Lt. Col. Jeremy Raley, Defense Advanced Research Projects Agency (DARPA), Ryan M. Weisman, Air Force Research Laboratory, C. Channing Chow II, Integrity Applications Incorporated – Pacific Defense Solutions, Michael Czajkowski, Lockheed Marticn, Kristin Sotzen, Johns Hopkins Univeristy, Applied Physics Laboratory
Keywords: Autonomous, Algorithms, data quality,
Abstract:
As the space object population has rapidly grown, the data volume required to produce reliable orbital estimates has far surpassed the pace of the traditional government sensor acquisition process. Fortunately, over the last few years, the commercial, academic, and amateur communities have stepped up to build cost-effective sensor networks leveraging commercial off-the-shelf (COTS) and existing hardware. Certifying and calibrating this multitude of diverse sensors using the traditional manual process is not feasible. Over the last three years, the Defense Advanced Research Projects Agency (DARPA) has been investing in concepts to develop a highly autonomous process to parametrically assess the quality of data originating from non-traditional sensors and to fuse this information with that obtained from certified sensors. Successful simulations and the development of automatic calibration algorithms have set the stage for an active demonstration effort using a global network of sensors including commercial, academic, amateur, and government sources. This paper will discuss progress to date and demonstrations scheduled for completion through spring 2017.
Date of Conference: September 20-23, 2016
Track: SSA Algorithms