Small unmanned aircraft systems (UAS) are rapidly gaining popularity. As the excitement surrounding small UAS has grown, the Federal Aviation Administration (FAA) has repeatedly stated that UAS must be capable of detecting and avoiding manned and unmanned aircraft. In developing detect-and-avoid (DAA) technology, one of the key challenges is identifying a suitable sensor. Automatic Dependent Surveillance-Broadcast (ADS-B) has gained much attention in both the research and consumer sectors as a promising solution. While ADS-B has many positive characteristics, further analysis is necessary to determine if it is suitable as a DAA sensor in environments with high-density small UAS operations. To further the understanding of ADS-B, we present a characterization of ADS-B measurement error that is derived from FAA regulations. Additionally, we analyze ADS-B by examining its strengths and weaknesses from the perspective of DAA on small UAS. To demonstrate the need and method for estimation of ADS-B measurements, we compare four dynamic filters for accuracy and computational speed. The result of the comparison is a recommendation for the best filter for ADS-B estimation. We then demonstrate this filter by estimating ADS-B measurements that have been recorded from the National Airspace System (NAS). We also present a novel long-range, convex optimization-based path planner for ADS-B-equipped small UAS in the presence of intruder aircraft. This optimizer is tested using a twelve-state simulation of the ownship and intruders.We also consider the effectiveness of ADS-B in high-density airspace. To do this we present a novel derivation of the probability of interference for ADS-B based on the number of transmitting aircraft. We then use this probability to document the need for limited transmit range for ADS-B on small UAS. We further leverage the probability of interference for ADS-B, by creating a tool that can be used to analyze self-separation threshold (SST) and well clear (WC) definitions based on ADS-B bandwidth limitations. This tool is then demonstrated by evaluating current SST and WC definitions and making regulations recommendations based on the analysis. Coupling this tool with minimum detection range equations, we make a recommendation for well clear for small UAS in ADS-B congested airspace. Overall these contributions expand the understanding of ADS-B as a DAA sensor, provide viable solutions for known and previously unknown ADS-B challenges, and advance the state of the art for small UAS.



College and Department

Ira A. Fulton College of Engineering and Technology; Mechanical Engineering



Date Submitted


Document Type





ADS-B, Automatic Dependent Surveillance-Broadcast, unmanned aircraft systems, UAS, UAV, detect and avoid, sense and avoid