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A Comprehensive Ionosphere Storm Data Analysis Method to Support LAAS Threat Model Development

机译:全面的电离层风暴数据分析方法,支持LAAS威胁模型开发

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Several recent papers have analyzed the potential threat of severe ionosphere spatial gradients on LAAS users [1-4]. To support this work, a comprehensive methodology has been developed to analyze WAAS Supertruth data as well as both raw and JPL-processed data from the IGS/CORS receiver network to search for anomalous gradients. Anomalous gradients that result from this method are used to populate and validate the LAAS ionosphere spatial gradient "threat model" that is used to determine the potential impact of ionosphere anomalies on LAAS users. This paper explains the ionosphere data analysis method in detail. This method includes two separate chains of analysis. One chain uses dual-frequency (L1 and L2) data that is post-processed by JPL to remove receiver inter-frequency biases as well as obvious receiver glitches. A search for the largest ionosphere spatial gradients (in terms of the apparent gradient "slope" in mm/km) is then performed, and the resulting observations are put through a screening process that confirms that the observed gradients are due to actual ionosphere gradients as opposed to other causes (e.g., incorrect L1-L2 bias estimates; unexplained measurement "jumps"). Surviving observations from this chain are then validated by an analysis of ionosphere rate of change using L1 codeminus-carrier only to insure that the apparent gradients are not due to receiver errors after recovery from loss of lock on L2. Observations confirmed to be due to ionosphere gradients are then analyzed further (using additional nearby receivers) to estimate the gradient width and propagation speed to the extent possible. This paper presents results for analyses conducted using this method for the October 29 - 30 and November 20, 2003 ionosphere storms over CONUS. These days appear to represent the worst ionosphere storms experienced in CONUS since WAAS and IGS/CORS data became available. Preliminary results for several earlier storms in CONUS that might also be of concern to LAAS are also presented.
机译:最近有几篇论文分析了LAAS用户[1-4]严重的电离层空间梯度的潜在威胁。为了支持这项工作,一套全面的方法已经发展到分析WAAS Supertruth数据以及从IGS / CORS接收机网络RAW和JPL处理的数据来搜索异常梯度。异常梯度从该方法中该结果用于填充和验证LAAS电离层,其用于确定电离层的异常上LAAS用户的潜在影响空间梯度“威胁模型”。本文详细解释了电离层数据分析方法。该方法包括分析两个独立的链。一种链采用双频率(L1和L2),其由JPL后处理以除去接收机频率间的偏差,以及明显接收机毛刺数据。一种用于最大电离层空间梯度搜索(在明显的梯度以mm / km的“斜率”而言),然后执行,并且所得到的观察结果通过筛选过程把该确认所观察到的梯度是由于实际电离层梯度作为相对于其他的原因(例如,不正确的L1-L2偏差估计;不明原因的测量“跳跃”)。从这个链存活观察然后通过使用L1 codeminus载波变化的电离层率的分析,验证只以确保该表观梯度不是由于从L2失锁后恢复接收器的错误。观察证实是由于电离层,然后梯度进行分析进一步(使用附加的附近接收器),从而估算梯度宽度和传播速度尽可能。 30和2003年11月20日,电离层风暴在美国本土 - 使用这种方法为10月29日进行了本文呈现的结果进行分析。这些天似乎代表在美国本土遭受了最严重的电离层暴,因为WAAS和IGS / CORS数据变得可用。在美国本土几个早期的风暴,可能也是关注的LAAS初步结果也。

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