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Optimization and Enhancement of Space Object Identification Algorithms and Implementation Using Deep Learning Network

Satellites are continuously launched by various countries for some expeditions. Satellites, after completing their work become nonfunctional and disintegrate in space, as debris continues to revolve in the space orbit. Now, these may collide with each other or with the fully functional satellite. This causes the formation of more debris. Hence, there is a huge possibility that these debris may harm the satellite. This may cost billions and the failure of new projects. The proposed work uses CNN model of the deep learning algorithm and its various applications to classify space objects as debris using light curves. This current work studies the different deep learning approaches and compares the result of their accuracies to suggest the best approach.