Vijay Mishra

Complex and dynamic environments in many engineering applications require intelligent and autonomous agents that cognitively sense the environment, acquire the relevant information, and then use it to adapt in real-time for improved performance. In this context, inverse cognition --- wherein a 'defender' agent learns the information about itself sensed by a cognitive 'attacker' agent  --- has recently gathered significant research interest. The problem is motivated by the need to design counter-autonomous adversarial systems. A suitable example is a military surveillance application, where a target aircraft is tracked by a hostile but cognitive radar, which is equipped with a Bayesian tracker. It is then instructive for the target to become inversely cognitive and predict the actions of the radar and guard against them. This is precisely the objective of inverse Bayesian filtering, wherein given noisy observations, a posterior distribution of the underlying state is obtained. In particular, we consider this problem in a non-linear setting and develop a family of inverse stochastic filters to address inverse cognition. We begin with the inverse extended Kalman filter (I-EKF) and derive its theoretical stability guarantees using both bounded nonlinearity and unknown matrix approaches. We then generalize these formulations and results to the case of higher-order, Gaussian-sum, and dithered I-EKFs. We then obtain a more robust approach to nonlinearities in the form of an inverse unscented Kalman filter (I-UKF) and extend it to inverse cubature/quadrature Kalman filters (I-CKF/I-UKF). For both I-EKF and I-UKF, we also consider the scenario when the radar's filter is unknown to the target. This work has strong connections with general approximate Bayesian inference approaches in machine learning. The UKF, QKF, and CKF are a special case of assumed density filters (ADF) or online Bayesian learning, which sequentially approximates the posterior distribution of the underlying state. We close this talk by discussing the recent advances in meta-cognitive radar.

Biography:

Kumar Vijay Mishra (S’08-M’15-SM’18) obtained a Ph.D. in electrical engineering and M.S. in mathematics from The University of Iowa in 2015, and M.S. in electrical engineering from Colorado State University in 2012, while working on NASA’s Global Precipitation Mission Ground Validation (GPM-GV) weather radars. He received his B. Tech. summa cum laude (Gold Medal, Honors) in electronics and communication engineering from the National Institute of Technology, Hamirpur (NITH), India in 2003. He is currently Senior Fellow at the United States Army Research Laboratory (ARL), Adelphi; Technical Adviser to Singapore-based automotive radar start-up Hertzwell and Boston-based imaging radar startup Aura Intelligent Systems; and honorary Research Fellow at SnT - Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg. Previously, he had research appointments at Electronics and Radar Development Establishment (LRDE), Defence Research and Development Organisation (DRDO) Bengaluru; IIHR - Hydroscience & Engineering, Iowa City, IA; Mitsubishi Electric Research Labs, Cambridge, MA; Qualcomm, San Jose; and Technion - Israel Institute of Technology.

Dr. Mishra is the Distinguished Lecturer of the IEEE Communications Society (2023-2024), IEEE Aerospace and Electronic Systems Society (AESS) (2023-2024), and IEEE Future Networks Initiative (2022). He is the recipient of the IET Premium Best Paper Prize (2021), U. S. National Academies Harry Diamond Distinguished Fellowship (2018-2021), American Geophysical Union Editors' Citation for Excellence (2019), Royal Meteorological Society Quarterly Journal Editor's Prize (2017), Viterbi Postdoctoral Fellowship (2015, 2016), Lady Davis Postdoctoral Fellowship (2017), DRDO LRDE Scientist of the Year Award (2006), NITH Director’s Gold Medal (2003), and NITH Best Student Award (2003). He has received Best Paper Awards at IEEE MLSP 2019 and IEEE ACES Symposium 2019.

Dr. Mishra is Chair (2023-present) of the Synthetic Apertures Technical Working Group of the IEEE Signal Processing Society (SPS) and Vice-Chair (2021-present) of the IEEE Synthetic Aperture Standards Committee, which is the first SPS standards committee. He is the Vice Chair (2021-2023) and Chair-designate (2023-2026) of the International Union of Radio Science (URSI) Commission C. He has been an elected member of three technical committees of IEEE SPS: SPCOM, SAM, and ASPS, and IEEE AESS Radar Systems Panel. Since 2020, he has been Associate Editor of IEEE Transactions on Aerospace and Electronic Systems, where he was awarded Outstanding Editor recognition in 2021. He has been a lead/guest editor of several special issues in journals such as IEEE Signal Processing Magazine, IEEE Journal of Selected Topics in Signal Processing, and IEEE Journal on Selected Areas in Communications. He is the lead co-editor of three upcoming books on radar: Signal Processing for Joint Radar-Communications (Wiley-IEEE Press), Next-Generation Cognitive Radar Systems (IET Press Radar, Electromagnetics & Signal Processing Technologies Series), and Advances in Weather Radar Volumes 1, 2 & 3 (IET Press Radar, Electromagnetics & Signal Processing Technologies Series). His research interests include radar systems, signal processing, remote sensing, and electromagnetics.