The Daniel Guggenheim School of Aerospace Engineering

invites you to hear

"Space Situational Awareness: 
New Challenges & Advances in Estimation, Data Sharing, and Privacy"

by

 Prof. Raktim Bhattacharya

Assistant Professor
Texas A&M University
 

Thursday, September 26
3 - 4 p.m.
Guggenheim 442

About the Talk: 
Currently there are about 500K space objects of which only 30K are actively tracked. These include operational satellites and space debris. As the space is getting crowded with new launches, keeping track of all these space objects is becoming critical to prevent possible collisions. In this effort, there are initiatives to share data, which promise to improve our knowledge of the near-space environment, also known as space-situational awareness. While there are benefits to sharing data from a situational awareness perspective, there are critical privacy and national security issues associated with it. This requires understanding of the privacy-utility tradeoff to develop appropriate data-sharing policy. Thus, there are challenges in estimating states with acceptable accuracy for utility, but not too accurately to preserve privacy. In this talk, these challenges will be discussed in a nonlinear filtering framework, including uncertainty propagation in nonlinear manifolds, sensing with non-Gaussian uncertainty, new sampling algorithms in these manifolds, optimal sensing precision, and privacy aware filtering.

About the Speaker: 
Dr. Raktim Bhattacharya received his M.S. and Ph.D. degrees in aerospace engineering from the University of Minnesota in 2000 and 2003, respectively. He was a post-doctoral scholar at Caltech from 2003-2004 in the department of Control and Dynamical Systems. After that he was employed by United Technologies Research Center as a research scientist from 2004-2005. He joined the aerospace engineering department of Texas A&M University in 2005 and currently is an associate professor. His research interests include robust control and estimation, nonlinear dynamics, uncertainty quantification and convex optimization. His research is supported by NSF, AFOSR and NASA.