On-orbit Geometric Calibration of Linear Push-broom Optical Satellite Based on Sparse GCPs

The paper presents a geometric calibration method based on the sparse ground control points (GCPs), aiming to the linear push-broom optical satellite. This method can achieve the optimal estimate of internal and external parameters with two overlapped image pair along the charge-coupled device (CCD), and sparse GCPs in the image region, further get rid of the dependence on the expensive calibration site data. With the calibrated parameters, the line of sight (LOS) of all CCD detectors can be recovered. This paper firstly establishes the rigorous imaging model of linear push-broom optical satellite based on its imaging mechanism. And then the calibration model is constructed by improving the internal sensor model with a viewing-angle model after an analysis on systematic errors existing in the imaging model is performed. A step-wise solution is applied aiming to the optimal estimate of external and internal parameters. At last, we conduct a set of experiments on the ZY-3 NAD camera and verify the accuracy and effectiveness of the presented method by comparison.

Geometric positioning integrating optical satellite stereo imagery and a global database of ICESat-2 laser control points:A framework and key technologies

Block Adjustment(BA)is one of the essential techniques for producing high-precision geospatial 3D data products with optical stereo satellite imagery.For block adjustment with few ground-control points or without ground control,the vertical error of the model is the decisive factor that constrains the accuracy of 3D data products.The elevation data obtained by spaceborne laser altimeter have the advantages of short update periods,high positioning precision,and low acquisition cost,providing sufficient data support for improving the elevation accuracy of stereo models through the combined BA.This paper proposes a geometric positioning model based on the integration of Optical Satellite Stereo Imagery(OSSI)and spaceborne laser altimeter data.Firstly,we elaborate the principle and necessity of this work through a literature review of existing methods.Then,the framework of our geo-positioning models.Secondly,four key technologies of the proposed model are expounded in order,including the acquisition and management of global Laser Control Points,the association of LCPs and OSSI,the block adjustment model combining LCPs with OSSI,and the accuracy estimation and quality control of the combined BA.Next,the combined BA experiment using Ziyuan-3(ZY-3)OSSI and ICESat-2 laser data was carried out at the testing site in Shandong Province,China.Experimental results prove that our method can automatically select LCPs with high accuracy.The elevation deviation of the combined BA eventually achieved the Mean Error(ME)of 0.06 m and the Root Mean Square Error(RMSE)of 1.18 m,much lower than the ME of 13.20 m and the RMSE of 3.88 m before the block adjustment.A further research direction will be how to perform more adequate accuracy analysis and quality control using massive laser points as checkpoints.

Large-scale automatic block adjustment from satellite to indoor photogrammetry

Block Adjustment(BA)is a critical procedure in the geometric processing of satellite images,responsible for compensating and correcting the geometric positioning errors of the images.The accuracy of the photogrammetric products,including Digital Orthophoto Map(DOM),Digital Elevation Model(DEM),Digital Line Graphic(DLG),and Digital Raster Graphic(DRG),directly depends on the accuracy of BA results.In recent years,the rapid development of related technologies such as Artificial Intelligence(AI),Computer Vision(CV),Unmanned Aerial Vehicles(UAVs)and big data has greatly facilitated and transformed the classical BA in photogrammetry.This paper first reviews the current status of BA and then looks into the future.First,this paper provides a brief review of the key technologies involved in BA,including image matching,the establishment of adjustment model,the determination of the parameters and the detection of gross error.Then,taking the intercross and fusion of current technologies such as AI,cloud computing and big data with photogrammetry into account,this paper explores the future trends of photogrammetry.Finally,four typical cases of large-scale adjustment are introduced,including large-scale BA without Ground Control Points(GCPs)for optical stereo satellite images,large-scale BA with laser altimetry data for optical stereo satellite images,large-scale BA for UAV oblique photogrammetry,and large-scale BA for indoor photogrammetry in caves with a large number of close-range images.