  In this paper, we study a distributed parameter estimation problem with an
asynchronous communication protocol over multi-agent systems. Different from
traditional time-driven communication schemes, in this work, data can be
transmitted between agents intermittently rather than in a steady stream.
First, we propose a recursive distributed estimator based on an event-triggered
communication scheme, through which each agent can decide whether the current
estimate is sent out to its neighbors or not. With this scheme, considerable
communications between agents can be effectively reduced. Then, under mild
conditions including a collective observability, we provide a design principle
of triggering thresholds to guarantee the asymptotic unbiasedness and strong
consistency. Furthermore, under certain conditions, we prove that, with
probability one, for every agent the time interval between two successive
triggered instants goes to infinity as time goes to infinity. Finally, we
provide a numerical simulation to validate the theoretical results of this
paper.
