Geometric Continuity-Constrained SAR Tomography for Sparse Array InSAR Acquisitions

Synthetic aperture radar tomography (TomoSAR) is a standard tool for 3-D radar imaging, which overcomes the limitation of 2-D geometric distortion by using the baseline diversity. Conventional multibaseline SAR data acquired by repeat-pass spaceborne SAR missions requires a long waiting time. The new airborne array-SAR interferometry (InSAR) system can acquire multibaseline images in a single flight, significantly improving the practical capability of SAR-based 3-D reconstruction. However, the array InSAR system with many channels is very complex. The performance of existing algorithms decreases significantly with such a sparse acquisition. This article proposes a geometric continuity-constrained (GCC) TomoSAR algorithm to improve the performance of 3-D radar imaging with a few acquisitions. First, the relationship between spectrum correlation and geometry continuity is investigated. Then an implicit-GCC is proposed to optimize the 2-D radar spectrum in either range-elevation or azimuth-elevation domain. Additionally, assuming two typical overlaid patterns in an urban area, an explicit GCC is further developed to achieve a geometry-based overlay unmixing. The main advantage of the proposed method is the use of geometric continuity between neighboring pixels without an additional approach for extracting prior geometric information. The experimental results by real data show that the proposed GCC TomoSAR significantly improves the performance of 3-D reconstruction with only three-pass array InSAR images.