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RSS FeedsRemote Sensing, Vol. 11, Pages 2158: Iterative Pointing Angle Calibration Method for the Spaceborne Photon-Counting Laser Altimeter Based on Small-Range Terrain Matching (Remote Sensing)

 
 

16 september 2019 17:02:14

 
Remote Sensing, Vol. 11, Pages 2158: Iterative Pointing Angle Calibration Method for the Spaceborne Photon-Counting Laser Altimeter Based on Small-Range Terrain Matching (Remote Sensing)
 


The satellite, Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) has been equipped with a new type of spaceborne laser altimeter, which has the benefits of having small footprints and a high repetition rate, and it can produce dense footprints on the ground. Focusing on the pointing angle calibration of this new spaceborne laser altimeter, this paper proposes a fast pointing angle calibration method using only a small range of terrain surveyed by airborne lidar. Based on the matching criterion of least elevation difference, an iterative pointing angle calibration method was proposed. In the experiment, the simulated photon-counting laser altimeter data and the Ice, Cloud and Land Elevation Satellite-2 data were used to verify the algorithm. The results show that when 1 km and 2.5 km lengths of track were used, the pointing angle error after calibration could be reduced to about 0.3 arc-seconds and less than 0.1 arc-seconds, respectively. Meanwhile, compared with the traditional pyramid search method, the proposed iterative pointing angle calibration method does not require well-designed parameters, which are important in the pyramid search method to balance calculation time and calibration result, and the iterative pointing angle calibration method could significantly reduce the calibration time to only about one-fifth of that of the pyramid search method.


 
266 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 11, Pages 2150: Quantitative Remote Sensing of Land Surface Variables: Progress and Perspective (Remote Sensing)
Remote Sensing, Vol. 11, Pages 2157: Multi-Sensor Geodetic Observations and Modeling of the 2017 Mw 6.3 Jinghe Earthquake (Remote Sensing)
 
 
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