Sensor Scheduling for Airborne Multi-target Tracking with Limited Sensor Resources

Aerial surveillance systems have become an important aspect in a range of civilian and military applications. For instance, reliable location data of individuals or objects is essential for use cases such as traffic surveillance, search and rescue, relief efforts after natural disasters, or patrol and border control missions. Unmanned aerial vehicles (UAVs) provide great value in such situations but conventionally require at least one human operator whose insights and intuition are necessary for performing the task. With this contribution, we conceptualize a functional design that leverages performance models to track multiple targets and generate situational awareness autonomously. Further, we devise a testing harness for different scheduling schemes and provide some preliminary experimental data on basic scheduling policies found in literature.