Severity and Effect of ADS-B Message Drop Out in Detect and Avoid of Unmanned Aircraft System

This work analyzes the severity and risk associated with Automatic Dependent Surveillance- Broadcast (ADS-B) message drop out in Detect and Avoid (DAA) for Unmanned Aircraft System (UAS). Performance assessment of UAT ADS-B message implies that ADS-B may fail to update within specified update interval which is referred to as drop out. UAT ADS-B is a fundamental surveillance sensor for both class 1 and class 2 DAA. Message discontinuation or drop out has been found as one of the anomalies of the ADS-B system. Hence to ensure safe and reliable operation of UAS; hazard and risk assessment is essential. The severity and risk associate with drop out was assessed in this work. The drop out induced in the simulation was identified from the UAT ADS-B archived data. The data were received from the Grand Forks International Airport, North Dakota. Simulation results depicts that both the duration of drop out and DAA look-ahead time effect the safe operation of UAS and as a repercussion result in degraded situational awareness. The risk was also quantified with risk matrix in order to measure the overall threat. A system level analysis was carried out to recognize the potential reasons behind ADS-B drop out.