Start Date
5-12-2015 3:24 PM
Description
This paper presents a time-based path planning optimizer for separation assurance for unmanned aerial systems (UAS). Given Automatic Dependent Surveillance-Broadcast (ADS-B) as a sensor, position, velocity, and identification information is available at ranges on the order of 50 nautical miles. Such long-range intruder detection facilitates path planning for separation assurance, but also poses computational and robustness challenges. The time-based path optimizer presented in this paper provides a path planning method that takes advantage of long-range ADS-B information and addresses the associated challenges. It is capable of robust, long-range path planning and is computationally efficient enough to run successively for increased robustness. The ultimate result of this research is a time-based path planner that is suitable for a Sense and Avoid solution on small UAS in the National Airspace System.
Automatic Dependent Surveillance-Broadcast for Sense and Avoid on Small Unmanned Aircraft
This paper presents a time-based path planning optimizer for separation assurance for unmanned aerial systems (UAS). Given Automatic Dependent Surveillance-Broadcast (ADS-B) as a sensor, position, velocity, and identification information is available at ranges on the order of 50 nautical miles. Such long-range intruder detection facilitates path planning for separation assurance, but also poses computational and robustness challenges. The time-based path optimizer presented in this paper provides a path planning method that takes advantage of long-range ADS-B information and addresses the associated challenges. It is capable of robust, long-range path planning and is computationally efficient enough to run successively for increased robustness. The ultimate result of this research is a time-based path planner that is suitable for a Sense and Avoid solution on small UAS in the National Airspace System.