Time-Difference-of-Arrival (TDOA)-Based Distributed Target Localization by A Robotic Network

Localization and tracking of a moving target arises in many different contexts and is of particular interest in the field of robotic networks. One important class of localization schemes exploits the time-difference-of-arrival (TDOA) of a signal emitted by the target and detected by multiple sensors. In this article, we propose a fully distributed approach to TDOA-based localization and tracking of a moving target in 3-D space by a group of mobile robots. We utilize a networked extended Kalman filter to estimate the target's location in a distributed manner, and guarantee successful localization under fixed and time-varying undirected communication topologies if every agent is part of a network with a minimum of four connected, noncoplanar agents. Since localization performance under TDOA-based schemes degrades as the target moves away from the convex hull formed by the agents, it is important for the network to track the target as it moves in space. We thus further propose a movement control strategy based on the norm of the estimation covariance matrices, with a tuning parameter to balance the tradeoff between estimation performance and the total distance traveled by the robots. A numerical example involving robots with simplified 3-D dynamics is provided to illustrate the performance of the proposed approach.