Work

Fast Phase Estimation Approach for Distributed Scatterer Based on Power Method

Year: 2025

Type: article

Abstract: Distributed scatterer (DS) possesses a medium signal-to-noise ratio (SNR), and its interferometric phase is typically estimated from sample covariance matrix (SCM) using phase linking (PL) algorithm. However, the phase estimation of DS is very time consuming. The eigenvalue decomposition (EVD) methods benefit from highly optimized eigen-decomposition libraries and therefore have a higher computational efficiency. Nevertheless, EVD methods are still insufficient due to the massive data provided by modern SAR satellites with multi-polarizations and high spatio-temporal resolution. The essence of conventional EVD methods is to decompose the SCM (or modified SCM) with a series of eigenvalue-eigenvector pairs and then select only the eigenvector corresponding to the largest eigenvalue as the optimal estimate. Inspired by that, we proposed a fast phase estimation approach based on power method (PM), a straightforward algorithm that approximates the largest eigenvalue and its associated eigenvector. The convergence rate of PM depends on the ratio between the second and the first largest eigenvalue, i.e., λ2/λ1. We demonstrate that there is an intrinsic correlation between λ2/λ1and the traditional quality measure (γPTA). Based on this correlation, we design two termination criteria for PM to enable fast and accurate phase estimation. Experiments with simulated and real SAR data demonstrate that PM achieves comparable phase estimation accuracy to EVD but is 3–6 times faster. Additionally, we compare the computational efficiency and accuracy of EVD, PM, and the eigendecomposition-based maximum likelihood estimator of interferometric phase (EMI), providing practical guidance for different application scenarios.

Source: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

DOI: 10.1109/jstars.2025.3569847

Authors: Chuanguang Zhu, Yangqi Gao, Liya Zhang, Mengguang Liao, Wenhao Wu

Institution: Hunan University of Science and Technology

Language: English

Topic: Synthetic Aperture Radar (SAR) Applications and Techniques

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,800

Funders: National Natural Science Foundation of China, Natural Science Foundation of Hunan Province