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Geolocation with error analysis using imagery from an experimental spotlight SAR.

机译:使用来自实验聚光灯SAR的图像进行误差分析的地理位置。

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This dissertation covers the development of a geometry-based sensor model for a specific monostatic spotlight synthetic aperture radar (SAR) system---referred to as the ExSAR (for experimental SAR). This sensor model facilitates single- and multiple-image geopositioning with error analysis. It allows for the use of known ground control points in refining the collection geometry parameters (a process called image resection) and for the subsequent geopositioning of other points using the resected image. Theoretically, the model also allows for the potential recovery of bias-like, persistent errors common across multiple images. The model also includes multi-image correspondence equations to aid in the cross-image identification of conjugate points.;The sensor model development begins with a generic, theoretical approach to the modeling of spotlight SAR. A closed-form solution to the range and range-rate condition equations and the corresponding error propagation equation are presented. (The SAR condition equations have traditionally been solved iteratively.) The application of the closed-form solution in the image-to-ground and ground-to-image transformations is documented. The theoretical work also includes a preliminary error sensitivity analysis and a treatment of the spotlight SAR resection process.;The ExSAR-specific model is established and assessed with an extensive set of images collected using the experimental radar over arrays of ground control points. Using this set, the imagery metadata elements are assessed, and the optimal element set for geopositioning is determined. The ExSAR imagery is shown to be transformed to the ground plane in only one dimension.;The eventual ExSAR sensor model is used with known elevations and single-image geopositioning to show a horizontal accuracy of 8.23 m (rms). With resection using five ground-surveyed control points per image, the horizontal accuracy of reserved check points is 0.45 m (rms). Resections using the same points, but recovering fewer geometry parameters produced nearly equal accuracies.;Three-dimensional geopositioning was shown feasible using the model and multiple images. Correspondence curve equations were developed and tested. These define the expected location of a conjugate point in overlapping imagery.;This work includes extensive explanatory appendices, including preliminary work with bistatic SAR modeling. The experimental data set and MATLAB RTM code are available.
机译:本论文涵盖了针对特定的单基地聚光合成孔径雷达(SAR)系统-基于ExSAR(用于实验SAR)的基于几何的传感器模型的开发。该传感器模型有助于通过误差分析实现单幅和多幅图像的地理定位。它允许使用已知的地面控制点来完善收集几何参数(称为“图像后方交会”的过程),以及随后使用切除的图像对其他点进行地理定位。从理论上讲,该模型还可以潜在地恢复跨多个图像常见的类似偏差的持续性错误。该模型还包括多图像对应方程,以帮助对共轭点进行跨图像识别。传感器模型的开发始于对聚光SAR建模的通用理论方法。给出了范围和范围率条件方程以及相应的误差传播方程的闭式解。 (传统上,SAR条件方程式是迭代求解的。)记录了闭式解在图像到地面和地面到图像转换中的应用。理论工作还包括初步的误差敏感性分析和聚光SAR切除过程的处理。建立和评估ExSAR专用模型,并使用实验雷达在地面控制点阵列上收集的大量图像进行评估。使用该集合,可以评估图像元数据元素,并确定用于地理定位的最佳元素集。已显示ExSAR图像仅在一维上转换为地平面。最终的ExSAR传感器模型用于已知的高程和单图像地理定位,显示的水平精度为8.23 m(rms)。通过每个图像使用五个地面测量控制点进行切除,保留检查点的水平精度为0.45 m(rms)。使用相同点进行后方交会,但恢复较少的几何参数产生的精度几乎相等。开发并测试了对应曲线方程。这些定义了重叠图像中共轭点的预期位置。这项工作包括大量的解释性附录,包括双基地SAR建模的初步工作。提供了实验数据集和MATLAB RTM代码。

著录项

  • 作者

    Wonnacott, William Mark.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Engineering Aerospace.;Remote Sensing.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 530 p.
  • 总页数 530
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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