Zhenli Wang^{1, *}, Qun Wang¹, Fujuan Li¹, Shuai Wang²

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1533-1543, 2020, DOI:10.32604/cmc.2020.09721 - 30 April 2020

Abstract The traditional Range Doppler (RD) algorithm is unable to meet practical needs owing to the limit of resolution. The order of fractional Fourier Transform (FrFT) and the length of sampling signals affect SAR imaging performance when FrFT is applied to RD algorithm. To overcome the above shortcomings, the purpose of this paper is to propose a high-resolution SAR image algorithm by using the optimal order of FrFT and the sample length constraints for the range direction. The expression of the optimal order of SAR range signals via FrFT is deduced in detail. The initial sample More >

Y,ong Gao¹, Shubi Zhang^1,*, Kefei Zhang^2,*, Shijin Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.2, pp. 349-363, 2019, DOI:10.32604/cmes.2019.03943

Abstract Interferometric phase filtering is one of the key steps in interferometric synthetic aperture radar (InSAR/SAR). However, the ideal filtering results are difficult to obtain due to dense fringe and low coherence regions. Moreover, the InSAR/SAR data range is relatively large, so the efficiency of interferential phase filtering is one of the major problems. In this letter, we proposed an interferometric phase filtering method based on an amended matrix pencil and linear window mean filter. The combination of the matrix pencil and the linear mean filter are introduced to the interferometric phase filtering for the first… More >