集群微波遥感卫星稀疏随机分布构型成像

随着对空中/空间目标实时高分辨探测成像的需求日益增长,利用新概念集群体制的微波遥感卫星实现该需求的方式越来越受到重视。针对目前和未来一段时间,我国遥感卫星组网构型呈现的稀疏随机典型特征,本文提出一种基于压缩感知理论的高分辨目标实时成像方法。该方法依托卫星自身特点(稀疏随机构型等约束条件),在不改变目前多颗在轨运行微波遥感卫星相对集群分布状态的前提下,为实现目标的高分辨实时探测提供了一条可能的途径。     

面向应用的CBERS-02星高分辨率相机成像数值模拟技术框架

技术框架研究的目标是准确仿真卫星高分辨率相机成像过程中辐射和几何质量的下降情况,从应用方的角度建立评价高分辨率卫星相机在国土资源领域的应用潜力和技术框架,并以CBERS-02B星HR相机在轨成像模拟为例进行了原理验证,同时对今后以国土资源应用评价为目标的高分辨率相机在轨成像模拟改进方案提出了建议。     

OpenGL虚拟相机模拟摄影测量二次成像

利用OpenGL虚拟相机重现摄影测量过程,借助OpenGL中的高级函数对已知摄影参数的影像进行二次成像模拟,建立OpenGL透视成像各函数参数与摄影测量内外方位元素之间的定量表达式,实现利用OpenGL对航空摄影测量获取影像过程的成像模拟。试验结果表明,在已知空间物体的三维信息和摄影参数的基础上,获取的空间物体二次成像结果与UCD相机获取的航空影像完全叠合。     

集群并发环境下大规模矢量数据负载均衡算法

为了提高集群环境下网络地理信息系统(WebGIS)大规模矢量数据的并发访问性能,提出了集群并发环境下大规模矢量数据内容网格化负载均衡算法,研究了大规模矢量数据内容网格化方法,集群并发访问时内容网格的自动识别、分析、聚合、反馈算法,实现了面向任务的负载均衡。实验表明,本算法能在大规模、高强度的矢量数据提取和显示中均衡地分发请求,使集群服务器充分发挥其优势从而获得最小的请求响应时间。     

集群环境下的复合最小不连续相位解缠算法

提出了一种集群环境下的复合最小不连续相位解缠算法。首先主线程根据计算资源数将原始缠绕相位分为规则小块,并将未解缠相位块发送至空闲计算节点进行解缠。单块缠绕相位图解缠时,先计算相位质量图,并将缠绕相位分为高低质量区域,然后采用质量引导与最小不连续相结合的复合相位解缠策略进行解缠,最后将解缠结果和区域分割结果发送回主线程。完成所有分块缠绕相位解缠后,主线程在不同解缠相位块边界及其与边界相邻的低质量区域进行最小不连续优化来获取最终的解缠相位。通过集群环境下的并行相位解缠试验,验证了所提算法的正确性和高效性。     

集群环境下网络空间信息服务高性能内存缓存方法

针对现有集群环境下网络空间信息服务性能优化策略的特点和弊端进行分析,提出集群环境下网络空间信息服务高性能内存缓存方法,重点研究网络空间信息服务高性能内存缓存体系结构、可扩展的高性能内存缓存控制设计、内存缓存工作流程,最终实现集群环境下基于内存缓存的网络空间信息服务的加速,解决传统WebGIS模型中存在的I/O瓶颈问题。最后,使用五个常用的网络空间信息服务类型对文中提出的方法进行实验,结果证明与传统的集群环境下网络空间信息服务相比,文中设计的网络空间信息服务高性能内存缓存方法能够有效地提升服务并发处理能力,具有良好的可扩展性。     

月球卫星三线阵CCD影像EFP光束法空中三角测量

本文对月球卫星摄影三线阵CCD影像的EFP(等效框幅相片)光束法空中三角测量作两种处理:一是与现行摄影测量常用的将平差转到切面坐标系进行,二是在摄影测量坐标系内,长航线自由网EFP光束法平差利用三线CCD推扫特点,在EFP平差中增加对前、后视影像的相机主距的附加改正项,用以补偿由于球面曲率产生的前、后视影像比例尺的差异,平差得到的是平面基准的地面坐标及外方位元素的平差值。前者计算,数学上严格,但长航线要适当分段为切面处理;后者计算数学上有近似性,可方便地用于估算卫星姿态变化率,或作地面模型的几何反演等实验研究。利用嫦娥一号获取的第一条航线,并给出相应的结果。     

基于中间件的高分辨率卫星影像正射纠正的分布式处理

当前摄影测量系统软件正向分布式并行处理方向发展,目前大家研究比较多的是在高性能计算机系统(如刀片机)下进行并行数据处理,而研究普通PC机集群分布式并行处理数据则相对比较少。因此本文在多PC机环境下按照分布式处理思想提出了一种对高分辨率卫星影像进行正射纠正的基于中间件模式的分布式并行处理系统,着重叙述了该系统的组成以及任务调度中的相关处理等问题,并在实践中验证了它的可行性。     

On RPC model of satellite imagery

The RPC model has recently raised considerable interest in the photogrammetry and remote sensing community. The RPC is a generalized sensor model that is capable of achieving high approximation accuracy. Unfortunately, the computation of the parameters of RPC model is subject to the initial of the parameter in all available liteature. An algorithm for computation of parameters of RPC model without initial value is presented and tested on SPOT-5, CBERS-2, ERS-1 imageries. RPC model is suitable for both push-broom and SAR imagery.     

