S-SLATS: Scalable Simultaneous Localization and Time Synchronization

Description: As the density of wireless, resource-constrained sensors grows, so does the need to choreograph their actions across both time and space. We aim to develop a novel approach to simultaneously localizing and time synchronizing networked mobile devices. We would like to extend the size of a network of test beds by duplicating an available PCB design to show the scalability factor. Then use scalable distributed kalman filter to simultaneously localize and time synchronize a network of testbeds.

The Networked and Embedded Systems Lab (NESL) currently has a setup with several monitors placed around the room, tracking a series of stationary nodes using UWB. Existing programs allow us to estimate their positions and clock skew by utilizing a distributed Kalman filter at each node. The problem is that each node currently works with state vectors containing information about all nodes; as the number of nodes increases, such computation will quickly grow to become unscalable.

Our goal is to implement a distributed Kalman filtering scheme at each node that allows each node to estimate its own state and that of its neighbors, without requiring data or estimation about other nodes in the network. Much of our research has been focused on the paper "Distributing the Kalman Filter for Large-Scale Systems", by Usman A. Khan and José M.F. Moura.