基于壓縮感知的矩陣型聯(lián)合SAR成像與自聚焦算法
發(fā)布時間:2018-10-23 12:49
【摘要】:模型準(zhǔn)確情況下,壓縮感知在合成孔徑雷達(dá)成像中得到良好應(yīng)用;但在實際情況中,模型會存在一定誤差,這些誤差造成圖像偏離真實位置、引起散焦降低成像質(zhì)量.本文提出一種矩陣型聯(lián)合CS-SAR成像與自聚焦算法,該算法在CS-SAR成像重構(gòu)方法方面,基于光滑l_0范數(shù)方法提出了矩陣型正則化光滑l_0范數(shù)重構(gòu)方法,該方法具有較強(qiáng)容錯能力并能直接重構(gòu)矩陣型信號,能克服現(xiàn)有聯(lián)合CS-SAR成像與自聚焦算法在計算效率方面的缺陷.最后,通過仿真驗證了所提算法的有效性.
[Abstract]:Compression sensing is well applied in synthetic Aperture Radar (SAR) imaging when the model is accurate, but in practice, there will be some errors in the model, which cause the image to deviate from the real position and defocus to reduce the imaging quality. In this paper, a matrix type combined CS-SAR imaging and autofocus algorithm is proposed. In the aspect of CS-SAR reconstruction, a matrix regularized smooth l0-norm reconstruction method is proposed based on the smooth ls-stack norm method. This method has strong fault-tolerant ability and can directly reconstruct matrix signals. It can overcome the shortcomings of the existing joint CS-SAR imaging and self-focusing algorithms in computing efficiency. Finally, the effectiveness of the proposed algorithm is verified by simulation.
【作者單位】: 河北師范大學(xué)物理科學(xué)與信息工程學(xué)院;北京理工大學(xué)信息與電子學(xué)院;
【基金】:河北省高等學(xué)校自然科學(xué)重點項目(No.ZD2016031) 河北師范大學(xué)自然科學(xué)科研基金(No.L2016B06,No.L2010Y01)
【分類號】:TN957.52
本文編號:2289295
[Abstract]:Compression sensing is well applied in synthetic Aperture Radar (SAR) imaging when the model is accurate, but in practice, there will be some errors in the model, which cause the image to deviate from the real position and defocus to reduce the imaging quality. In this paper, a matrix type combined CS-SAR imaging and autofocus algorithm is proposed. In the aspect of CS-SAR reconstruction, a matrix regularized smooth l0-norm reconstruction method is proposed based on the smooth ls-stack norm method. This method has strong fault-tolerant ability and can directly reconstruct matrix signals. It can overcome the shortcomings of the existing joint CS-SAR imaging and self-focusing algorithms in computing efficiency. Finally, the effectiveness of the proposed algorithm is verified by simulation.
【作者單位】: 河北師范大學(xué)物理科學(xué)與信息工程學(xué)院;北京理工大學(xué)信息與電子學(xué)院;
【基金】:河北省高等學(xué)校自然科學(xué)重點項目(No.ZD2016031) 河北師范大學(xué)自然科學(xué)科研基金(No.L2016B06,No.L2010Y01)
【分類號】:TN957.52
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