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Full-Text Articles in Astrodynamics
Satellite Conjunction Assessment Risk Analysis For “Dilution Region” Events: Issues And Operational Approaches, Matthew D. Hejduk
Satellite Conjunction Assessment Risk Analysis For “Dilution Region” Events: Issues And Operational Approaches, Matthew D. Hejduk
Space Traffic Management Conference
An important activity within Space Traffic Management is the detection and prevention of possible on-orbit collisions between space objects. The principal parameter for assessing collision likelihood is the probability of collision, which is widely accepted among conjunction assessment practitioners; but it possesses a known deficiency in that it can produce a false sense of safety when the orbital position uncertainties for the conjuncting objects are high. The probability of collision is said to be “diluted” in such a situation and to understate the possible risk; certain approaches have been recommended by researchers to provide (largely conservative) risk estimates and remediation …
Space Objects Classification And Characterization Via Deep Learning And Light Curves: Applications To Space Traffic Management, Roberto Furfaro, Richard Linares, Vishnu Reddy
Space Objects Classification And Characterization Via Deep Learning And Light Curves: Applications To Space Traffic Management, Roberto Furfaro, Richard Linares, Vishnu Reddy
Space Traffic Management Conference
Recent advancements in deep learning (e.g. Convolutional Neural Networks (CNN), Recurrent Neural networks (RNN)) have demonstrated impressive results in many practical and theoretical fields (e.g. speech recognition, computer vision, robotics). Whereas deep learning methods are becoming ubiquitous, they have been barely explored in SSA applications, in particular with regard to object characterization for Space Traffic Management (STM).
In this paper, we report the results obtained in designing and training a set of CNNs and RNNs for Space Object (SO) classification and characterization using light-curve measurements. More specifically, we provide a comparison between deep networks trained on both physically-based models (i.e. …
Near Real Time Satellite Event Detection And Characterization With Remote Photoacoustic Signatures, Justin Spurbeck, Moriba K. Jah
Near Real Time Satellite Event Detection And Characterization With Remote Photoacoustic Signatures, Justin Spurbeck, Moriba K. Jah
Space Traffic Management Conference
Active satellites frequently maneuver to mitigate conjunctions and maintain nominal mission orbits. With an ever-growing Resident Space Object (RSO) population, the need to detect and predict any changes in active RSO trajectories has become increasingly important. There is typically a lag on the order of hours to days from time of maneuver to unmodeled dynamic event detection depending on the magnitude of the delta-v. For uncooperative objects, this detection lag poses a threat to other satellites. Implementing an active photoacoustic signature change detection methodology to detect and predict unmodeled dynamic events would reduce the overall conjunction risk and provide a …