On-Orbit smart camera system to observe illuminated and unilluminated space objects

Steven Morad, Ravi Teja Nallapu, Himangshu Kalita, Byong Kwon, Vishnu Reddy, Roberto Furfaro, Erik Asphaug, Jekan Thangavelautham

Research output: Contribution to journalArticlepeer-review


The wide availability of Commercial Off-The-Shelf (COTS) electronics that can withstand Low Earth Orbit conditions has opened avenue for wide deployment of CubeSats and small-satellites. CubeSats thanks to their low developmental and launch costs offer new opportunities for rapidly demonstrating on-orbit surveillance capabilities. In our earlier work, we proposed development of SWIMSat (Space based Wide-angle Imaging of Meteors) a 3U CubeSat demonstrator that is designed to observe illuminated objects entering the Earth's atmosphere. The spacecraft would operate autonomously using a smart camera with vision algorithms to detect, track and report of objects. Several CubeSats can track an object in a coordinated fashion to pinpoint an object's trajectory. An extension of this smart camera capability is to track unilluminated objects utilizing capabilities we have been developing to track and navigate to Near Earth Objects (NEOs). This extension enables detecting and tracking objects that can't readily be detected by humans. The system maintains a dense star map of the night sky and performs round the clock observations. Standard optical flow algorithms are used to obtain trajectories of all moving objects in the camera field of view. Through a process of elimination, certain stars maybe occluded by a transiting unilluminated object which is then used to first detect and obtain a trajectory of the object. Using multiple cameras observing the event from different points of view, it may be possible then to triangulate the position of the object in space and obtain its orbital trajectory. In this work, the performance of our space object detection algorithm coupled with a spacecraft guidance, navigation, and control system is demonstrated. In our tests, we were able to successfully detect a transit 88% of the time with σ= 0.5 DN sensor readout noise. Our method scales linearly in time and with the number of pixels, with the most computationally intensive phases being parallelizable and simple enough to be offloaded to SWIMSat's onboard FPGA. A thorough description of the detection algorithm, along with the tracking controller is presented in this work. Our work suggests both a critical need and the promise of such a tracking algorithm for implementation of an autonomous, low-cost constellation for performing Space Situational Awareness (SSA).

Original languageEnglish (US)
JournalUnknown Journal
StatePublished - Sep 6 2018

ASJC Scopus subject areas

  • General

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