The Catalina Sky Survey (CSS) software suite is designed to detect and track Near-Earth Objects (NEOs), such as asteroids, that may pose a collision risk with Earth. By coordinating observations and data processing through multiple subsystems, the suite enables accurate tracking of these objects. The software manages telescope operations, image acquisition, and data analysis, culminating in the calculation of asteroid orbits and sizes. This information is shared with the Minor Planet Center (MPC) to facilitate global research and collaboration. A key component of CSS is its “Control” program, which orchestrates the suite's operations, ensuring the smooth execution of tasks and allowing observers to monitor and manage data efficiently. Control gathers user input for the evening’s operations, executes most of the individual programs that make up the system in the proper order with consistent parameters, and reports back on their status. Control provides a graphical user interface that makes it possible for observers to detect and fix problems quickly, process data easily, and efficiently report results to the MPC. With this system, the CSS contributes to planetary defense by identifying potential threats from space, supporting NASA's Open-Source Data Management Plan, and making their findings accessible to the broader scientific community. Background: Near-Earth Objects, such as asteroids, are ones which could potentially collide with Earth, posing a significant threat to our planet. Current solutions for NEO detection involve various global surveys and space agencies using telescopes and software to detect asteroids, but these systems often face challenges such as limited field coverage, slower processing of observations, and difficulties in distinguishing between asteroids and other celestial objects. The risk of missing or inaccurately tracking NEOs due to these limitations leaves gaps in planetary defense efforts. The Catalina Sky Survey’s specialized software suite stands out by offering a more streamlined and efficient approach to NEO detection and tracking, ensuring faster identification and more accurate tracking of objects. Applications:
Advantages: