Improved Maximum Likelihood Estimation for Optimal Phase History Retrieval of Distributed Scatterers in InSAR Stacks

Autor: Changjun Zhao, Zhen Li, Ping Zhang, Bangsen Tian, Shuo Gao
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: IEEE Access, Vol 7, Pp 186319-186327 (2019)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2019.2961154
Popis: Distributed scatterer (DS) decorrelation poses a challenge to multibaseline SAR interferometry. To overcome this challenge, the SqueeSAR retrieves an optimal phase time-series using a maximum likelihood estimation (MLE) method, which has been commonly used due to its remarkable effect. Unfortunately, however, the MLE's performance is compromised for various reasons, such as inaccurate statistically homogeneous pixels (SHPs) and the bias in the estimator used. In this paper, we present an approach aiming to improve the MLE's performance. The proposed approach includes the employment of the Kullback-Leibler divergence to realize more accurate SHP selection and the use of the second kind statistical estimator to mitigate the coherence bias. The performance of the conventional MLE is significantly improved by the proposed approach, making it close to its optimal performance. The experimental results on both simulated and real TerraSAR-X data demonstrate the improvements of the proposed approach with respect to the conventional MLE.
Databáze: Directory of Open Access Journals