LAUSR

Multitemporal synthetic aperture radar interferometry (MT-InSAR) is able to reconstruct a 3-D surface model with high precision but requires a long waiting time to get the multibaseline synthetic aperture radar (SAR) images. The array InSAR system can acquire multibaseline images in a single flight, which significantly improves the practical capability of 3-D reconstruction. However, the array InSAR system with many channels has very high complexity in both system and processing because of cross-channel calibration and decoupling. Thus, reducing the number of channels requires the investigation of the 3-D reconstruction algorithm to be suitable for sparse array InSAR images. This work proposed an asymptotic 3-D phase unwrapping (PU) algorithm for 3-D reconstruction using sparse array InSAR images, i.e., as few as three or four channels. A 2-D (space) + 1-D (baseline) PU framework is developed to improve the reliability of the 3-D PU, and a novel asymptotic strategy is proposed for the combination of the short–long baseline interferogram. Using successful unwrapping (SU) criteria, the bounds of the possible baseline combinations and the expected minimal coherence are derived, respectively. The main advantage of the proposed algorithm is the reliable PU with very sparse channels and an analysis of the possible baseline combinations. The experimental results by both the simulated and real data show that the proposed method can achieve a 3-D reconstruction using only three-pass array InSAR images and optimize the baseline design for the array InSAR system.