Ms. Anissa Zacharias Profile

Anissa Zacharias

at Georgia Tech Research Institute

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Proceedings Article | 27 April 2020 Paper

Estimation of thruster plumes for resident space object optical observation

Keith Prussing, Anissa Zacharias, John Corker

Proceedings Volume 11422, 114220B (2020) https://doi.org/10.1117/12.2552075

KEYWORDS: Solar cells, Satellites, Mathematical modeling, Analytical research, Visualization, Telescopes, Reflection, Mirrors, Prisms

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With the ever-growing number of resident space objects (RSOs) surrounding the Earth, it is imperative that we develop techniques for determining their current and future state by leveraging a collection of radio frequency and optical observations to maintain space domain awareness (SDA). The state of an RSO at a future time is determined by its current state and the forces acting upon it. In theory, this prediction is trivial; however, knowing all of the forces is not practical. When a space object undergoes a maneuver, this simple extrapolation fails, and more measurements are required before an updated state estimate would be available causing tracking methods to fail. One means by which an RSO undergoes a maneuver, is by firing its thruster which provides a transient component to its signature. For example, many small satellites use Hall effect thrusters to perform station keeping. The emission from these thrusters can be up to three times greater than the rest of the satellite. This change in the signature provides information about the aspect of the RSO and the amount of energy expended by the engine to produce a thrust on the object. This information can be passed back to the state estimators to reduce the time necessary to update the RSO’s state. In this paper, we present a model for estimating the upper bound of the signature change of an RSO due to thruster engagement. We then present our initial results of a rendered model both with and without a plume present.

Proceedings Article | 14 May 2019 Presentation + Paper

Stellar background rendering for space situational awareness algorithm development

Keith Prussing, Christopher Valenta, Christopher Cordell, Anissa Zacharias, Layne Churchill

Proceedings Volume 10986, 109860Z (2019) https://doi.org/10.1117/12.2519009

KEYWORDS: Stars, Algorithm development, Satellites, Situational awareness sensors, Detection and tracking algorithms, Systems modeling, Sensors, Computer simulations, Optical tracking, Telescopes

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A key component of a night scene background on a clear moonless night is the stellar background. Celestial objects affected by atmospheric distortions and optical system noise become the primary contribution of clutter for detection and tracking algorithms while at the same time providing a solid geolocation or time reference due to their highly predictable motion. Any detection algorithm that needs to operate on a clear night must take into account the stellar background and remove it via background subtraction methods. As with any scenario, the ability to develop detection algorithms depends on the availability of representative data to evaluate the difficulty of the task. Further, the acquisition of measured field data under arbitrary atmospheric conditions is difficult if not impossible. For this reason, a radiometrically accurate simulation of the stellar background is a boon to algorithm developers. To aid in simulating the night sky, we have incorporated a star-field rendering model into the Georgia Tech Simulations Integrated Modeling System (GTSIMS). Rendering a radiometrically accurate star-field requires three major components: positioning the stars as a function of time and observer location, determining the in-band radiance of each star, and simulating the apparent size of each star. We present the models we have incorporated into GTSIMS and provide a representative sample of the images generated with the new model. We then demonstrate how the clutter in the neighborhood of a pixels change by including a radiometrically accurate rendering of a star-field.

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