标题： 基于嵌套阵列的少量观测TomoSAR成像新方法 显示英文标题

标题： A novel TomoSAR imaging method with few observations based on nested array

摘要： 合成孔径雷达层析成像（TomoSAR）基线优化技术能够降低系统复杂性并提高数据的时间相干性，在TomoSAR领域已成为一项重要研究。 本文提出了一种嵌套TomoSAR技术，将嵌套阵列引入TomoSAR作为基线配置。 该技术通过嵌套阵列获得均匀且连续的差分虚拟阵列，从而增加系统的自由度（DoF），并沿高程方向扩展虚拟孔径。 为了充分利用差分虚拟阵列，需要获取回波的协方差矩阵。 因此，我们提出了基于嵌套阵列的TomoSAR稀疏重建算法，利用自适应协方差矩阵估计算法在复杂场景下提升估计性能。 我们通过模拟和真实数据实验验证了所提方法的有效性。 与传统TomoSAR和Coprime TomoSAR相比，我们提出的方法具有更好的抗噪性能，并保留更多图像信息。 显示英文摘要

摘要： Synthetic aperture radar tomography (TomoSAR) baseline optimization technique is capable of reducing system complexity and improving the temporal coherence of data, which has become an important research in the field of TomoSAR. In this paper, we propose a nested TomoSAR technique, which introduces the nested array into TomoSAR as the baseline configuration. This technique obtains uniform and continuous difference co-array through nested array to increase the degrees of freedom (DoF) of the system and expands the virtual aperture along the elevation direction. In order to make full use of the difference co-array, covariance matrix of the echo needs to be obtained. Therefore, we propose a TomoSAR sparse reconstruction algorithm based on nested array, which uses adaptive covariance matrix estimation to improve the estimation performance in complex scenes. We demonstrate the effectiveness of the proposed method through simulated and real data experiments. Compared with traditional TomoSAR and coprime TomoSAR, the imaging results of our proposed method have a better anti-noise performance and retain more image information.