Geometric in-flight calibration of the stereoscopic line-CCD scanner MOMS-2P

This paper describes the geometric in-flight calibration of the Modular Optoelectronic Multispectral Scanner MOMS-2P, which has collected digital multispectral and threefold along-track stereoscopic imagery of the earth's surface from the PRIRODA module of the Russian space station MIR from October 1996 to August 1999. The goal is the verification and, if necessary, the update of the calibration data, which were estimated from the geometric laboratory calibration. The paper is subdivided into two parts, describing two different procedures of geometric in-flight calibration. The first method is based on DLR matching software and is restricted to nadir looking channels, which are read out simultaneously. From a high number of individual point matches between the images of the same area taken by the different CCD arrays, the most reliable ones are selected and used to calculate shifts with components in and across flight direction between the CCD arrays. These actual shifts are compared to the nominal shifts, derived from the results of the laboratory calibration, and parameters of the valid camera model are estimated from both data sets by least squares adjustment. A special case of band-to-band registration are the two optically combined CCD-arrays of the nadir high-resolution channel. They are read out simultaneously with a nominal 10 pixel overlap in stereoscopic imaging mode A. The DLR matching software is applied to calculate the displacement vector between the two CCD-arrays. The second method is based on combined photogrammetric bundle adjustment using an adapted functional model for the reconstruction of the interior orientation. It requires precise and reliable ground control information as well as navigation data of the navigation-package MOMS-NAV. Nine contiguous image scenes of MOMS-2P data-take T083C building an about 550-km-long strip over southern Germany and Austria taken in March 1997 were evaluated. From both procedures calibration data are estimated, which are presented and compared to the lab-calibration results.     

基于三线阵航天遥感影像的DEM自动生成

由于三线阵立体影像在提取3维空间信息方面具有突出的优点，文中利用MOMS-02前、后视影像对基于三线阵航天遥感影像的DEM自动生成进行了研究与试验，主要内容包括三线阵航天遥感影像的外部定向、数字影像匹配、DEM自动生成等。试验结果表明，采用文中提出的方法用于DEM自动生成可以取得较高的高程精度。     

Bias-corrected rational polynomial coefficients for high accuracy geo-positioning of QuickBird stereo imagery

The rational function model (RFM) is widely used as an alternative to physical sensor models for 3D ground point determination with high-resolution satellite imagery (HRSI). However, owing to the sensor orientation bias inherent in the vendor-provided rational polynomial coefficients (RPCs), the geo-positioning accuracy obtained from these RPCs is limited. In this paper, the performances of two schemes for orientation bias correction (i.e., RPCs modification and RPCs regeneration) is presented based on one separate-orbit QuickBird stereo image pair in Shanghai, and four cases for bias correction, including shift bias correction, shift and drift bias correction, affine model bias correction and second-order polynomial bias correction, are examined. A 2-step least squares adjustment method is adopted for correction parameter estimation with a comparison with the RPC bundle adjustment method. The experiment results demonstrate that in general the accuracy of the 2-step least squares adjustment method is almost identical to that of the RPC bundle adjustment method. With the shift bias correction method and minimal 1 ground control point (GCP), the modified RPCs improve the accuracy from the original 23 m to 3 m in planimetry and 17 m to 4 m in height. With the shift and drift bias correction method, the regenerated RPCs achieve a further improved positioning accuracy of 0.6 m in planimetry and 1 m in height with minimal 2 well-distributed GCPs. The affine model bias correction yields a geo-positioning accuracy of better than 0.5 m in planimetry and 1 m in height with 3 well-positioned GCPs. Further tests with the second-order polynomial bias correction model indicate the existence of potential high-order error signals in the vendor-provided RPCs, and on condition that an adequate redundancy in GCP number is available, an accuracy of 0.4 m in planimetry and 0.8 m in height is attainable.     

