Homa AnsariFrancesco De ZanRichard Bamler
Signal decorrelation poses a limitation to multipass SAR interferometry. In pursuit of overcoming this limitation to achieve high-precision deformation estimates, different techniques have been developed; with SBAS, SqueeSAR and CAESAR as the overarching schemes. These different analysis approaches raise the question of their efficiency and limitation in phase and consequently deformation estimation. This contribution firstly addresses this question and secondly proposes a new estimator with improved performance. Called Eigendecomposition based Maximum-likelihood-estimator of Interferometric phase (EMI), the proposed estimator combines the advantages of the state-of-the-art techniques. Identical to CAESAR, EMI is solved using Eigendecomposition; it is therefore computationally efficient and straightforward in implementation. Similar to SqueeSAR, EMI is a maximum-likelihood-estimator; hence it retains estimation efficiency. The computational and estimation efficiency of EMI renders it as an optimum choice for phase estimation. A further marriage of EMI with the proposed Sequential Estimator of [1] provides an efficient processing scheme tailored to the analysis of Big InSAR Data. EMI is formulated and verified in relation to the state-of-the-art approaches via mathematical formulation, simulation analysis and experiments with time series of Sentinel-1 data over the volcanic island of Vulcano, Italy.
G. FornaroAntonio PauciulloDiego Reale
Sami Samiei-EsfahanyRamon F. Hanssen
Kui ZhangZhengzhou LiGuojie MengYaqiong Dai
Pietro GuccioneAndrea Monti GuarnieriStefano Tebaldini