Abstract
Multipolarimetric synthetic aperture radar (SAR) interferometric phase optimization and phase series estimation have received a lot of attentions recently from the polarimetry SAR interferometry (PolInSAR) community. In this article, a maximum likelihood estimation (MLE) method for the interferometric coherence matrix (ICM) is proposed, which is further applied to both interferometric phase optimization and phase series estimation. By modeling the PolInSAR coherence matrix as the Kronecker product of the polarimetric coherence matrix and ICM, the MLE of ICM under complex circular Gaussian distribution hypothesis is acquired through an alternate iterative optimization method. In addition, it is theoretically proved in this article that the two state-of-the-art methods, i.e., the TP (total power) method and the MLE-MPPL method, are suboptimal compared to the proposed method regarding the MLE of ICM. Numerical experiments are conducted on simulated fully polarimetric data, airborne fully polarimetric E-SAR data, and spaceborne dual polarimetric Sentinel-1A data, to confirm the effectiveness and superiority of the proposed method.
Original language | English |
---|---|
Pages (from-to) | 10007-10021 |
Number of pages | 15 |
Journal | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Volume | 16 |
DOIs | |
Publication status | Published - Oct 2023 |
Keywords
- Interferometric coherence matrix (ICM)
- interferometric phase optimization
- maximum likelihood estimation (MLE)
- phase series estimation
- PolInSAR
ASJC Scopus subject areas
- Computers in Earth Sciences
- Atmospheric Science