Collaborative and Opportunistic Navigation
Future autonomous systems will demand full situational awareness and reliable, consistent, tamper-proof, and highly accurate navigation systems. Global navigation satellite system (GNSS) is at the heart of virtually all current navigation systems. However, GNSS will not meet the demands of future autonomous systems. First, GNSS signals are extremely weak and unusable indoors and in deep urban canyons. Second, GNSS signals are susceptible to intentional and unintentional jamming and interference. Third, civilian GNSS signals are unencrypted, unauthenticated, and specified in publicly-available documents, making them spoofable.
Our research in this thrust asks: what information is already available in the surrounding environment, and how can it be exploited for positioning, navigation, and timing? The information extracted from the environment is fused with on-board sensors to build a spatio-temporal map of the environment within which the autonomous system localizes itself in space and time. Information is also shared among multiple systems to achieve global situational awareness within the environment.
Signals of Opportunity Aided Inertial Navigation
Modeling and Analysis of Sector Clock Bias Mismatch in Cellular Systems
Vertical Dilution of Precision Reduction
Adaptive Estimation of Signals of Opportunity
Observability & Estmability Analyses of Collaborative Opportunistic Environments