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ENSEMBLE TIME IN GNSS - PERFORMANCE REQUIREMENTS AND ALGORITHM TESTS

机译:集合时间在GNSS中 - 性能要求和算法测试

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Any Global Navigation Satellite System (GNSS) relies on a highly stable and reliable System Time that has to meet high-performance requirements to enable GNSS services suitable for navigation and timing communities. The challenge is to guarantee this high performance continuously. The Kalman filter algorithm implemented in GPS, called the GPS Composite Clock, is a mature method to generate such a highly robust System Time. The algorithm estimates the time offsets of every individual clock to the so-called implicit mean, which is a common component in all clock estimates. The common component offers the functionality of System Time and is understandable as a weighted average out of all ensemble clock readings. GPS Composite Clock performance is analyzed by simulations of a "light" GNSS configuration with 10 rubidium satellite clocks, including deterministic drift, six ground cesium clocks, and two ground active hydrogen masers. Besides evaluating the stability of an error-free clock constellation to define the regular performances, the behavior of the algorithm is investigated considering different operational scenarios: exclusion of clocks from the GNSS ensemble and occurrence of clock feared events (frequency steps in rubidium satellite clocks and ground H-masers).
机译:任何全球导航卫星系统(GNSS)都依赖于高度稳定和可靠的系统时间,这些系统必须满足高性能要求,以使适用于导航和定时社区的GNSS服务。挑战是不断保证这种高性能。在GPS中实现的卡尔曼滤波器算法称为GPS复合时钟,是一种成熟的方法,用于生成这种高度稳健的系统时间。该算法估计每个单个时钟到所谓的隐式均值的时间偏移,这是所有时钟估计中的公共组件。通用组件提供系统时间的功能,并且可以作为所有集合时钟读数的加权平均值可以理解。通过使用10个铷卫星钟表的“光”GNSS配置的模拟来分析GPS复合时钟性能,包括确定性漂移,六个接地铯钟和两个接地活性氢气剂。除了评估无差错时钟星座的稳定性来定义常规性能之外,考虑到不同的操作场景,研究了算法的行为:从GNSS集合中排除时钟和时钟恐惧事件的发生(铷卫星时钟中的频率步骤)地面H-Masers)。

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