Geometric Calibration Using Stellar Sources in Earth Observation Satellite

Kim, Hee-Seob; Kim, Eunghyun; Chung, Dae-Won; Seo, Doochun

doi:10.2322/tjsass.52.104

Cited by 2 publications

(1 citation statement)

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“…Additionally, being independent of GCPs, star-based geometric calibration, unaffected by the eclipse and interfering daylight, is also a promising and effective method [ 39 ]. Kim et al [ 40 ] proposed a geometric calibration using stellar sources in an earth observation satellite, which can help monitor the geographic location accuracy of satellite images. In addition, numerical simulation verified the effectiveness of the method.…”

Section: Introductionmentioning

confidence: 99%

On-Orbit Geometric Calibration from the Relative Motion of Stars for Geostationary Cameras

Jiang

et al. 2021

Sensors

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Affected by the vibrations and thermal shocks during launch and the orbit penetration process, the geometric positioning model of the remote sensing cameras measured on the ground will generate a displacement, affecting the geometric accuracy of imagery and requiring recalibration. Conventional methods adopt the ground control points (GCPs) or stars as references for on-orbit geometric calibration. However, inescapable cloud coverage and discontented extraction algorithms make it extremely difficult to collect sufficient high-precision GCPs for modifying the misalignment of the camera, especially for geostationary satellites. Additionally, the number of the observed stars is very likely to be inadequate for calibrating the relative installations of the camera. In terms of the problems above, we propose a novel on-orbit geometric calibration method using the relative motion of stars for geostationary cameras. First, a geometric calibration model is constructed based on the optical system structure. Then, we analyze the relative motion transformation of the observed stars. The stellar trajectory and the auxiliary ephemeris are used to obtain the corresponding object vector for correcting the associated calibration parameters iteratively. Experimental results evaluated on the data of a geostationary experiment satellite demonstrate that the positioning errors corrected by this proposed method can be within ±2.35 pixels. This approach is able to effectively calibrate the camera and improve the positioning accuracy, which avoids the influence of cloud cover and overcomes the great dependence on the number of the observed stars.

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Section: Introductionmentioning

confidence: 99%