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Robust GNSS Differential Processing for All Baselines

机译:所有基准的强大GNSS差分处理

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Applied Research Laboratories, The University of Texas (ARL:UT) has developed a differential processor titled "ProcNet" to support high-precision short-baseline surveys performed by the National Geospatial-Intelligence Agency (NGA) for the Air Force's Holloman High Speed Test Track. ProcNet eliminates many of the limitations of the legacy differential processor titled "DDBase" that is currently employed, including rigorously processing dual frequency observations and allowing the use of ANTEX antenna models. ProcNet provides improved robustness and performance as compared to DDBase, particularly when dual frequency observations are used. Initial analysis indicates short baseline precision improvements ranging from 30 to 50%, with a notable precision increase in the vertical direction. Robustness is improved by employing undifferenced GNSS observations via a rearrangement of the observation equations instead of the traditional approach using double differenced values. ProcNet is part of a new unified processing architecture developed at ARL:UT that provides both Precise Point Positioning and Differential Positioning capabilities. As a result of the new architecture, ProcNet can employ site displacement and measurement models that are traditionally used for Precise Point Positioning solutions to enable better relative solutions for long baselines.
机译:德克萨斯大学(ARL:UT)应用研究实验室开发了一个差动处理器,标题为“Procnet”,以支持国家地理空间 - 情报局(NGA)为空军霍洛斯高速测试执行的高精度短基线调查追踪。 PROCNET消除了当前采用“DDBase”的传统差分处理器的许多限制,包括严格处理双频观察并允许使用Antex天线模型。 PARCNET与DDBase相比,提供了改进的鲁棒性和性能,特别是当使用双频观察时。初始分析表明,短的基线精度改善范围为30%至50%,垂直方向具有显着的精度。通过使用双重差异值的检测方程的重新排列而不是传统方法采用未分化的GNSS观察来改善鲁棒性。 PROCNET是在ARL:UT上开发的新统一处理架构的一部分,提供精确点定位和差分定位能力。由于新架构的结果,PROCNET可以采用传统上用于精确点定位解决方案的站点位移和测量模型,以实现长基线的更好的相对解决方案。

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