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Real time performance monitoring and noise analysis in an operational WAM system

机译:可操作的WAM系统中的实时性能监视和噪声分析

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Wide Area Multilateration (WAM) systems are complex systems and suffer from several typse of interference that vary over time. To ensure reliable operation and high data quality, a continuous verification approach is needed. The typical quality metrics in Asterix Cat 20 data are not fully sufficient to determine the operational capability of a WAM system. Different parameters are needed additionally to characterise system performance. This approach also allows detecting small changes and degradations of the system over time that may not only be caused by system intrinsic effects, but also by external evolution, like RF environment, different traffic patterns and equipment mix, or different surveillance infrastructure. This paper shows crucial low level parameters and their real time evaluation within the operational system like •propagation path effects (especially for low level targets) •probability of telegram reception and error rate •interrogation efficiency •accuracy and outlier rate of timing measurements •system synchronisation monitoring •measurement and track noise characterisation •comparison against other metrics (e.g. ADS-B and the side effects thereof) •aircraft transponder anomaly monitoring Based on these analyses, optimized data output strategies are proposed how to convey the maximum amount of information into Asterix reports for further processing. A more detailed definition of some fields will become necessary, especially when the MLAT data is fed into a sensor data fusion.
机译:广域多纬度(WAM)系统是复杂的系统,并且会受到几种干扰的影响,这些干扰会随时间而变化。为了确保可靠的操作和较高的数据质量,需要一种连续的验证方法。 Asterix Cat 20数据中的典型质量指标不足以确定WAM系统的操作能力。此外,还需要不同的参数来表征系统性能。这种方法还可以检测系统随时间的细微变化和降级,这些变化和降级不仅可能是由系统固有影响引起的,而且还可能是由外部演变(例如RF环境,不同的流量模式和设备组合或不同的监视基础结构)引起的。本文展示了关键的低层参数及其在操作系统中的实时评估,例如•传播路径效应(尤其是低层目标)•电报接收和错误率的可能性•询问效率•定时测量的准确性和异常率•系统同步监视•测量和跟踪噪声特征•与其他度量(例如ADS-B及其副作用)的比较•飞机应答器异常监视基于这些分析,提出了优化的数据输出策略,该方法建议如何将最大量的信息传达到Asterix报告中进行进一步处理。某些字段的更详细定义将变得很有必要,尤其是当MLAT数据输入到传感器数据融合中时。

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