Presentation Type
Paper (supporting PowerPoints may be added as Additional Files)
Location
Bass Auditorium
Start Date
26-2-2019 2:00 PM
Abstract
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 means for a near real time pulse of satellite events [1]. If photometric data is collected at a sufficient rate, any changes in outgoing photon flux due to satellite body vibrations caused by on-board events can be detected. The analysis of high-rate light curve data in the photometric, frequency, and photoacoustic domains can thus help characterize the event and provide mission specific intelligence. This research also investigates the use of signal processing methods, primarily cross-correlation, to improve the satellite body minimum displacement detection threshold in the presence of noise induced by the chaotic atmosphere.
[1] Spurbeck, J., Jah, M., Kucharski, D., Bennet, J., Webb, J. “Satellite Characterization, Classification, and Operational Assessment Via the Exploitation of Remote Photoacoustic Signatures.” Advanced Maui Optical and Space Surveillance Technologies Conference, Maui, Hawaii, 2018.
Area of Interest
Space Situational Awareness
Included in
Near Real Time Satellite Event Detection and Characterization with Remote Photoacoustic Signatures
Bass Auditorium
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 means for a near real time pulse of satellite events [1]. If photometric data is collected at a sufficient rate, any changes in outgoing photon flux due to satellite body vibrations caused by on-board events can be detected. The analysis of high-rate light curve data in the photometric, frequency, and photoacoustic domains can thus help characterize the event and provide mission specific intelligence. This research also investigates the use of signal processing methods, primarily cross-correlation, to improve the satellite body minimum displacement detection threshold in the presence of noise induced by the chaotic atmosphere.
[1] Spurbeck, J., Jah, M., Kucharski, D., Bennet, J., Webb, J. “Satellite Characterization, Classification, and Operational Assessment Via the Exploitation of Remote Photoacoustic Signatures.” Advanced Maui Optical and Space Surveillance Technologies Conference, Maui, Hawaii, 2018.
Comments
Visit the panel session Orbital Coordination: Part 1