遥感影像纠正中控制点库建立相关技术

地面控制点的选取是遥感影像几何纠正中的重要环节。针对人工选取控制点的缺陷,根据控制点数据的特点提出了控制点属性数据和图像数据的一体化存储管理方案;设计了控制点库查询检索、匹配选点的使用流程;实现了一个控制点影像数据库的应用系统。系统的使用效果达到预期设想,大大提高了选点精度和效率。对控制点数据进行建库管理可以充分利用已有控制点成果,并能提高选点效率和精度。     

Pass processing of IRS-1C/1D PAN subscene blocks

This paper describes a method for pass processing of IRS-1C/1D imagery acquired by the three CCD arrays of the panchromatic (PAN) camera. It is based on the fact that during a single pass, the image data stream from the three CCD arrays of the PAN camera can be adjusted together as a single image, exploiting the knowledge of the internal geometry and the angular relationships between the CCD arrays. The geometry of this extended image can be rectified with a single ground control point (GCP). A full PAN scene consists of nine subscenes, each with a dimension of 23.5 km×23.5 km. The method is not restricted in the number of continuous full scenes (in the same pass) that can be adjusted. The scale variations between the images from the three detectors are corrected by computing the relative focal lengths of detectors 1 and 3 with respect to detector 2. Two tests were conducted to verify the accuracy of the adjustment procedure. Average root-mean-square (RMS) errors of ±10.5 m in the latitude direction and ±11.3 m in the longitude direction were obtained with a single surveyed GCP and a set of survey points used as checkpoints. The results of the tests show that the adjustment of full PAN scenes, as proposed in this paper, is an effective means of reducing the number of GCPs required for precise determination of ground coordinates.     

直线特征约束的资源3号卫星影像自检校平差

针对控制点获取较困难地区卫星影像定位精度不高的情况,对直线特征作为控制信息提升卫星影像定位精度进行了研究。以"像方直线上任意一点必然位于物方直线和投影中心所构成的平面"作为几何约束条件,通过对直线的参数化表示,建立了基于直线特征的共面模型;在该模型基础上,针对航天传感器的成像特点,分析建立了8标定参数的内方位元素模型和简化的外方位元素模型,最终构建了直线特征约束的卫星影像自检校平差模型。利用资源3号(ZY-3)卫星获取的华盛顿地区数据对构建的平差模型进行实验验证。结果表明,该模型能够解决缺乏地面控制点地区影像定位精度差的问题,可达到与常规自检校平差相同量级的精度。     

基于单位四元数的机载三线阵影像光束法平差

为克服欧拉角在空间方位的描述和插值中的局限性,采用单位四元数来描述相机的姿态,推导了四元数描述的共线条件方程。在此基础上,提出了将四元数球面线性插值(Slerp)引入到三线阵影像定向片法平差的思想,通过利用Slerp公式进行相机姿态的匀速插值,建立了基于单位四元数的三线阵影像平差的数学模型并进行了线性化。两套ADS40数据的试验结果表明,在区域四角布设平高控制点的情况下,基于Slerp模型的定向片光束法平差在平面和高程方向均可取得优于1个地面像元(GSD)的定位精度,是三线阵相机检校和空中三角测量较理想的技术手段。     

Sea WiFS与AVHRR资料自动几何配准

研究了一种自动几何配准的方法,来实现多时相的卫星资料和不同遥感资料之间的几 配准。利用海岸线自动选取ＧＣＰ的点,借助相关松弛法录找同名点,且有判别机制来保证ＧＣＰ的正确性,可以方便地得到分布密集的ＧＣＰ值。同时研究了二元ｎ次方程组和ＧＣＰ数目与配维精度的关系,得到ＧＣＰ数目的增加可明显提高几何配准精度。利用该方法对ＳｅａＷｉＦＳ和ＡＶＨＲＲ资料进行了几何配准,可以提高几何配准的精度和节省机时,为遥     

Principle, software and experiment of GPS-supported aerotriangulation

1 IntroductionAs is now well known, the high accurate point de-termination with airborne remOe sensing data hasalways ben one of the most fundaxnental prObletns..in aerial photOgrammtry. According to the princi-ple of the geOmtry reversal in photOgramrntry,the interior and exterior orientation elements ofaerial phOtOgraphs must first be known in order toreconstnJct the measuring stereo geometric medels.For the past 60 years, however, the interior orienta-tion parameters of carnera were main…     

