A Polarization Stacking Method for Optimizing Time-Series Interferometric Phase of Distributed Scatterers

DOI码：10.3390/rs14174168

发表刊物：Remote Sensing

关键字：time-series InSAR (TSInSAR); polarimetric optimization; total power (TP) coherency matrix; phase linking (PL); stacking; Cramer–Rao lower bound (CRLB); equivalent number of looks (ENL)

摘要：For time-series interferometric phases optimization of distributed scatterers (DSs), the SqueeSAR technology used the phase linking (PL) to extract the equivalent single-master (ESM) interferometric phases from the multilooking time-series coherence matrix. The Cramer–Rao lower bound (CRLB) for the PL describes the highest achievable estimation accuracy of the ESM phases, which depends on the number of looks and the time-series coherence magnitude matrix. With the abundance of time-series polarimetric SAR data, many scholars have studied the coherence magnitude-based polarimetric optimization methods for optimizing the DS’s time-series interferometric phases, for example, the widely-used exhaustive search polarimetric optimization (ESPO) algorithm. However, the traditional polarimetric optimization methods select the boundary extremums of the coherence region (CR) as the optimized complex coherence, which is usually biased from the free-noise one. Currently, in the polarimetric InSAR (PolInSAR) technology, Shen et al. innovatively considered polarimetric information as statistical samples and proposed the total power (TP) coherency matrix construction method for increasing the number of looks and reducing the interferometric phase noise. Therefore, to optimize the time-series interferometric phases for DS, this paper proposes performing a polarization stacking and extending the PolInSAR TP construction to the time-series PolInSAR (TSPolInSAR) data configuration, called the time-series TP (TSTP) method. Simulated and real experiments prove that the new TSTP construction method has better performance and higher efficiency than the single polarimetric and the traditional ESPO algorithms.

合写作者：Hu Jun

论文类型：期刊论文

通讯作者：Wang Changcheng

学科门类：工学

文献类型：J

卷号：14

期号：17

页面范围：4168

是否译文：否

发表时间：2022-08-25

收录刊物：SCI

发布期刊链接：https://www-mdpi-com-s.vpn.whu.edu.cn/2072-4292/14/17/4168