At DLR we are currently carrying out preliminary studies for an L-band SAR satellite mission called Tandem-L. This contribution illustrates some results obtained by integrating a performance analysis tool for d-InSAR applications into a mission simulator.ududThe Tandem-L SAR mission will measure and monitor over time a variety of parameters ranging from surface deformation (d-InSAR) to forest height and structure (Multi-baseline pol-InSAR), ice flows, ocean currents etc.ududThe current study is oriented towards the development of a systematic and extensive acquisition plan over the areas of interest for the different applications. Such an acquisition strategy is driven by the desire to give complete and consistent snapshots of a variety of dynamical processes taking place on Earth.ududGiven the variety of applications, the mentioned desired acquisition policy and the wide regions of interest, it is clear that the mission design faces a number of challenges in the allocation of system resources such as data volume and acquisition opportunities. Besides this we have to consider geographical conflicts between the various applications (e.g. seismic areas covered by forests).ududIn order to optimize the resource allocation we have developed for each application a performance model. We want to have predictions about the quality of intermediate and final products based on an acquisition scenario and instrument performance.ududFor the d-InSAR applications we based our performance analysis for image stacks on the hybrid Cramér-Rao bound [1] (single line of sight) and using well know formulas for the optimum linear combination of measurements for the multi-dimensional case (3D and 2D vector displacements).ududThese performance predictions are integrated into a mission simulator that can provide parameters for each available acquisition on a given point on the earth. Besides the acquisition dates the simulator outputs geometrical information such as look directions, incidence angles, baselines, resolution, plus NESZ and ambiguity level. All these parameters are inputs for the d-InSAR performance module.ududThe advantage of using such a simulator is that conflicts between different requirements are taken into account and the impact on the performance can be the immediately quantified.
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机译:在DLR,我们目前正在对称为TANDEM-L的L波段SAR SAR卫星使命进行初步研究。该贡献说明了通过将D-Insar应用程序的性能分析工具集成到任务模拟器中来获得的一些结果。 UD udthe串联-L SAR任务将测量和监控随着时间的各种参数,范围从表面变形(D-INSAR)森林高度和结构(多基线POL-INSAR),冰流,海洋电流等。 ud ud ud udthe目前的研究是通过对不同申请的兴趣领域进行系统和广泛的收购计划的发展。这样的收购策略是由在地球上进行的各种动态过程的完整和一致快照的愿望驱动。 ud Udgiven的各种应用程序,所附所需的收购政策和广泛的兴趣区域,很清楚特派团设计面临着多项挑战,在数据量和收购机会等系统资源分配中。除此之外,我们必须考虑各种应用之间的地理冲突(例如,森林覆盖的地震区域)。 ud udin命令优化我们为每个应用程序开发的资源分配是一种性能模型。我们希望根据采集方案和仪器性能对中间和最终产品质量进行预测。 UD UDFor D-Insar应用程序,我们基于对HybridCramér-Rao绑定的图像堆栈的性能分析[1](单线视线)和使用众所周知的公式,了解多维外壳的测量值(3D和2D矢量位移)。 UD Udthese预测集成到任务模拟器中,可以为每个可用的参数提供参数收购地球上的给定点。除了采集日期之外,模拟器输出几何信息,例如外观,入射角,基线,分辨率,分辨率以及模糊性水平。所有这些参数都是D-Insar性能模块的输入。 UD Ud使用此类模拟器的优势在于考虑不同要求之间的冲突,并且对性能的影响可以是立即量化的。
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