利用ERDAS IMAGINE进行影像的几何精校正

几何精校正是利用地面控制点(GCP)对遥感影像进行的几何校正。用ERDAS IMAGINE软件进行几何精校正，关键在于相关模型参数设置、控制点输入和几何精校正。影响几何精校正的因素，主要表现在GCP的数量、分布和定位精度。此外校正方法不同，影像的纠正精度也不同。     

提高卫星三线阵CCD影像空中三角测量精度及摄影测量覆盖效能

利用数字模拟方法,进一步探讨了类似MOMS-02参数的卫星三线阵CCD影像单航线、航线首末4角隅设一个控制点(以下简写为单航线4控点)的空中三角测量高程精度低的问题。研究得出,宽高比特别小(1:9)只是原因之一,更主要的因素还在于平差整过程数学关系带有近似性(包括EFP法和定向片法)。提出了改善精度的措施,并拟订了提高卫星三线阵CCD影像空中三角测量精度及摄影测量覆盖效能的系统。模拟计算表明,航线长度可以≥2B,在有外方位元素或无外方位元素少量控制点条件下,不论二线交会区,还是三线交会区均可达到高程精度为6m的摄影测量成果。     

资源三号卫星三线阵影像自检校区域网平差

利用卫星的辅助数据构建资源三号卫星影像的严格几何模型。以此为基础,考虑镜头光学畸变、像元尺寸变化和CCD旋转变化等因素的影响,构建附加参数模型;     

Geopositioning Accuracy of Ikonos Imagery: Indications from Two Dimensional Transformations

Earth observation satellites with 1m resolution, such as Space Imaging's Ikonos system, offer the photogrammetric and remote sensing communities a significant new means for geospatial information collection. These satellites possess the potential for pixel-level geopositioning precision and promise timely, highly automated generation of two dimensional (2D) and three dimensional (3D) spatial information products. This paper concentrates on the pursuit of optimal accuracy and considers an essential first step in the evaluation of the Ikonos imaging system, namely the metric integrity of the sensor system. In the absence of sensor calibration information (the camera model), an empirical evaluation approach has been adopted. This involves an assessment of 2D transformations between image and planar object space. It is shown that based on results obtained in the Melbourne Ikonos Testfield, 2D geopositioning to 0.5 m accuracy is possible from the base-level "Geo"product when a modest amount of good quality ground control is available and sub-pixel image mensuration is achieved. These findings are applicable to both near-nadir imagery and oblique stereo images. Moreover, the results obtained suggest that there are no significant geometric perturbations in the sensor system and initial image processing, which augurs well for the successful application of non-collinearity based 3D orientation and triangulation models for Ikonos imagery.     

基于Kalman滤波的InSAR基线估计方法

针对目前SAR干涉测量中基线估计现存的问题,提出了利用Kalman滤波和配准参数进行基线估计的方法.所提出的方法具有不需地面控制点、不受地形限制和不依赖于轨道参数等优点,并可以估计时变的基线参数.利用南京地区的ERS-1/2 tandem数据进行了试验研究,并对提出的方法进行了验证.结果表明,在精确的卫星轨道数据和地面控制点不能获取时,所提出的方法仍能有效地估计InSAR基线.这在一定程度上补偿了轨道偏移带来的误差,为获取高精度的DEM奠定了基础.     

An improved approach for the production of satellite-based geospatial reference imagery

