Question: Enhanced Orbit Determination of Resident Space Objects for Collision Avoidance Using Advanced Imaging Algorithms The increasing number of spacecraft and debris in low Earth orbit

Enhanced Orbit Determination of Resident Space Objects for Collision Avoidance Using Advanced Imaging Algorithms
The increasing number of spacecraft and debris in low Earth orbit (LEO) poses significant challenges for orbital mechanics and mission planning. The lack of precise orbital elements for these objects necessitates the development of advanced methods for orbit determination. Accurate knowledge of the state of resident space objects (RSOs) is crucial for autonomous collision avoidance and for the execution of rendezvous and docking maneuvers. The project plans to develop an algorithm using an Extended Kalman Filter (EKF) for the estimation of the orbital parameters of RSOs based on visual data collected through an advanced camera system. Simulating the dynamics of spacecraft in a two-body environment while considering real-world complexities such as non-linear motion, sensor noise, and measurement inaccuracies, will provide the necessary data for this project. Evaluating the performance of the EKF against traditional methods, such as a standard Kalman Filter, in terms of accuracy and robustness in orbit determination. Camera System Simulation: Utilize a simulated advanced camera algorithm capable of determining the range, angles, and orientation of RSOs. This will be modeled to reflect current commercially available technology. Dynamics Modeling: Implement Clohessy-Wiltshire equations to simulate the relative motion of two objects in near-circular orbits, addressing the challenges posed by non-linear spacecraft dynamics. Data Collection and Processing: Collect synthetic observational data reflecting realistic scenarios and noise levels. Use MATLAB to develop the simulation and implement the EKF for data processing. Performance Evaluation: Compare the performance of the EKF with a standard Kalman Filter under various conditions, analyzing metrics such as estimation accuracy, computational efficiency, and robustness against sensor errors. The development of a reliable algorithm for orbit determination can be implemented in future spacecraft systems. A comprehensive assessment of the efficacy of the EKF in real-world scenarios, will provide insights into the future of spacecraft operations. While including the recommendation for the integration of advanced imaging systems and filtering algorithms in spacecraft design to enhance collision avoidance capabilities.
I am coding on MATLAB, where do I start?

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