Estimation and improvement in the geolocation accuracy of rational polynomial coefficients with minimum GCPs using KOMPSAT-3A

ABSTRACT

In this paper, we propose a method to regenerate Rational Polynomial Coefficients (RPCs) using KOMPSAT-3A imagery and to reduce the geolocation error using minimum ground control points (GCPs). To estimate the new RPCs, the physical sensor model fitted to KOMPSAT-3A imagery was utilized and virtual GCPs over the study area were created. The size of the virtual grid used was 20x20x20. To remove the sensor-related errors in physical sensor model, three different image correction models (image coordinate translation model, shift and drift model, and affine transformation model) were additionally applied. We evaluated our proposed method in two areas within Korea, one in urban (Seoul) and one in rural (Goheung) areas. The results showed that there was a significant improvement after applying the suggested approach in the two areas. The image coordinate translation model is suggested in terms of GCP requirement and expected errors estimated from the error propagation analysis using Gauss–Markov Model (GMM).     

CBERS-02B卫星遥感影像的区域网平差

针对中巴资源一号卫星(CBERS-02B)卫星遥感影像姿态角误差较大的特点,提出了利用区域网平差方法提高其对地目标定位精度的策略和具体计算过程。首先对参与平差的每景影像选取4个地面控制点进行影像姿态角常差检校,然后采用与地形无关方案解求各自的RPC参数,最后选取带仿射变换项的有理函数模型(RFM)进行多重覆盖影像的区域网平差。对两个地区的0级CBERS-02B单条CCD立体影像对的区域网平差试验表明,对地目标定位的平面和高程精度均达到了±3个像元的水平,且高程精度明显优于平面精度。相对于常规的卫星遥感影像区域网平差方法,平面和高程精度均有明显提升,几乎达到国外同等高分辨率卫星遥感影像的几何定位精度。这说明中国卫星遥感影像亦具有较好的几何定位潜力,在区域网平差之前进行系统误差预改正是必要和可行的。     

光学卫星摄影无控定位精度分析

"全球连续覆盖"和"局部区域覆盖"是卫星摄影测量常用的两种摄影模式,两种模式应用目标和无控定位实现途径也各有特点。本文简要介绍了两种模式典型的卫星无控定位精度情况,阐述了光束法平差的关键技术,重点对前方交会和光束法平差无控定位精度进行试验分析。试验结果表明,姿态误差是影响无控定位精度的重要因素,影像分辨率对其影响较小。当外方位角元素误差大于0.5″时,即使影像分辨率为5m,光束法平差后,其无控定位精度也优于0.5m分辨率影像前方交会精度。     

基于严格仿射变换模型的遥感影像RPC参数求解

提出了利用少量地面控制点,采用基于严格仿射变换模型求解遥感影像的RPC参数,并对CBERS-02B卫星HR相机遥感影像进行了试验,获得了一些有意义的结论。     

Orthorectification of VHR optical satellite data exploiting the geometric accuracy of TerraSAR-X data

Orthorectification of satellite data is one of the most important pre-processing steps for application oriented evaluations and for image data input into Geographic Information Systems. Although high- and very high-resolution optical data can be rectified without ground control points (GCPs) using an underlying digital elevation model (DEM) to positional root mean square errors (RMSEs) between 3 m and several hundred meters (depending on the satellite), there is still need for ground control with higher precision to reach lower RMSE values for the orthoimages. The very high geometric accuracy of geocoded data of the TerraSAR-X satellite has been shown in several investigations. This is due to the fact that the SAR antenna measures distances which are mainly dependent on the terrain height and the position of the satellite. The latter can be measured with high precision, whereas the satellite attitude need not be known exactly. If the used DEM is of high accuracy, the resulting geocoded SAR data are very precise in their geolocation. This precision can be exploited to improve the orientation knowledge and thereby the geometric accuracy of the rectified optical satellite data. The challenge is to match two kinds of image data, which exhibit very different geometric and radiometric properties. Simple correlation techniques do not work and the goal is to develop a robust method which works even for urban areas, including radar shadows, layover and foreshortening effects. First the optical data have to be rectified with the available interior and exterior orientation data or using rational polynomial coefficients (RPCs). From this approximation, the technique used is the measurement of small identical areas in the optical and radar images by automatic image matching, using a newly developed adapted mutual information procedure followed by an estimation of correction terms for the exterior orientation or the RPC coefficients. The matching areas are selected randomly from a regular grid covering the whole imagery. By adjustment calculations, parameters from falsely matched areas can be eliminated and optimal improvement parameters are found. The original optical data are orthorectified again using the delivered metadata together with these corrections and the available DEM. As proof of method the orthorectified data from IKONOS and ALOS-PRISM sensors are compared with conventional ground control information from high-precision orthoimage maps of the German Cartographic Survey. The results show that this method is robust, even for urban areas. Although the resulting RMSE values are in the order of 2-6 m, the advantage is that this result can be reached even for optical sensors which do not exhibit low RMSE values without using manual GCP measurements.     

