Orbit Logic’s Onboard Planning Software Enables Enhanced SSA Using Satellite Clusters

The effort is a research partnership with the University of Texas at Austin (UT), with whom we previously developed a ground-based version of Heimdall – a planning framework to optimize the use of ground- and space-based sensors to maximize resident space object situational awareness by using an information gain metric as a component of the tasking plan’s score.

Heimdall Onboard will enable of a team of satellites in a cooperating cluster to perform fully automated Resident Space Object (RSO) custody maintenance of an operator-specified set of high interest objects. The logic required to a) determine an agile schedule to acquire images using onboard sensors, b) detect objects in the images, c) determine orbits for those detections, d) associate the orbits with objects in the locally-maintained onboard catalog, and e) adapt the sensor tasking plans dynamically based on uncertainties, sensor capabilities, and the relative viewing perspectives of the cluster members over time – will all be performed on the flight computers of the cluster elements using decentralized approaches to collaborative autonomy and data fusion.

This effort will integrate UT’s mature processing and fusion algorithms with the mature, flight-qualified version of Orbit Logic’s Autonomous Planning System (APS) that was developed for AFRL’s SaFIRE program, enhancing its decentralized collection planning to ensure that the observations being made by each satellite most effectively contribute to building an SSA picture of all RSOs of interest.