Session
Weekend Poster Session 1
Location
Utah State University, Logan, UT
Abstract
With large constellations of satellites, it can be difficult to determine coverage capabilities as well as determine the best-suited satellites for fulfilling requests for information as quickly as possible. When expanding constellation coverage by increasing the number of sensors, incomplete awareness of current coverage may lead to money and time being spent acquiring assets providing additional coverage in areas with already sufficient coverage rather than filling in gaps. Even in areas with sufficient coverage, receiving imagery before it becomes obsolete relies on tasking the most optimal sensor for quick data turnaround. With sensors potentially having differing tasking lead times, latencies, and imagery conditions - as in the case of electro optical sensors needing sunlight and minimal cloud cover - manually determining which sensor to task is an arduous task. This project uses Systems Tool Kit to automate generation of heat maps of constellation coverage within user-defined parameters and to develop a Python program to determine the sensors within a constellation that can provide viable imagery the fastest.
Visualization of Sensor Coverage and Optimization of Sensor Tasking for Satellite Constellations
Utah State University, Logan, UT
With large constellations of satellites, it can be difficult to determine coverage capabilities as well as determine the best-suited satellites for fulfilling requests for information as quickly as possible. When expanding constellation coverage by increasing the number of sensors, incomplete awareness of current coverage may lead to money and time being spent acquiring assets providing additional coverage in areas with already sufficient coverage rather than filling in gaps. Even in areas with sufficient coverage, receiving imagery before it becomes obsolete relies on tasking the most optimal sensor for quick data turnaround. With sensors potentially having differing tasking lead times, latencies, and imagery conditions - as in the case of electro optical sensors needing sunlight and minimal cloud cover - manually determining which sensor to task is an arduous task. This project uses Systems Tool Kit to automate generation of heat maps of constellation coverage within user-defined parameters and to develop a Python program to determine the sensors within a constellation that can provide viable imagery the fastest.
