individual
What campus are you from?
Daytona Beach
Authors' Class Standing
James Kirk, Senior
Lead Presenter's Name
James Kirk
Faculty Mentor Name
Cagri Kilic
Abstract
Satellite deployment has become increasingly dangerous with the rise of debris and uncatalogued objects in outer space. Since 2010, "known" satellite deployment has increased by approximately 1415%, significantly expanding the population in an already crowded region. Notably, high-profile events such as the 2009 collision of the Iridium and Cosmos satellites generated about 1800 pieces of trackable debris (larger than 10 cm), instantly escalating risks for surrounding satellites. These threats are set to intensify as more satellites are planned for Low Earth Orbits (LEO) to support exploration and experiments. Consequently, satellite safety must be optimized by cataloging uncontrolled fragments. Currently, the United States Space Surveillance Network (SSN) and other ground-based stations reliably track debris larger than 10 cm in LEO and 1 m in Geosynchronous Earth Orbits (GEO). However, the large distance between objects and ground stations limits tracking capabilities. In particular, studies have shown that debris in the 1–10 cm range pose the greatest risk to satellites and spacecraft due to their sheer number and high velocities. These gaps in tracking highlight the urgent need for effective solutions to monitor and catalog small resident space objects (RSOs), which have become crucial for the future of space operations. The primary challenge in detecting small debris is to identify debris that reflect faint light using modern technology. This effort is constrained by aperture size, focal length, and dynamic range. This comprehensive study addresses these challenges by modeling and simulating the probability of detection of small debris in Systems Tool Kit Electro-Optical and Infrared (STK EOIR) tool. First, STK EOIR is configured with proven star trackers and imagers. This setup evaluates sensors' performance under high-fidelity situations. Properties such as integration time and dynamic range are optimized to maximize detection probability. The ASTRO CL CAM f/8 configuration is used for preliminary testing. Parameters come from the vendor’s website (e.g., full well capacity, quantum efficiency, readout noise, etc.). To separate RSOs from stars, RSO and streak detection algorithms are applied to images generated in STK EOIR. Monte Carlo debris generation tools are also used. Tools include STK’s Gaussian breakup models and the NASA Standard Satellite Breakup Model (SSBM) for post-collision analysis, prediction, and assessment. Initially, the debris forms into a cloud and then disperses over time, creating a quasi-ring structure around the central body. The average orbital elements of the quasi-ring are calculated to determine the patrol orbit for a "probe." Lowering the semi-major axis (SMA) increases the probe’s velocity relative to the debris. This allows continuous scanning with cameras pointed along the zenith vector. For scanning, step and stare methods are used to maximize coverage. The probe collects a series of inertial stares while orbiting the central body. These image collections can be overlaid, creating a visible streak as the RSO moves between frames. Future work will aim to refine Monte Carlo simulations for the Gaussian and NASA Standard Breakup Models. Additional patrol orbit optimization will also take place with the additional sensor design for improved coverage reliability. Ultimately, the methods that will be utilized will aim to provide the groundwork for small debris cataloging within close-proximity operations.
Did this research project receive funding support from the Office of Undergraduate Research.
No
Eliminating Range Constraints for Optical Tracking of Sub-10 cm Orbital Debris
Satellite deployment has become increasingly dangerous with the rise of debris and uncatalogued objects in outer space. Since 2010, "known" satellite deployment has increased by approximately 1415%, significantly expanding the population in an already crowded region. Notably, high-profile events such as the 2009 collision of the Iridium and Cosmos satellites generated about 1800 pieces of trackable debris (larger than 10 cm), instantly escalating risks for surrounding satellites. These threats are set to intensify as more satellites are planned for Low Earth Orbits (LEO) to support exploration and experiments. Consequently, satellite safety must be optimized by cataloging uncontrolled fragments. Currently, the United States Space Surveillance Network (SSN) and other ground-based stations reliably track debris larger than 10 cm in LEO and 1 m in Geosynchronous Earth Orbits (GEO). However, the large distance between objects and ground stations limits tracking capabilities. In particular, studies have shown that debris in the 1–10 cm range pose the greatest risk to satellites and spacecraft due to their sheer number and high velocities. These gaps in tracking highlight the urgent need for effective solutions to monitor and catalog small resident space objects (RSOs), which have become crucial for the future of space operations. The primary challenge in detecting small debris is to identify debris that reflect faint light using modern technology. This effort is constrained by aperture size, focal length, and dynamic range. This comprehensive study addresses these challenges by modeling and simulating the probability of detection of small debris in Systems Tool Kit Electro-Optical and Infrared (STK EOIR) tool. First, STK EOIR is configured with proven star trackers and imagers. This setup evaluates sensors' performance under high-fidelity situations. Properties such as integration time and dynamic range are optimized to maximize detection probability. The ASTRO CL CAM f/8 configuration is used for preliminary testing. Parameters come from the vendor’s website (e.g., full well capacity, quantum efficiency, readout noise, etc.). To separate RSOs from stars, RSO and streak detection algorithms are applied to images generated in STK EOIR. Monte Carlo debris generation tools are also used. Tools include STK’s Gaussian breakup models and the NASA Standard Satellite Breakup Model (SSBM) for post-collision analysis, prediction, and assessment. Initially, the debris forms into a cloud and then disperses over time, creating a quasi-ring structure around the central body. The average orbital elements of the quasi-ring are calculated to determine the patrol orbit for a "probe." Lowering the semi-major axis (SMA) increases the probe’s velocity relative to the debris. This allows continuous scanning with cameras pointed along the zenith vector. For scanning, step and stare methods are used to maximize coverage. The probe collects a series of inertial stares while orbiting the central body. These image collections can be overlaid, creating a visible streak as the RSO moves between frames. Future work will aim to refine Monte Carlo simulations for the Gaussian and NASA Standard Breakup Models. Additional patrol orbit optimization will also take place with the additional sensor design for improved coverage reliability. Ultimately, the methods that will be utilized will aim to provide the groundwork for small debris cataloging within close-proximity operations.