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Exploiting GNSS signal structure to enhance observability

机译：利用GNSS信号结构增强可观察性

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摘要

There are a number of different error sources, such as multipath and thermal noise, which corrupt satellite navigation waveforms from their theoretical structure. However, even under ideal conditions the broadcast signals have some degree of deformation as a result of the practical individual hardware implementation. For the most demanding users of satellite navigation, such as aircraft navigation and landing systems, it is important to characterize the nominal signal structure in order to detect minimal variations resulting from hardware-based errors. Thus far such precorrelation Global Navigation Satellite System (GNSS) signal quality monitoring has been performed through high gain antennas, which allow for raising the GNSS spectrum above the thermal noise floor and observing the structure of the signal directly at the front end output. This paper describes a new approach to achieve such observability based on signal processing techniques, such as dithering and averaging, which leverage the repetitive nature of the GNSS signal. The paper presents how these techniques can drastically improve the signal-to-noise ratio (SNR) in postprocessing, allowing for the direct analysis of GNSS signals using traditional front end designs and conventional antennas. Results are predicted using the appropriate theory and validated using data collected from the Global Positioning System (GPS).
机译：存在许多不同的误差源，例如多径误差和热噪声，它们从理论结构上破坏了卫星导航波形。然而，即使在理想条件下，由于实际的单独硬件实现，广播信号也具有一定程度的变形。对于卫星导航的最苛刻的用户（例如飞机导航和着陆系统），表征标称信号结构非常重要，以便检测出基于硬件的错误导致的最小变化。到目前为止，已经通过高增益天线执行了这种预相关的全球导航卫星系统（GNSS）信号质量监视，这可以将GNSS频谱提高到热本底噪声之上，并直接在前端输出端观察信号的结构。本文介绍了一种基于信号处理技术（例如抖动和平均）的新方法，该技术利用了GNSS信号的重复性，从而达到了这种可观察性。本文介绍了这些技术如何在后处理中大幅改善信噪比（SNR），从而允许使用传统的前端设计和传统的天线直接分析GNSS信号。使用适当的理论对结果进行预测，并使用从全球定位系统（GPS）收集的数据进行验证。

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