Abstract

An innovative and practical satellite image product is described that is ideal for applications in Northern Canada because of its wide area coverage and mapping-quality features. This product is generated from a new procedure developed at the Canada Centre for Remote Sensing (CCRS) for processing Landsat 7 imagery, and by extension, imagery from other Earth Observation satellites. By working with multiple satellite passes, each containing the equivalent of multiple scenes, the new procedure could dramatically reduce the turn-around time for generating georeferenced image products, and also increase their geometric and radiometric accuracy compared to those produced by the current methods. The objective of the process has been to generate satellite image mosaics covering large areas (e.g. >500 000 km²) with uniformly distributed errors at sub-pixel resolution. The paper discusses the theoretical basis of a photogrammetric adjustment for satellite imagery and the results obtained from several tests. The process is generic, involving a sensor model, a satellite orbit model and ground control information; thus it may be easily adapted to any satellite that allows for repeat coverage with overlapping paths. By performing an adjustment to correct the satellite position and attitude data prior to the production of orthoimage products, it is possible to create a mosaic with a single resampling process which minimises both the radiometric and geometric resampling artifacts. The results from three separate tests are presented, along with a discussion of the procedures that were followed in each case. All three tests have successfully demonstrated that sub-pixel sample size errors may be consistently obtained over large areas. A by-product process developed to support the measurement of ground control point coordinates for the satellite adjustment was the automatic matching of geographic features such as lakes and islands in vector data format. This has been a significant development in that it has eliminated manual intervention in the measurement of these features in the imagery, allowing the ground control for entire passes containing several scenes to be obtained in minutes instead of hours.     

Comparison of four UAV georeferencing methods for environmental monitoring purposes focusing on the combined use with airborne and satellite remote sensing platforms

This work is aimed at the environmental remote sensing community that uses UAV optical frame imagery in combination with airborne and satellite data. Taking into account the economic costs involved and the time investment, we evaluated the fit-for-purpose accuracy of four positioning methods of UAV-acquired imagery: 1) direct georeferencing using the onboard raw GNSS (GNSSNAV) data, 2) direct georeferencing using Post-Processed Kinematic single-frequency carrier-phase without in situ ground support (PPK1), 3) direct georeferencing using Post-Processed Kinematic double-frequency carrier-phase GNSS data with in situ ground support (PPK2), and 4) indirect georeferencing using Ground Control Points (GCP). We tested a multispectral sensor and an RGB sensor, onboard multicopter platforms. Orthophotomosaics at <0.05 m spatial resolution were generated with photogrammetric software. The UAV image absolute accuracy was evaluated according to the ASPRS standards, wherein we used a set of GCPs as reference coordinates, which we surveyed with a differential GNSS static receiver. The raw onboard GNSSNAV solution yielded horizontal (radial) accuracies of RMSEr≤1.062 m and vertical accuracies of RMSEz≤4.209 m; PPK1 solution gave decimetric accuracies of RMSEr≤0.256 m and RMSEz≤0.238 m; PPK2 solution, gave centimetric accuracies of RMSEr≤0.036 m and RMSEz≤0.036 m. These results were further improved by using the GCP solution, which yielded accuracies of RMSEr≤0.023 m and RMSEz≤0.030 m. GNSSNAV solution is a fast and low-cost option that is useful for UAV imagery in combination with remote sensing products, such as Sentinel-2 satellite data. PPK1, which can register UAV imagery with remote sensing products up to 0.25 m pixel size, as WorldView-like satellite imagery, airborne lidar or orthoimagery, has a higher economic cost than the GNSSNAV solution. PPK2 is an acceptable option for registering remote sensing products of up to 0.05 m pixel size, as with other UAV images. Moreover, PPK2 can obtain accuracies that are approximate to the usual UAV pixel size (e.g. co-register in multitemporal studies), but it is more expensive than PPK1. Although indirect georeferencing can obtain the highest accuracy, it is nevertheless a time-consuming task, particularly if many GCPs have to be placed. The paper also provides the approximate cost of each solution.     

缺少控制点的卫星遥感对地目标定位

从单线阵推扫式传感器的成像机理出发，利用6个卫星轨道开普勒参数和3个传感器姿态角建立了推扫式卫星遥感影像坐标与其地面点在地心坐标系下的坐标关系式，即构像方程。按照所建立的构像方程，对某地区一景SPOT-5影像进行对地目标定位，获得了实地上83．392m的平面精度；利用单个地面控制点对卫星轨道开普勒参数和传感器姿态实施调整后，目标定位精度提高到14．217m。试验证实，所建立的构像方程是正确的,在卫星遥感对地目标定位中有较好的应用前景。     

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.     

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。     

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。