Extraction of Three-Dimensional Architectural Data from QuickBird Images

Extraction of accurate spatial information from high-resolution satellite imagery is becoming increasingly important for a variety of tasks. In this study, three-dimensional architectural data were extracted from QuickBird images using Barista’s monoplotting function. We evaluated the accuracy of the Rational Polynomial Coefficients bundle adjustment and extracted building heights. We obtained accuracies of one-pixel in geo-positioning and 2.66 m in building height. The height accuracy is 0.16 m greater than the estimated error for a one-pixel image measurement. The presence of roof overhangs is one primary factors affecting height accuracy. The application of three-dimensional architectural data represents well the vertical extension of urban growth in Tiexi District from 2002 to 2008.     

Orientation of MOMS-02/D2 and MOMS-2P/PRIRODA imagery

This paper deals with the orientation of three-line imagery which has been taken during the MOMS-02/D2 experiment in spring 1993, and during the MOMS-2P/PRIRODA mission since April 1996. The reconstruction of the image orientation is based on a combined adjustment of the complete image, ground control, orbit and attitude information. The combined adjustment makes use of the orientation point approach or the orbital constraints approach. In the second case, the bundle adjustment algorithm is supplemented by a rigorous dynamical modeling of the spacecraft motion. The results of the combined adjustment using MOMS-02/D2 imagery and control information of orbit #75b are presented. Based on the orientation point approach an empirical height accuracy of up to 4 m (0.3 pixel) is obtained. In planimetry the empirical accuracy is limited to about 10 m (0.7 pixel), since the ground control points (GCP) and check points could not be identified in the imagery with the required accuracy. Computer simulations on MOMS-2P/PRIRODA image orientation based on realistic input information have shown that good accuracies of the estimated exterior orientation parameters and object point coordinates can be obtained either with a single strip and a few precise GCP or even without ground control information, if a block of several overlapping and crossing strips with high geometric strength (q≈60%) is adjusted.     

区域网平面平差超控外推定位技术验证

以资源三号卫星影像数据为例,基于RPC模型提出利用SRTM辅助的卫星影像区域网平面平差的方法进行超长距离控制外推,来提高无控地区的影像几何定位精度。试验表明,影像原始RPC直接定位精度含有明显的系统误差。在起算影像区域内布设一个控制点进行区域网平面平差,沿轨外推11景(491.62 km)、垂轨外推6景(282.36 km)后,相比原始影像13.335 m的平均定位精度,其外推区域影像的几何定位精度可优于7.5 m,无控区域的整体定位精度有明显提升,验证了该方法的有效性。     

