Closely spaced object detection utilizing spatial information in spectroastrometric observations

J. Zachary Gazak; Ryan Swindle; Zachary Funke; Matthew Phelps; Justin Fletcher

doi:10.1117/12.2625366

3 June 2022 Closely spaced object detection utilizing spatial information in spectroastrometric observations

J. Zachary Gazak, Ryan Swindle, Zachary Funke, Matthew Phelps, Justin Fletcher

Proceedings Volume 12121, Sensors and Systems for Space Applications XV; 121210K (2022) https://doi.org/10.1117/12.2625366
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

The detection of closely spaced artificial satellites informs tactical decision making in a high risk scenario in the space domain. In regimes where spatial information is lost (ground observations of small or distant satellites), spectroastrometry simulations have demonstrated the potential to detect the presence of multiple objects down to 0′′.05–ten meters at geostationary orbit–using a medium resolution optical spectrograph on a large aperture telescope.¹ This technique falls into the growing field of learned space domain awareness: leveraging convolutional neural networks to rapidly infer tactical information from complex, non-intuitive data. In this work we present a field rotation nodding technique that removes the need for a priori knowledge of the closely spaced object on sky orientation. We discuss modifications to an optical spectrograph necessary to perform this technique. We present simulated bounds on the effectiveness of spectroastrometry for the detection of closely spaced objects.

Conference Presentation

Citation Download Citation

J. Zachary Gazak, Ryan Swindle, Zachary Funke, Matthew Phelps, and Justin Fletcher "Closely spaced object detection utilizing spatial information in spectroastrometric observations", Proc. SPIE 12121, Sensors and Systems for Space Applications XV, 121210K (3 June 2022); https://doi.org/10.1117/12.2625366

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available