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UAT ADS-B Data Anomalies and Effect of Flight Parameters in Dropout

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Submitted:

13 April 2018

Posted:

13 April 2018

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Abstract
An analysis of the performance of Automatic Dependent Surveillance-Broadcast (ADS-B) data received from the Grand Forks, North Dakota International Airport was carried in this study. The purpose was to understand the vulnerabilities of UAT ADS-B system and recognize the effects on present and future Air Traffic Control (ATC) operation. At present unmanned aircraft systems (UAS) and autonomous air traffic control (ATC) towers are being integrated into the aviation industry. As a fundamental component of future surveillance system, the anomalies and vulnerabilities of ADS-B system need to be identified to enable a fully utilized airspace with enhanced situational awareness. The anomaly detection of ADS-B messages was based on the Federal Aviation Administration’s (FAA) ADS-B performance assessment report. Data investigation revealed ADS-B message suffered from different anomalies including drop out; missing payload; data jump; low confident data and altitude discrepancy. Among all the anomalies detected message discontinuation or dropout was found to be most frequent. Considering the potential danger being imposed, an in-depth analysis was carried out to characterize message dropout. Three flight parameters were selected to investigate their effect on drop out. Statistical analysis identified that altitude affected drop out more than any other flight parameters.
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Subject: Engineering  -   Control and Systems Engineering
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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