仅用虚拟控制点的超大区域无控制区域网平差

利用光学卫星影像进行无控制测图是摄影测量追求的目标。针对超大区域无控制测图的需求,本文提出了一种以单景影像为平差单元,基于虚拟控制点的光学卫星影像超大规模无控制区域网平差方法。该方法利用待平差影像的初始RPC模型生成虚拟控制点,并将其作为带权观测值引入平差模型中以改善平差模型的状态,克服了在无控制点条件下平差精度不稳定、误差过度累积引起的网的扭曲变形等问题。为了验证本方法的有效性和精度,利用资源三号卫星获取的覆盖全国的26 406景影像进行区域网平差试验,并利用全国范围内分布的约8000个高精度控制点对平差后自动生产的DOM和DSM产品的几何精度进行验证。试验结果表明,平面和高程中误差均达到了4m以内,同时,区域网内部相邻影像之间的几何拼接精度优于1个像素,满足无缝拼接的要求。     

机载干涉雷达数据联合定位及拼接技术研究

针对大区域多航带InSAR(干涉合成孔径雷达)影像定位及拼接时缺少GCP(地面控制点)的问题,提出了一种多航带InSAR影像联合定位的方法。该方法借鉴摄影测量中的光束法平差思想,并利用InSAR干涉定标后得到影像上各点高程值。通过对四川绵阳地区的多航带InSAR实际数据的实验,验证了本方法的可行性,且精度达到了各景影像独立校正的水平。分析了控制点数量、位置、重叠区域范围、地形起伏对平差精度的影响,并给出了控制点布放原则。     

一种基于复共线性分析的RPC参数优选法

推导了求解有理多项式系数(RPC)的严密误差方程,从分析误差方程设计矩阵列向量间的复共线性着手,提出了一种去相关的RPC参数优选方法。对一景SPOT-5 HRG 1A级影像进行实验,结果表明,当地面控制点稀疏时,通过优选20~30个RPC参数,可以很好地消除参数间的相关性,有效消除有理函数模型(RFM)在地形拟合中出现的振荡现象,可明显提高RPC参数求解和RFM的影像几何处理精度。当地面控制点足够多时,利用此方法优选的RPC参数进行地形拟合的结果与用常规最小二乘法求解的78个RPC参数实施地形拟合的结果完全一致。     

Using horizontal and vertical building structure to constrain indirect sensor orientation

This paper presents a method to integrate linear horizontal, vertical and right-angled scene structures into the bundle adjustment of image sequences. An increasing number of airborne image acquisition systems is available and equipped with non-metric small- or medium-frame cameras and no or insufficiently accurate INS devices. In cases where the data is to be used for the production of geo-spatial data, where a certain accuracy and precision is required, an indirect sensor orientation, possibly including self-calibration, needs to be performed. The idea which led to the presented approach is to reduce the number of GCPs necessary for this task by applying the mentioned scene structures. The method directly uses the linear structures, visible at man-made objects as fictive observations within the adjustment, while self-calibration of intrinsic camera parameters and lens distortion is included as well.Experiments with two datasets demonstrate that, through this method, only limited GCP information is required to obtain satisfactory results. In fact, in one experiment using oblique images, several scene constraints were provided and only the datum was defined by ground control. The residuals at check points from this setup were similar to the traditional case where several well-distributed GCPs were available in the scene. In the second experiment the ability of this approach to support the bundle adjustment was shown for a UAV dataset. Although no GCP and camera calibration information was available, the visual inspection of adjusted object points and the residuals at horizontal structures confirmed the ability of the method to align an image block with the structure, as embodied in the defined scene constraints. Despite the convincing outcome of the experiments, it needs to be mentioned that some manual work is still involved in defining the constraints. In future work the issue of automation will be addressed.     

基于IRS-P5卫星影像测图的关键技术研究

针对IRS-P5卫星影像的误差来源,分析了基于RPC的区域网平差数学模型,实验结果表明:仿射变换模型能有效地消除RPC模型的误差。基于EGM2008重力场模型的移去恢复法,显著提高了正常高的精度,节约了大量的水准测量工作。在山地和高山地,2.5 m分辨率的IRS-P5卫星影像可满足1∶10 000比例尺地形图的精度要求。     

