Consensus-based Distributed Algorithm for Multisensor-Multitarget Tracking under Unknown-but-Bounded Disturbances
Peer reviewed, Journal article
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Original versionIFAC-PapersOnLine. 2020, . http://dx.doi.org/10.1016/j.ifacol.2020.12.1756
We consider a dynamic network of sensors that cooperate to estimate parameters of multiple targets. Each sensor can observe parameters of a few targets, reconstructing the trajectories of the remaining targets via interactions with “neighbouring” sensors. The multi-target tracking has to be provided in the face of uncertainties, which include unknown-but-bounded drift of parameters, noise in observations and distortions introduced by communication channels. To provide tracking in presence of these uncertainties, we employ a distributed algorithm, being an “offspring” of a consensus protocol and the stochastic gradient descent. The mathematical results on the algorithm’s convergence are illustrated by numerical simulations.