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

TL;DR

This paper develops a neural network-based approach to predict optimal trajectories for the Apophis asteroid flyby and to fuse data for mission launch window planning, enhancing asteroid monitoring and planetary defense strategies.

Contribution

It introduces a novel deep neural network model for orbit prediction and launch window data fusion specific to the Earth-Apophis mission, improving accuracy and planning efficiency.

Findings

Neural network model accurately predicts asteroid orbits.

Data fusion method optimizes launch window selection.

Enhanced trajectory prediction reduces mission risk.

Abstract

In recent years, understanding asteroids has shifted from light worlds to geological worlds by exploring modern spacecraft and advanced radar and telescopic surveys. 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. 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 error