资源三号卫星传感器校正产品的精度评估

分别选取资源三号(ZY-3)卫星平地和山地区域的前后视影像,量测20个GPS点作为控制点和检查点,对卫星传感器校正产品定位精度进行验证。通过区域网平差算法对传感器校正产品(SC)自带的有理函数模型(RPC)进行优化,消除系统误差。实验结果表明:在地形平坦地区ZY-3卫星SC产品的平面定位精度可达3.275 m,高程定位精度可达1.686 m;在地形起伏较大的山区平面定位精度可达4.335 m,高程定位精度可达3.628 m,满足1∶50 000地形图测绘的要求。     

高分辨率遥感影像几何纠正方法

在对某些地区的高分辨率卫星影像进行几何校正时,由于地形等因素影响难以寻找控制点,从而导致控制点较少且分布不均匀,影响了校正精度。针对这些问题,对线阵推扫式的高分辨率遥感影像的特点进行了分析,提出了利用直线这种更高级的几何特征对影像进行几何校正的方法;构建空间直线矢量,提出了基于空间直线矢量的多项式几何校正模型;并利用SPOT5高分辨率卫星影像数据对该校正模型进行精度验证。     

Google Earth辅助下的高分辨率遥感影像区域网平差

针对国产卫星境外定位的实际需要,提出利用Google Earth数据量测控制点辅助高分辨率遥感影像区域网平差的方法。首先统一坐标系,将所量测的控制点高程坐标转换为大地高;然后将其视为精度较低的控制点参与平差。试验分为无地面控制点和布设稀少地面控制点两种情况,对于每种情况分别设计不同的试验方案分析Google Earth数据对于定位精度的影响。结果表明利用Google Earth数据辅助区域网平差可以明显提高定位精度,可为缺少地面控制点的境外地区的光学线阵遥感影像几何定位提供新的思路。     

卫星摄影姿态测定系统低频误差补偿

姿态测定系统不仅存在高频误差,还存在与卫星轨道纬度及时间有关的低频误差,严重影响无地面控制点测量精度。本文分析了产生低频误差的因素及相关解决措施,并在天绘一号(TH-1)卫星工程中,利用光束法平差实现低频误差的自动检测与补偿处理,消除低频误差对定位精度的影响,最后进行了试验验证。试验结果表明:低频误差补偿技术,很好地解决了无地面控制定位系统误差问题,为实现天绘一号卫星全球定位精度的一致性发挥了重要作用。     

Three-Dimensional Geopositioning Accuracy of Ikonos Imagery

An investigation of the accuracy potential of Ikonos 1m satellite imagery is reported. Three sensor orientation/triangulation models are applied to stereo- and three-image configurations of "Geo" imagery with the aim of achieving 3D geopositioning to sub-metre accuracy. The models considered comprise rational functions with bias compensation, affine projection and the direct linear transformation. Test results from the Melbourne Ikonos Testfield are reported and these show that with modest provision of good quality ground control, Ikonos "Geo" imagery can yield 3D object-point determination to an accuracy of 0.5m in planimetry and 0.7m in height. The accuracy achieved is not only consistent with expectations for rigorous sensor orientation models, but is also readily attainable in practice with only a small number of ground control points being required     

GCP collection for corona satellite photographs: Issues and methodology

Use of high-resolution and historic CORONA satellite photographs for mapping and other purposes requires Ground Control Points (GCPs), as ephemeris data and image parameters are not available. However, the alterations in landscape in last 34 years (i.e., since the acquisition of these photographs) prevent identification and collection of large number of GCPs in the field. This paper presents a methodology for collection of GCPs for CORONA photographs. The advantages and limitations of the methodology are discussed. For a study site, situated in Siwaliks and Lower Himalayas, the GCPs were identified in CORONA photographs and their WGS84 coordinates were estimated through a process of datum transformation and georeferencing. Estimated GCP coordinates from the topo sheets and 2D and 3D views of photographs, helped in identifying the GCP locations in field, which were observed using DGPS. Investigations were carried out to relate Differential Global Positioning System (DGPS) accuracy with base line length and time of observation. Abase line of 350 km and half an hour observation were found appropriate to yield accuracy in GCP collection by DGPS method, which conforms to CORONA resolution of 3 m.