On RPC model of satellite imagery

IntroductionThe rational polynomial coefficient ( RPC)model is a generalized sensor model that is usedas an alternative solution for the rigorous sensormodel for IKONOS of the spacei maging. As thenumber of sensors increases along with greatercomplexity ,…     

Pinpointing source of Mekong and measuring its length through analysis of satellite imagery and field investigations

For centuries, explorers and scientists from different countries had made their own conclusions on the source of the Mekong. However, the geographic source of the Mekong is still arguable because of the complexity of the Mekong source water system, inaccessible environment and the varied technologies used by those explorers and scientists. The satellite remote sensing technology has been used to pinpoint the source of the Mekong, associated with the on-the-spot investigations made by the authors in June 1999 and September 2002. The actual length of the Mekong has also been calculated.     

Epipolar resampling of linear pushbroom satellite imagery by a new epipolarity model

This paper presents a practical epipolarity model for high-resolution linear pushbroom satellite images acquired in either along-track or cross-track mode, based on the projection reference plane in object space. A new method for epipolar resampling of satellite stereo imagery based on this model is then developed. In this method, the pixel-to-pixel relationship between the original image and the generated epipolar image is established directly by the geometric sensor model. The approximate epipolar images are generated in a manner similar to digital image rectification. In addition, by arranging the approximate epipolar lines on the defined projection reference plane, a stereoscopic model with consistent ground sampling distance and parallel to the object space is thus available, which is more convenient for three-dimensional measurement and interpretation. The results obtained from SPOT5, IKONOS, IRS-P5, and QuickBird stereo images indicate that the generated epipolar images all achieve high accuracy. Moreover, the vertical parallaxes at check points are at sub-pixel level, thus proving the feasibility, correctness, and applicability of the method.     

多条带WorldView卫星图像几何定位精度分析

本文针对多个条带WorldView卫星图像,研究了基于有理函数模型的附加参数区域网平差方法,对高分辨率卫星图像定位精度进行了详细分析。青海地区WorldView卫星图像试验结果表明:无地面控制点时,多条带整体区域网定位结果优于各个条带单独平差结果,区域网平差方法结果优于直接前方交会方法;有地面控制点时,多条带区域网平差结果与各个条带单独平差结果相当,且沿路线不大于10km布设一个地面控制点,其精度可满足1∶2000比例尺加密精度要求,可用于公路初步设计。     

Accuracy assessment of high resolution satellite imagery orientation by leave-one-out method

Interest in high-resolution satellite imagery (HRSI) is spreading in several application fields, at both scientific and commercial levels. Fundamental and critical goals for the geometric use of this kind of imagery are their orientation and orthorectification, processes able to georeference the imagery and correct the geometric deformations they undergo during acquisition. In order to exploit the actual potentialities of orthorectified imagery in Geomatics applications, the definition of a methodology to assess the spatial accuracy achievable from oriented imagery is a crucial topic.In this paper we want to propose a new method for accuracy assessment based on the Leave-One-Out Cross-Validation (LOOCV), a model validation method already applied in different fields such as machine learning, bioinformatics and generally in any other field requiring an evaluation of the performance of a learning algorithm (e.g. in geostatistics), but never applied to HRSI orientation accuracy assessment.The proposed method exhibits interesting features which are able to overcome the most remarkable drawbacks involved by the commonly used method (Hold-Out Validation — HOV), based on the partitioning of the known ground points in two sets: the first is used in the orientation–orthorectification model (GCPs — Ground Control Points) and the second is used to validate the model itself (CPs — Check Points). In fact the HOV is generally not reliable and it is not applicable when a low number of ground points is available.To test the proposed method we implemented a new routine that performs the LOOCV in the software SISAR, developed by the Geodesy and Geomatics Team at the Sapienza University of Rome to perform the rigorous orientation of HRSI; this routine was tested on some EROS-A and QuickBird images. Moreover, these images were also oriented using the world recognized commercial software OrthoEngine v. 10 (included in the Geomatica suite by PCI), manually performing the LOOCV since only the HOV is implemented.The software comparison guaranteed about the overall correctness and good performances of the SISAR model, whereas the results showed the good features of the LOOCV method.     

The georeferencing of RASAT satellite imagery and some practical approaches to increase the georeferencing accuracy

RASAT Earth Observation Satellite is the second remote sensing satellite of The Scientific and Technological Research Council of Turkey (TUBITAK) Space Technologies Search Institute (TUBITAK Space). Generally, the first step to utilize the satellite imagery in GIS applications is the accurate geometric correction of the imagery. But, the geometric correction process of RASAT images is somewhat difficult due to insufficient orbit data and lack of satellite imagery processing software with RASAT model. Although the geolocation of RASAT images is investigated in some recent studies, subpixel accuracies cannot be achieved. In this study, different geometric correction methods and combination of them are tested with a more interactive workflow that uses the results of other approaches. Results show that these approaches can be used for the geometric correction of RASAT like pushbroom satellite images with insufficient orbit data and better geolocation accuracies can be achieved by different geometric correction approaches.     

基于星敏感器的遥感卫星姿态确定仿真系统实现

为了在地面实验中研究基于星敏感器的遥感卫星姿态自主确定相关技术,本文在基于星敏感器的遥感卫星姿态确定半物理仿真系统工作原理的基础上,对整个系统的总体及各模块进行了详细的设计,最后建立了该半物理仿真系统,为多种目的服务。整个系统的建立能够为基于星敏感器的遥感卫星姿态确定技术新方法、新思路和新方案的研究提供参考。