Session
Swifty Session 2
Location
Utah State University, Logan, UT
Abstract
We conducted a campaign to demonstrate rapid responsiveness by tasking a nanosatellite with in-transit plane and ship image captures. By utilizing open-source information, approximate routes can be generated using ANSYS's Systems Tool Kit (STK) Software for these vehicles1.
GEOStare SV2 was leveraged for this effort by utilizing a new imaging mode for tracking and sweeping between coordinate locations ("nodes"). GEOStare SV2 is a 6U CubeSat in a mid-latitude LEO orbit with a dual camera remote sensing payload. The satellite is operated by Terran Orbital, with the payload designed by Lawrence Livermore National Laboratories (LLNL). Since launching in May 2021, it has taken over 100,000 images of ground and space-based targets, including landmarks, environmental disasters, war zones, satellites, and asteroids at an average cadence of several thousand images per month. The capabilities of GEOStare SV2's attitude determination and control system (ADCS) enable unique imaging modes such as mosaics that can quickly and easily be leveraged by ground operators. For this campaign, mosaics was used to attempt to track and image the position of vehicles of interest. Mosaics is designed to sweep between several nodes at specified timestamps to command the line-of-sight of the camera such that it coincides with a location of interest at a given point in time. This imaging mode allows the spacecraft to capture more information within a given image session by ensuring a moving object remains in frame or by capturing larger portions of the terrain.
A ground scheduling system was used to build command parameters and send them to the spacecraft without an operator in the loop. Ground tools include filters based on the team's experimental findings for improving image integrity, such as weather and exposure times. The images can be downlinked and moved to a desired location without operator intervention. Upon receiving the images, the team is immediately able to view and determine the quality and contents of an image, then schedule new images or deliver them to customers.
Demonstrating Rapid Response for Remote Sensing Applications Using Automation and Intelligent Software on GEOStare SV2
Utah State University, Logan, UT
We conducted a campaign to demonstrate rapid responsiveness by tasking a nanosatellite with in-transit plane and ship image captures. By utilizing open-source information, approximate routes can be generated using ANSYS's Systems Tool Kit (STK) Software for these vehicles1.
GEOStare SV2 was leveraged for this effort by utilizing a new imaging mode for tracking and sweeping between coordinate locations ("nodes"). GEOStare SV2 is a 6U CubeSat in a mid-latitude LEO orbit with a dual camera remote sensing payload. The satellite is operated by Terran Orbital, with the payload designed by Lawrence Livermore National Laboratories (LLNL). Since launching in May 2021, it has taken over 100,000 images of ground and space-based targets, including landmarks, environmental disasters, war zones, satellites, and asteroids at an average cadence of several thousand images per month. The capabilities of GEOStare SV2's attitude determination and control system (ADCS) enable unique imaging modes such as mosaics that can quickly and easily be leveraged by ground operators. For this campaign, mosaics was used to attempt to track and image the position of vehicles of interest. Mosaics is designed to sweep between several nodes at specified timestamps to command the line-of-sight of the camera such that it coincides with a location of interest at a given point in time. This imaging mode allows the spacecraft to capture more information within a given image session by ensuring a moving object remains in frame or by capturing larger portions of the terrain.
A ground scheduling system was used to build command parameters and send them to the spacecraft without an operator in the loop. Ground tools include filters based on the team's experimental findings for improving image integrity, such as weather and exposure times. The images can be downlinked and moved to a desired location without operator intervention. Upon receiving the images, the team is immediately able to view and determine the quality and contents of an image, then schedule new images or deliver them to customers.
