The prevalent imaging method in inverse synthetic aperture radar (ISAR) system is range-Doppler (RD) method, which is implemented by the fast Fourier transformation (FFT). FFT is computationally efficient, but it comes with a price – the problems of wide main-lobes and high side-lobes, especially under the sparse apertures condition. In addition, the resolution of RD method is determined by the radar parameters, which poses limitation to super-resolution imaging, multi-tasking and cognitive reconfigurable applications. In this study, the authors propose a novel super-resolution ISAR imaging method based on the total least squares-estimation of signal parameters via rotational invariance technique (TLS-ESPRIT). The locations and intensities of the scatterers are obtained by employing the ESPRIT algorithm and the least squares technique. Then the ISAR image is formulated, having circumvented all of the above-mentioned limitations. Experiments based on simulated and real measured data validate the effectiveness of the proposed method.

中文翻译：

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TLS-ESPRIT技术的新型稀疏孔径ISAR成像算法

逆合成孔径雷达（ISAR）系统中普遍使用的成像方法是距离多普勒（RD）方法，它是通过快速傅里叶变换（FFT）实现的。FFT计算效率高，但要付出代价–主瓣偏宽和旁瓣偏高的问题，尤其是在稀疏孔径条件下。此外，RD方法的分辨率由雷达参数确定，这限制了超分辨率成像，多任务处理和认知可重构应用。在这项研究中，作者提出了一种新颖的超分辨率ISAR成像方法，该方法基于通过旋转不变技术（TLS-ESPRIT）进行的信号参数的总最小二乘估计。散射体的位置和强度是通过使用ESPRIT算法和最小二乘技术获得的。然后，规避了所有上述限制，制定了ISAR图像。基于模拟和真实测量数据的实验验证了该方法的有效性。