High-resolution spacecraft images provide important astrometric constraints for orbit refinement, but measurements of resolved bodies are often limited by labor-intensive control-point selection and the difficulty of achieving consistent reductions over large image archives. We present an automated shape-model-based astrometric pipeline for Phobos and apply it to Mars Express Super Resolution Channel (SRC) images. For each exposure, a synthetic image is rendered from a high-resolution 3D shape model under the nominal spacecraft-target-Sun geometry. Feature correspondences between the observed and synthetic images are established using SuperPoint and SuperGlue, followed by RANSAC filtering. The matched synthetic-image keypoints are then associated with surface points through ray-shape intersection. The geometric adjustment fixes the adopted body orientation, spacecraft state, and corrected camera pointing and estimates only two effective plane-of-sky position offsets using the exact perspective-projection model. These offsets are used to derive the center-of-figure position of Phobos. We first test the method on an image set previously analysed with a control-point approach and obtain comparable astrometric performance. We then extend the analysis to a larger SRC dataset spanning 2007-2025 and obtain 1113 successful measurements. Relative to the JPL MAR099 ephemeris, the resulting observed-minus-computed residuals have mean values of 0.186 km in $\alpha \times cos(\delta)$ and 0.053 km in $\delta$, with corresponding standard deviations of 0.609 km and 0.583 km. These results demonstrate that the proposed pipeline provides a practical approach to large-scale, homogeneous astrometric reduction of archival spacecraft images of Phobos, with potential application to other resolved bodies.
ADORA provides a flexible framework for studying astrometric extraction, calibration-bias diagnosis, and future SHERA requirements, and Pixel-position errors across the tested range remain near the matched-model recovery scale indicating robustness to certain detector calibration errors.
Dylan M. McKeithen, S. Shaklan, G. Vasisht et al.· Space Telescopes and Instrum...· 0 citations
Accurate satellite tracking requires up-to-date Two-Line Elements (TLEs), as outdated data can lead to significant positioning errors. While ground-based optical telescopes are highly accessible, generating TLEs from their data is complicated by the fundamental lack of direct range measurements. This paper presents an automated end-to-end pipeline designed to overcome this limitation by proposing a robust method to estimate the range from prior TLE. The pipeline can then generate the updated TLEs by calculating new satellite state vectors using the estimated range. The pipeline consists of star and satellite detection, astrometric calibration, and orbit determination. For star and satellite detection, the key component of the pipeline is a robust deep learning-based detection model. To achieve this, we benchmarked models such as Deformable DETR, RF-DETR, and YOLOv12 against traditional image processing methods with 3105 images in FITS (Flexible Image Transport System) format. RF-DETR yields the highest F1 score (0.93) and precision (0.97) at an 8-pixel threshold. The detected star coordinates resulting from using RF-DETR, the best-performing model, were fed into Astrometry.net for precise astrometric calibration to determine the satellite celestial coordinates. The range required for orbit determination was estimated by extracting the prior TLE and propagating it to the observation epoch via SGP4. The satellite state vectors were then calculated using TLE-constrained orbit determination approach using the estimated range, followed by an inverse SGP4 optimization to recover the mean orbital elements. The generated TLEs were validated against public TLEs from Space-Track.org. To evaluate this pipeline, updated TLEs were generated specifically for medium Earth orbit (MEO) and geostationary Earth orbit (GEO) targets. The results demonstrate that the proposed method yields high accuracy for GEO satellites, achieving a mean motion difference of 0.0030 rev/day and a 24-hour ground-track position error of 0.83 degrees. In comparison, MEO satellites achieve a mean motion difference of 0.0126 rev/day and an error of 5.27 degrees. These results suggest that the proposed pipeline provides a robust foundation for automated orbit determination with clear potential for further refinement.
Kamin Kanchanapradit, K. Noysena, R. Lipikorn· IEEE Access· 0 citations
(Photometry and Astrometry of Point Sources), a fully automated Python-based pipeline for photometric reduction with integrated astrometric calibration, is introduced, supporting the homogeneous reduction of stellar and moving Solar System objects, independent of telescope aperture or detector type.
