Abstract
Indian Space Research Organisation’s Radar Imaging Satellite (RISAT) -1 was the first Synthetic Aperture Radar (SAR) satellite equipped with the compact polarimetric (CP) mode for data acquisition. To exploit the advantages offered by the CP mode, the datasets need to be polarimetrically calibrated. The polarimetric calibration procedure estimates the polarimetric distortions in the datasets caused due to channel imbalance, crosstalk, and Faraday rotation. These polarimetric distortions cause the misinterpretation of the ground targets in the polarimetric decomposition techniques. The Freeman compact-pol polarimetric calibration algorithm is the most commonly used algorithm. In this study, the RISAT-1 Circular Transmit Linear Receive (CTLR) dataset of the RISAT Cal Val site was used to estimate the polarimetric distortion parameters and these distortion parameters were used to polarimetrically calibrate the RISAT-1 CTLR dataset of the Doon Valley region, Uttarakhand, India. The Cloude compact-pol decomposition algorithm was used to evaluate the ground target characterization accuracy before and after polarimetric calibration using the Freeman compact-pol polarimetric calibration algorithm. Before polarimetric calibration, urban targets were showing surface scattering behavior and river channels were showing increased double-bounce scattering behavior. After polarimetric calibration, the urban targets showed dominance in double-bounce scattering and river channels showed dominance in surface scattering as per the theory.
Highlights
In the compact polarimetry (CP) synthetic aperture radar system architecture, only one polarization of electromagnetic wave is transmitted, which is a combination of equal weighted horizontal and vertical polarizations [1]
This study focuses on the estimation and minimization of polarimetric distortions in the RISAT1 compact-pol fine resolution Stripmap (FRS) dataset using the external polarimetric calibration techniques with the help of polarimetric distortion parameters estimated from the trihedral and dihedral corner reflectors deployed at the Synthetic Aperture Radar (SAR) calibration and validation site in India
By analyzing the Google Earth image of the study area shown in Figure 2 and the polarimetrically calibrated False Color Composite (FCC) composite shown in Figure 4, it can be observed that the dry river beds and the water channels appear in the blue color, indicating odd bounce scattering behavior; the urban structures appear in red color, indicating dominance of the double bounce scattering component, and a decrease in volume scattering and increase in double-bounce scattering behavior can be observed at the less dense vegetated areas
Summary
In the compact polarimetry (CP) synthetic aperture radar system architecture, only one polarization of electromagnetic wave is transmitted, which is a combination of equal weighted horizontal and vertical polarizations [1]. The polarimetric SAR data is useful in understanding the different scattering mechanisms happening on the Earth’s surface from different types of targets using the phase and amplitude information from the different polarization channels data with the help of polarimetric decomposition and classification techniques [5]. The polarimetric distortion in the Polarimetric Synthetic Aperture Radar (PolSAR) datasets causes the polarimetric decomposition and classification techniques to produce wrong outputs, which result in misinterpreting of the scattering phenomenon and ground targets. The channel imbalance, phase bias, and crosstalk are the various types of polarimetric distortions caused due to the system non-idealities and the Faraday rotation error is the polarimetric distortion induced due to the atmosphere, which is more dominant for lowfrequency SAR systems operating in the L-band and P-band [6]
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