S
Sriramya Bhamidipati
Researcher at University of Illinois at Urbana–Champaign
Publications - 34
Citations - 210
Sriramya Bhamidipati is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Global Positioning System & Spoofing attack. The author has an hindex of 7, co-authored 23 publications receiving 120 citations. Previous affiliations of Sriramya Bhamidipati include Indian Institute of Technology Bombay & Mitsubishi Electric Research Laboratories.
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Proceedings ArticleDOI
GPS Spoofing Detection and Mitigation in PMUs using Distributed Multiple Directional Antennas
TL;DR: A Belief-Propagation (BP)-based Extended Kalman Filter (EKF) algorithm is developed to estimate the timing errors caused by spoofing, which successfully detects meaconing and accurate estimation of GPS timing that complies with the IEEE-C37.118 standards is validated.
Journal ArticleDOI
GPS Multireceiver Joint Direct Time Estimation and Spoofer Localization
TL;DR: A novel algorithm for the joint estimation of spoofer location (LS) and GPS time using multireceiver direct time estimation (MRDTE) and the theoretical Cramér Rao lower bound for estimating the localization accuracy of the spoofer is formulated.
Proceedings ArticleDOI
GPS time authentication against spoofing via a network of receivers for power systems
TL;DR: This work proposes their GPS time authentication algorithm using a network of widely dispersed static receivers and their known positions, and demonstrates that the networked approach successfully detects these spoofing events with high probability.
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Locating Multiple GPS Jammers Using Networked UAVs
TL;DR: This work proposes a simultaneous localization of multiple jammers and receivers (SLMR) algorithm by analyzing the variation in the front-end signal power recorded by the GPS receivers on-board a network of UAVs, and designs a Gaussian mixture probability hypothesis density filter over a graph framework.
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Artificial-Intelligence-Based Distributed Belief Propagation and Recurrent Neural Network Algorithm for Wide-Area Monitoring Systems
TL;DR: A new wide-area monitoring algorithm, which comprises distributed belief propagation and a bidirectional recurrent neural network (RNN), is developed under the framework of artificial intelligence (AI), which authenticates each power substation by evaluating the estimated GPS timing error by its distributed processing capability.