Prediction of Apophis Asteroid Flyby Optimal Trajectories and Data Fusion of Earth-Apophis Mission Launch Windows using Deep Neural Networks

• URL: http://arxiv.org/abs/2104.06249v1
• Date: Sun, 11 Apr 2021 21:42:53 GMT
• Title: Prediction of Apophis Asteroid Flyby Optimal Trajectories and Data Fusion of Earth-Apophis Mission Launch Windows using Deep Neural Networks
• Authors: Manuel Ntumba, Saurabh Gore, Jean-Baptiste Awanyo
• Abstract summary: The Earth-Apophis mission is driven by additional factors and scientific goals beyond the unique opportunity for natural experimentation. understanding the strength and internal integrity of asteroids is not just a matter of scientific curiosity. This paper presents a conceptual robotics system required for efficiency at every stage from entry to post-landing.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In recent years, understanding asteroids has shifted from light worlds to geological worlds by exploring modern spacecraft and advanced radar and telescopic surveys. Apophis' near-Earth. However, flyby in 2029 will be an opportunity to conduct an internal geophysical study and test the current hypothesis on the effects of tidal forces on asteroids. The Earth-Apophis mission is driven by additional factors and scientific goals beyond the unique opportunity for natural experimentation. However, the internal geophysical structures remain largely unknown. Understanding the strength and internal integrity of asteroids is not just a matter of scientific curiosity. It is a practical imperative to advance knowledge for planetary defense against the possibility of an asteroid impact. The mounting of theoretical studies and physical evidence of tidal forces altering the shapes, spins, and surfaces of near-Earth asteroids indicates that these Earth-Apophis interactions are fundamental to the problem of asteroid risk as impact studies themselves. This paper presents a conceptual robotics system required for efficiency at every stage from entry to post-landing and for asteroid monitoring. In short, asteroid surveillance missions are futuristic frontiers, with the potential for technological growth that could revolutionize space exploration. Advanced space technologies and robotic systems are needed to minimize risk and prepare these technologies for future missions. A neural network model is implemented to track and predict asteroids' orbits. Advanced algorithms are also needed to numerically predict orbital events to minimize errors.

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