Orhan Erece, Yücel Kılıç· Astronomy & Astrophysics· 1 citation
Precise orbit determination of main-belt asteroids is essential for deep-space mission design, navigation, and target characterization. This study presents a refined orbit-determination analysis for 623 Chimaera and 269 Justitia, the two largest targets of the Emirates Mission to the Asteroid Belt (EMA). The dynamical model includes perturbations from sun, major planets, Pluto, selected massive asteroids, selected Kuiper Belt Objects, and solar radiation pressure. To improve computational efficiency while retaining the dominant dynamical effects, we developed a perturber-selection scheme based on a perturbing-acceleration indicator and a knee-point criterion. Long-arc ground-based optical astrometry was combined with high-precision measurements from Gaia, TESS, WISE, and stellar occultations. Catalogue-dependent debiasing, residual-based outlier rejection, and station-dependent weighting were applied to mitigate the heterogeneity of the astrometric data. The resulting solutions were evaluated using post-fit residual statistics, covariance propagation, and comparisons with reference ephemerides generated through JPL Horizons. The differences between the derived orbits and the reference ephemerides remain at the kilometre-to-tens-of-kilometres level over the investigated interval, corresponding to small angular offsets at the relevant geocentric distances. A sensitivity and covariance analysis was also conducted to assess the observability of solar radiation pressure. The results indicate that milliarcsecond-level astrometry is required for a reliable estimation of the radiation-pressure coefficient; therefore, this coefficient was fixed to its nominal theoretical value in the adopted solutions. These results provide a dynamical and observational basis for further ephemeris refinement of EMA target asteroids.
R. Lu, Zimeng Li, Wanling Yang et al.· Frontiers in Astronomy and S...· 0 citations
Abstract. Determining accurate asteroid rotation parameters is essential for establishing a body-fixed coordinate system during deep-space proximity operations. However, early mission phases often lack prior exterior orientation data. When combined with edge effects from the deep-space background, this deficiency leads to high mismatch rates and ill-conditioned geometries. In this paper, we propose an integrated photogrammetric pipeline to refine these parameters using adaptive feature masking and stereo intersection angle optimization. Rather than using conventional matching, our approach isolates the asteroid target via an adaptive grayscale-threshold mask and morphological refinement, which restricts feature extraction to valid surface textures and significantly reduces outliers. We then introduce a geometric filter to discard stereo pairs with intersection angles below 5°, effectively preventing error propagation along the line of sight. Ultimately, the precise Right Ascension (RA) and Declination (Dec) are determined through an iterative coarse-to-fine grid search that minimizes spatial intersection residuals. Testing our method on 127 images of asteroid (162173) Ryugu from the Hayabusa2 ONC-T camera yielded strong results. The masking strategy successfully cut the number of mismatches in half (from 14,949 to 7,369). Within four iterations, the rotational parameters converged to RA = 96.5° and Dec = -66.4°. These refined results offer a reliable foundation for subsequent 3D reconstruction and high-precision planetary mapping.
Zhen Peng, Xun Geng, Pengying Liu et al.· The International Archives o...· 0 citations
On-orbit absolute radiometric calibration tracks sensor radiometric degradation and ensures accuracy for quantitative applications. Low-cost commercial satellites lack expensive on-board calibration systems, and traditional alternative methods cannot achieve automated, reliable calibration for large sensor fleets with low resource consumption. Pseudo-invariant calibration sites require no ground instruments, but commercial satellites’ heavy imaging schedules hinder frequent PICS observations. The Jilin-1 constellation is a large commercial constellation composed of satellites carrying multispectral imagers with resolution better than 1 m, and it has no on-board calibration system. Thus, an automated calibration method applicable to numerous imagers is needed, one that requires widely available clear-sky ground targets. Using MCD43A2 and MCD12Q1 products, we generate calibration region vectors to transfer the MODIS radiometric reference to Jilin-1. A look-up table (LUT) is constructed for the input parameters of the MODTRAN model. Calibration pixels and model input parameters are then extracted from Jilin-1 imagery using the region vectors, the LUT is interpolated to obtain the at-aperture radiance for each pixel and band, and on-orbit absolute radiometric calibration coefficients are calculated. The proposed method requires no ground-based synchronous experiments, achieves a high level of automation, and does not consume commercial imaging resources. The site calibration validation based on RadCalNet for the JL1GF02F PMS1 sensor shows that the maximum relative difference in the method across all bands is less than 4%.
Xiaojie Yang, Qiuyan Liu, Song Yang et al.· Remote Sensing· 1 citation
