Temporal decorrelation is one of the major problems in synthetic aperture radar (SAR) tomography (TomoSAR) of a natural environment that leads to blurring and spreading in focused image space. In the context of spatiotemporal focusing using the multi-temporal multi-baseline (MB) SAR data, a model-based differential TomoSAR is employed. Along this and with the aim of temporal decorrelation-robust focusing, a differential tomography framework based on generalized Capon estimator is investigated. The method can cope with temporal decorrelation of the distributed environment by spatiotemporal focusing with optimal bandwidth of the distributed signal. In addition, the method employs an additional parameter for coherence channel balancing in the model of generalized Capon that benefits from it in characterizing the spatiotemporal backscattering by mitigating the inconsistency between channels. The analysis is performed with a realistic simulation of temporal decorrelation in the presence of different decorrelation sources and taking into account the dependence on the vertical structure of the forested area. Effectiveness of the proposed framework has been assessed on both simulated and real data sets by evaluation and characterization of the canopy and under foliage ground in terms of deviation between the estimated covariance matrix and one of the generalized TomoSAR models.
|Number of pages||10|
|Journal||IEEE transactions on geoscience and remote sensing|
|Publication status||Published - 25 Jul 2019|