Assessment of ICESat-2’s Horizontal Accuracy Using Precisely-Surveyed Terrains in McMurdo Dry Valleys, Antactica

This paper presents an assessment of the horizon-tal accuracy and precision of the laser altimetry observations collected by NASA's ICESat-2 mission. We selected the terrain-matching method to determine the position of laser altimeter profiles within a precisely knownn surface, represented by a DEM. We took this classical approach a step further, approx-imated the DEM by planar surfaces and calculated the optimal position of the laser profile by minimizing the square sum of the elevation differences between reference DEMs and ICESat-2 profiles. We found the highly accurate DEMs of the McMurdo Dry Valleys, Antarctica, ideal for this research because of their stable landscape and rugged topography. We computed the 3D shift parameters of 379 different laser altimeter profiles along two reference ground tracks collected within the first two years of the mission. Analyzing these results revealed a total geolocation error (mean + 1 sigma) of 4.93 m for release 3 and 4.66 m for release 4 data. These numbers are the averages of the six beams, expressed as mean + 1 sigma and lie well within the mission requirement of 6.5 m.

Assessment of ICESat-2’s Horizontal Accuracy Using Precisely-Surveyed Terrains in McMurdo Dry Valleys, Antactica

This paper presents an assessment of the horizon-tal accuracy and precision of the laser altimetry observations collected by NASA's ICESat-2 mission. We selected the terrain-matching method to determine the position of laser altimeter profiles within a precisely knownn surface, represented by a DEM. We took this classical approach a step further, approx-imated the DEM by planar surfaces and calculated the optimal position of the laser profile by minimizing the square sum of the elevation differences between reference DEMs and ICESat-2 profiles. We found the highly accurate DEMs of the McMurdo Dry Valleys, Antarctica, ideal for this research because of their stable landscape and rugged topography. We computed the 3D shift parameters of 379 different laser altimeter profiles along two reference ground tracks collected within the first two years of the mission. Analyzing these results revealed a total geolocation error (mean + 1 sigma) of 4.93 m for release 3 and 4.66 m for release 4 data. These numbers are the averages of the six beams, expressed as mean + 1 sigma and lie well within the mission requirement of 6.5 m.

A Fast Selection Method of Landmarks for Terrain Matching Navigation

Under fixed imaging conditions, the landmark selection method based feature traversal analysis has high computational complexity. The hierarchical statistical significance detection method uses global statistical information for feature analysis to overcome the computational complexity problem caused by feature traversal analysis. The frequency domain de-correlation method can remove repeat mode in the image by adaptive Gaussian filtering on the amplitude-frequency characteristics. In this paper, combined the hierarchical statistical saliency detection method with the frequency domain de-correlation method, a fast landmark selection algorithm based on saliency analysis is proposed. Based on the proposed algorithm, the automatic landmark selection architecture for terrain matching navigation was constructed. The selection of landmark points was carried out in the Qin-ling Mountains and the Guangdong and Guangxi hills. The results show that compared with the feature or pixel-based landmark selection method, the landmark selection efficiency of the proposed method is improved by 2 to 3 orders of magnitude. The correct matching rate of candidate landmarks selected in the Qinling Mountains and the Guangdong and Guangxi hills are 73.9% and 88.3% respectively.

Iterative Pointing Angle Calibration Method for the Spaceborne Photon-Counting Laser Altimeter Based on Small-Range Terrain Matching

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.