Fall 2022 Colloquium - Raktim Bhattacharya

College of Engineering, Texas A&M University

Tile: The Sunset of Smallsats and the Dawn of Big Space

Abstract: The need for enhanced RSO (resident space object) tracking technologies is growing as the cislunar space emerges as a new frontier. The Artemis program's lunar gateway and exploration ambitions have piqued interest in stable Lagrange point orbits, which can enable sophisticated mission structures. Several governments want to keep their presence in cislunar space. The cislunar space has no inherent military value, but it does give adversaries new opportunities to "hide in space".

With existing capabilities, tracking objects in cislunar space is highly challenging due to poor sensing over large distances and lunar exclusion zones. Consequently, conventional space tracking systems cannot track cislunar objects satisfactorily and may lose it due to an evasive maneuver. This limitation enables hostile RSOs to perform undetected evasive maneuvers and find new ways to be in the blind spot of the tracking system, resulting in possible near-Earth military advantage. For example, orbits like the free return paths, designed for the US Apollo missions, can be easily modified to hide a spacecraft's origin and potentially re-enter the Earth-orbiting domain without sufficient early identification.

This presentation will describe some of the key challenges in tracking cislunar RSOs and present some new approaches to address them.

Bio: Raktim Bhattacharya received his B.Tech degree from the Indian Institute of Technology in Aerospace Engineering, followed by an M.S. and Ph.D. degree in aerospace engineering from the University of Minnesota. After that, he was a post-doctoral scholar at Caltech in the Department of Control and Dynamical Systems. After Caltech, he joined United Technologies Research Center as a research scientist. Following that, he joined the Aerospace Engineering department of Texas A&M University in 2005 and is currently a full professor. His research interests include robust control and estimation, nonlinear dynamics, robust control, uncertainty quantification, and convex optimization.