Jul 2026· The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences· Vol XLIX-B3-2026, pp. 1249-1255· 0 citations· 1 references
Abstract
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.
Abstract. Accurate attitude estimation is essential for stable guidance and control during rocket recovery, yet it remains challenging because the target undergoes rapid pose changes, occupies only a limited image area over a large observation corridor, and often exhibits weak texture and approximate axial symmetry. To address these issues, this paper proposes a large-field binocular-vision-based attitude determination method for rocket recovery. First, a distortion-aware stereo calibration strategy based on stitched control points is developed to enable reliable geometric modeling over a large measurement field with a portable calibration target. Second, a robust contour extraction pipeline is constructed by combining bilateral filtering, gradient enhancement, and multi-threshold Canny fusion. Third, the rocket central axis is reconstructed by fitting 2D midlines in rectified stereo images and intersecting their corresponding back-projection planes, which improves stability over point-wise triangulation. Finally, pitch and yaw are derived from the recovered 3D axis direction, while roll is estimated by phase correlation on the polar-unwrapped base image under a temporal continuity constraint. Experiments on a 1:20 cylindrical scale model show RMS reprojection errors of 0.056 px and 0.066 px for the left and right cameras, respectively, and a 3D checkpoint RMSE of 33.42 mm. On a 100-frame sequence, the proposed method achieves RMSEs of 1.58°, 1.54° and 1.41° for roll, pitch, and yaw, respectively, outperforming ORB+PnP, SGBM, and Chamfer-based baselines. The results demonstrate that the proposed method provides an accurate and practical optical solution for external attitude measurement in rocket-recovery scenarios.
Yuqi Zhang, Xianglei Liu, Ruijie Wang et al.· The International Archives o...· 0 citations
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.
Wangxin Lai, Qing-Feng Zhang, Rui Zhang et al.· 0 citations
To address the scarcity of high-precision control points on planetary surfaces and the accumulated drift of conventional relative-localization methods in deep-space exploration missions, this paper proposes a visual absolute-localization method based on salient-landmark contour matching and centroid-consistency constraints. Absolute localization is defined as estimating the rover position in the landing-site North-East-Down (NED) coordinate system or a map-projection coordinate system, rather than in image-pixel coordinates. Stable natural objects, including dunes and impact craters, are treated as generalized feature points. Local terrain is reconstructed from binocular navigation imagery; LiDAR is additionally used in the ground physical-equivalent experiment for multi-source terrain fusion. Multi-class cross-scale contour matching provides homologous landmark associations, after which centroid consistency aligns the local terrain with the global DOM/DEM reference frame. For ten Tianwen-1/Zhurong camera stations, the mean planar error was 0.458 m and the RMSE was 0.491 m. For five ground-test conditions, the mean planar error was 0.494 m and the RMSE was 0.526 m; all tested errors were below 1 m. Because the in-orbit reference DOM has a ground sampling distance of 1 m/pixel, the in-orbit sub-meter values indicate agreement with the adopted reference products and should not be interpreted as absolute accuracy independent of reference-map uncertainty. The results support the feasibility of natural-landmark-based map localization for future Chang’e and Tianwen missions.
He Tian, Hanguang Zhao, Xin-Chao Xu et al.· Applied Sciences· 0 citations
High-resolution optical satellite constellations continuously generate massive volumes of remote sensing imagery, making automatic, ground-control-point-free (GCP-free) geometric positioning accuracy assessment increasingly important for ensuring the quality of downstream applications. However, conventional GCP-free inspection methods based on local feature matching often exhibit limited robustness under large initial positioning errors, weak-texture regions, cloud contamination, and temporal appearance variations, resulting in poor generalization across large-scale production scenarios. To address these challenges, this paper proposes a geometry-constrained framework that integrates Rational Polynomial Coefficient (RPC) prior constraints, coarse-to-fine registration, adaptive match-density-based block selection, hierarchical geometric verification, and a geolocation residual confidence measure into a unified automatic quality inspection pipeline. The framework leverages LoFTR for dense feature matching, but its principal contribution lies in the system-level integration and operational design for large-scale industrial satellite image production. Extensive experiments on multi-satellite and multi-scene datasets from the Jilin-1 satellite series show that the proposed method achieves a median positioning error below 2 m, an Average Precision (AP) improvement of 0.53 over the baseline, and nearly perfect accuracy on the evaluated test set for confidence thresholds above 0.5. The framework has also been deployed in the operational production system of multiple commercial Jilin-1 missions for more than six months, demonstrating its effectiveness, robustness, scalability, and practical applicability for large-scale optical satellite imagery.
Jia-Ming Cui, Wei-Bin Wang, Li-Ming Fan et al.· Remote Sensing· 0 citations
Point cloud registration remains challenging when the measured objects exhibit weak geometric features, where conventional geometric descriptors are often insufficient for establishing reliable correspondences. To address this issue, this paper proposes a coarse-to-fine registration framework that integrates two-dimensional image matching with threedimensional point cloud refinement. In the coarse registration stage, detector-free local feature matching with transformers is used to construct cross-modal correspondences, followed by a scale-invariant geometric consistency filtering strategy to suppress mismatches and improve the reliability of the estimated transformation. Note that the image for the coarse registration can be computed from the fringe patterns captured in the fringe projection profilometry. In the fine registration stage, a progressive modulation-weighted point-to-plane iterative closest point and normal iterative closest point scheme is adopted to improve local alignment accuracy. Experiments on a custom paper-sheet specimen and a textured scale vehicle model show that the proposed method achieves sub-millimeter registration accuracy, with a root mean square error of 0.107 millimeters and a mean absolute error of 0.011 millimeters, demonstrating its effectiveness for weak-geometry point cloud registration in fringe projection measurement.
Chao Zeng, Fangzheng Lv, Yingdong Li et al.· International Conference on...· 0 citations
The results highlight that careful parameterization — combining observation weighting, n-tuple point filtering, and per-satellite sensor refinement — is key to producing accurate, geometrically consistent large-scalemosaics from bi-satellite stereo imagery.
Michaël Erblang, Emelyne Saulnier, Guillaume Laurent et al.· The International Archives o...· 2 citations
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