A Geometric Distortion Solution Specifically for Historical Observations and its Implementation

Abstract Geometric distortion (GD) critically constrains the precision of astrometry. Using well-established methods to correct GD requires calibration observations, which can only be obtained using a special dithering strategy during the observation period. Unfortunately, this special observation mode is not often used, especially for historical observations before those GD correction methods were presented. As a result, some telescopes have no GD calibration observations for a long period, making it impossible to accurately determine the GD effect. This limits the value of the telescope observations in certain astrometric scenarios, such as using historical observations of moving targets in the solar system to improve their orbits. We investigated a method for handling GD that does not rely on the calibration observations. With this advantage, it can be used to solve the GD models of telescopes which were intractable in the past. The method was implemented in Python and released on GitHub. It was then applied to solve GD in the observations taken with the 1 m and 2.4 m telescopes at Yunnan Observatory. The resulting GD models were compared with those obtained using well-established methods to demonstrate the accuracy. Furthermore, the method was applied in the reduction of observations for two targets, the moon of Jupiter (Himalia) and binary GSC 2038-0293, to show its effectiveness. After GD correction, the astrometric results for both targets show improvements. Notably, the mean residual between the observed and computed position ( O − C ) for binary GSC 2038-0293 decreased from 36 to 5 mas.

Authors

Publication Details

Journal
Research in Astronomy and Astrophysics
Published
2024-09-30
DOI
https://doi.org/10.1088/1674-4527/ad818b
Citations
1
Primary Topic
Satellite Image Processing and Photogrammetry
Type
article
Field-Weighted Citation Impact
0.34
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Geometric Distortion Solution Specifically for Historical Observations and its Implementation

Qing-Yu Peng, Zhongjie Zheng, Bifeng Guo, Furong Lin
1 citations
Research in Astronomy and Astrophysics
Satellite Image Processing and Photogrammetry
0.34
article

A Geometric Distortion Solution Specifically for Historical Observations and its Implementation

Qing-Yu Peng, Zhongjie Zheng, Bifeng Guo, Furong Lin
article en
1 citations

Abstract

Abstract Geometric distortion (GD) critically constrains the precision of astrometry. Using well-established methods to correct GD requires calibration observations, which can only be obtained using a special dithering strategy during the observation period. Unfortunately, this special observation mode is not often used, especially for historical observations before those GD correction methods were presented. As a result, some telescopes have no GD calibration observations for a long period, making it impossible to accurately determine the GD effect. This limits the value of the telescope observations in certain astrometric scenarios, such as using historical observations of moving targets in the solar system to improve their orbits. We investigated a method for handling GD that does not rely on the calibration observations. With this advantage, it can be used to solve the GD models of telescopes which were intractable in the past. The method was implemented in Python and released on GitHub. It was then applied to solve GD in the observations taken with the 1 m and 2.4 m telescopes at Yunnan Observatory. The resulting GD models were compared with those obtained using well-established methods to demonstrate the accuracy. Furthermore, the method was applied in the reduction of observations for two targets, the moon of Jupiter (Himalia) and binary GSC 2038-0293, to show its effectiveness. After GD correction, the astrometric results for both targets show improvements. Notably, the mean residual between the observed and computed position ( O − C ) for binary GSC 2038-0293 decreased from 36 to 5 mas.

Research in Astronomy and AstrophysicsVol. 24(11)
Openalex Percentile: Top 41%
Satellite Image Processing and Photogrammetry
0.34
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.