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RESEARCH ON AIRBORNE SAR IMAGING BASED ON ESC ALGORITHM
- Source :
- The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-2-W7, Pp 601-604 (2017)
- Publication Year :
- 2017
- Publisher :
- Copernicus Publications, 2017.
-
Abstract
- Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS) data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC). In this paper, extend chirp scaling algorithm (ECS) is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR) effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.
Details
- Language :
- English
- ISSN :
- 16821750 and 21949034
- Volume :
- XLII-2-W7
- Database :
- Directory of Open Access Journals
- Journal :
- The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.0a096af73e3c4eb38edbf7a6e7f80c54
- Document Type :
- article
- Full Text :
- https://doi.org/10.5194/isprs-archives-XLII-2-W7-601-2017