Public DEM-aided Geopositioning Without Ground Control Points For Chinese Satellite Imagery

Under the background of global surveying and mapping,the study of satellite image geopositioning without ground control points(GCPs)can not only effectively improve the geopositioning efficiency and save a lot of manpower and resources,but also have great practical value and significance in wartime,emergency service and other services.In recent years,various high resolution and high accuracy global digital elevation models(DEMs)have been freely released,which can be used as ideal auxiliary data to improve satellite image geopositioning accuracy without GCPs.Focus on the technology of public DEM-aided geopositioning without GCPs for Chinese satellite image,a set of theories and methods of public DEM-aided geopositioning without GCPs was proposed in this article.In addition,corresponding software is developed based on the theoretical research.The main work and innovation are as follow:1.The research background and significance of satellite image high accuracy geopositioning without GCPs were expatiated,and then the research status of high resolution optical satellite image geopositioning without GCPs or with a few GCPs,existing geocoded data-aided geopositioning and DEM matching were summarized.2.High resolution global pubic DEMs were introduced,and literatures about their accuracy analysis were summarized.Then,experimental three-line array CCD(TLC)images of Mapping Satellite-1(TH-1)and ZiYuan-3 surveying satellite(ZY-3)were introduced.Finally,comparison experiments were designed to analysis the quality and accuracy of public DEMs based on qualitative analysis,the runway method and the height difference method.Experimental results show that SRTM(Shuttle Radar Topography Mission)DEM and AW3D30(Advanced Land Observing Satellite World 3D–30m)DSM(digital surface model)have no obvious noise and gross error,which can express various terrains well,and the latter includes more terrain details.There are obvious particle effects in ASTER(Advanced Spaceborne Thermal Emission and Reflection Radiometer)GDEM(Global DEM),which result in it is difficult to express the terrain very well in the area with small elevation undulation.3.Aiming at the problem of public DEM-aided satellite image geopositioning,an efficient and robust geopositioning method based on DEM matching was proposed.Firstly,the target DEM was extracted from TLC image and then matched with the public DEM.In DEM matching,a least trimmed squares estimator was introduced into least Z-difference(LZD)method to overcome the adverse effects caused by local deformation and gross error in DEMs.At the same time,the corresponding point determination strategy was selected adaptively based on the resolution of DEMs involved in matching to ensure the computational efficiency.Finally,bias compensation parameters were solved.Multi-group experiments of TH-1 and ZY-3 images were designed.Experimental results show that the proposed method can make full use of the consistent and high accuracy and abundant information of the public DEM,and has good robustness and high computational efficiency.If target DEM resolution is relatively high,the geopositioning accuracy of TLC image aided by AW3D30 DSM or SRTM DEM without GCPs can satisfy the geometric accuracy requirements of 1:50 000 scale basic geographic information products.4.In order to fully compensate the relative and absolute bias in image geopositioning parameters,and to overcome the adverse effect of the water area on DEM extraction,a TLC image geopositioning method without GCPs based on public DEM multi-level constraint mechanism was proposed.The public DEM is integrated into the method in each part.In DEM matching,it is regarded as reference data.As for DEM extraction,it is also served as constraint of elevation determination and reference for water area marking.In addition,the weak geometric convergence between TLC image was compensated by free network adjustment.Experimental results show that the method can compensate bias in image geopositioning parameters effectively.It has preferable applicability to images of different regions such as the interior and the islands and reefs and of different Chinese satellite platforms such as TH-1 and ZY-3.Furthermore,its geopositioning accuracy has good stability,which is not sensitive to the change of target DEM resolution.5.To solve the problem that the geopositioning bias in the flat region image is difficult to effectively compensated by DEM matching,and to improve the geopositioning accuracy inconsistency between different TLC images,a public DEM-aided regional TLC images network geopositioning method without GCPs was proposed.Firstly,the bias compensation method for each TLC image is determined according to the undulation of terrain within image coverage area.Only vertical bias was compensated by using public DEM for the images of flat region,while biases in planimetric and vertical were compensated by DEM matching for other images.And then these non-flat region images which have obtained high geopositioning accuracy after bias compensation were used to compensate the bias in flat region images.Finally,block adjustment was conducted.Experimental results show that the evaluation index of terrain undulation is distinguishable.The public DEM-aided vertical bias compensation and non-flat region image-aided bias compensation can effectively improve the geopositioning accuracy of flat region image.Block adjustment can reduce the differences among TLC images geopositioning results effectively,and is applicable to a wide local area network.6.On the basis of theoretical research,the public DEM–aided Chinese satellite imagery geopositioning without GCPs software was designed and developed.It has strong applicability and can effectively compensate bias for different regions and terrains images obtained by different Chinese satellite platforms such as TH-1 and ZY-3.The software is humanization and is easy and convenient to operate.The geopositioning process also has a high degree of automation.Thus,it can be effectively applied to the actual production and application to improve the geopositioning accuracy of Chinese satellite images without GCPs.