互质层析SAR最少航过数量估计方法

在层析SAR技术的实际应用中，航过数量通常受高昂成本等因素的限制。互质层析SAR技术通过稀疏分布航过位置、延长基线孔径长度，可以降低所需的航过数量。当采用子空间方法开展互质层析SAR重构处理时，为了获得可靠的层析图，研究最少航过数量估计问题。考虑到子空间方法的重构性能受多个参数的影响，因此航过数量的选择必须综合考虑所有相关参数对重构结果的影响。为此，通过样本特征值分析方式建立子空间方法的可靠性保证条件。根据这个可靠性保证条件，提出了一种估计最少航过数量的方法。与传统的最少航过数量估计方法相比，所提方法的优势在于：同时考虑所有的相关参数，且具有解析的数学描述式。最后，仿真实验证实由所提方法估算的航过数量确实接近最小，且能够保证重构结果可靠。

Estimation of the Minimum Number of Acquisitions for Coprime Tomographic Synthetic Aperture Radar

In the practical application of Tomographic Synthetic Aperture Radar (TomoSAR), the number of acquisitions is usually restricted due to their expensive cost. A coprime TomoSAR technique was proposed to reduce the required number of acquisitions by sparsely distributing acquisitions and elongating baseline aperture. To guarantee a reliable tomogram, this study aims to determine the minimum number of acquisitions for the coprime TomoSAR when adopting a subspace method for performing the tomographic reconstruction. However, the performance of the subspace method depends on multiple parameters. In light of this, the selection of acquisition times has to comprehensively weigh the effects of all these parameters on the reconstruction performance. To this end, a prerequisite for reliable reconstruction is established by quantifying the relationship between the sample eigenvalues and all related parameters. Compared with conventional estimation approaches for the minimum number of acquisitions, the proposed approach has twofold advantages of containing all related parameters and of having a closed-form expression. Finally, the simulation experiments verify that the number of acquisitions estimated by our approach is close to the minimum and can guarantee reconstruction reliability.