Tyler A. Hobson, The University of Queensland, I. Vaughan L. Clarkson, The University of Queensland, Travis Bessell, Defence Science and Technology Group, Mark Rutten, Defence Science and Technology Group, Neil Gordon, Defence Science and Technology Group, Nicholas Moretti, Inovor Technologies, Brittany Morreale, United States Air Force
Keywords: Autonomous, SSA, telescope, search, track, JPDA, CAR
Abstract:
In order to safeguard the continued use of space-based technologies, effective monitoring and tracking of man-made resident space objects (RSOs) is paramount. The diverse characteristics, behaviours and trajectories of RSOs make space surveillance a challenging application of the discipline that is tracking and surveillance. When surveillance systems are faced with non-canonical scenarios, it is common for human operators to intervene while researchers adapt and extend traditional tracking techniques in search of a solution. A complementary strategy for improving the robustness of space surveillance systems is to place greater emphasis on the anticipation of uncertainty. Namely, give the system the intelligence necessary to autonomously react to unforeseen events and to intelligently and appropriately act on tenuous information rather than discard it. In this paper we build from our 2015 campaign and describe the progression of a low-cost intelligent space surveillance system capable of autonomously cataloguing and maintaining track of RSOs. It currently exploits robotic electro-optical sensors, high-fidelity state-estimation and propagation as well as constrained initial orbit determination (IOD) to intelligently and adaptively manage its sensors in order to maintain an accurate catalogue of RSOs. In a step towards fully autonomous cataloguing, the system has been tasked with maintaining surveillance of a portion of the geosynchronous (GEO) belt. Using a combination of survey and track-refinement modes, the system is capable of maintaining a track of known RSOs and initiating tracks on previously unknown objects. Uniquely, due to the use of high-fidelity representations of a target’s state uncertainty, as few as two images of previously unknown RSOs may be used to subsequently initiate autonomous search and reacquisition. To achieve this capability, particularly within the congested environment of the GEO-belt, we use a constrained admissible region (CAR) to generate a plausible estimate of the unknown RSO’s state probability density function and disambiguate measurements using a particle-based joint probability data association (JPDA) method. Additionally, the use of alternative CAR generation methods, incorporating catalogue-based priors, is explored and tested. We also present the findings of two field trials of an experimental system that incorporates these techniques. The results demonstrate that such a system is capable of autonomously searching for an RSO that was briefly observed days prior in a GEO-survey and discriminating it from the measurements of other previously catalogued RSOs.
Date of Conference: September 20-23, 2016
Track: Instrumentation & Optical Surveillance