Noise impairs the performance of inverse synthetic aperture radar (ISAR) motion compensation, which induces severe defocusing under low signal-to-noise ratio environments. To overcome this issue, a novel similarity-oriented (SO) method with a two-domain denoising strategy is proposed. A PIxEl similarity-oriented (PIE-SO) denoising method designed for range-Doppler (RD) domain and a modified RAnge Profile Similarity-Oriented (RAP-SO) denoising method designed for high-resolution range profile (HRRP) matrix are included in the presented framework. Firstly, the PIE-SO method directly performs a two-dimensional fast Fourier transform on dechirp processed echo data to form a coarsely focusing ISAR image in the RD domain. Then the focusing image is separated from the noise background by virtue of pixel similarity, after which the noise is preliminarily removed. Subsequently, the coarsely denoised image is transformed into the HRRP matrix. Considering the range profile similarity impaired by noise is restored by the PIE-SO denoising, a Laplacian regularised-weighted nuclear norm proximal (LR-WNNP) operator is proposed. The proposed modified RAP-SO method, that is, the LR-WNNP operator, exploits the low-rank property of the HRRP matrix and the local similarity of adjacent HRRPs to reduce the residual noise. As a result, ISAR imaging quality is significantly improved. Comprehensive experiments illustrate the effectiveness and superiority of the presented method.

中文翻译：

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面向相似性的低信噪比反合成孔径雷达成像方法

噪声会损害逆合成孔径雷达（ISAR）运动补偿的性能，从而在低信噪比环境下引起严重的散焦。为了克服这个问题，提出了一种具有两域去噪策略的新型相似性导向（SO）方法。为距离多普勒（RD）域设计的PIxEl相似性导向（PIE-SO）去噪方法和为高分辨率距离剖面（HRRP）矩阵设计的改进的RANge剖面相似性导向（RAP-SO）去噪方法包含在所提出的框架。首先，PIE-SO方法直接对去线性调频处理后的回波数据进行二维快速傅里叶变换，形成RD域的粗聚焦ISAR图像。然后利用像素相似度将聚焦图像与噪声背景分离，初步去除噪声。随后，粗略去噪的图像被转换成HRRP矩阵。考虑到PIE-SO去噪可以恢复受噪声影响的距离剖面相似性，提出了拉普拉斯正则加权核范数近端（LR-WNNP）算子。所提出的改进的RAP-SO方法，即LR-WNNP算子，利用HRRP矩阵的低秩特性和相邻HRRP的局部相似性来减少残留噪声。结果，ISAR成像质量显着提高。综合实验验证了该方法的有效性和优越性。