Distributed multi-target tracking with low information updates via an integral-type event-based approach.

The existing event-triggered (ET) strategies for distributed multi-target filter commonly employ triggering conditions focusing on the instantaneous information discrepancy. Although this approach can save communication resource, it suffers from its sensitivity to instantaneous disturbance and outliers that results in unnecessary communications. In this correspondence, an integral-type event-triggered mechanism is integrated with the consensus-based labeled multi-Bernoulli filter (LMB). The proposed algorithm provides a passivation effect that lowers the communication activities while preserving the tracking performance in the uncertain environment with disturbance. The theoretical analysis demonstrates that the integral-type event-triggered mechanism introduces bounded information discrepancy in the sense of Kullback–Leibler (KL) divergence. The proposed algorithm is also verified by numerical simulations in a target tracking scenario. • Integral term is introduced into the ET-based consensus-based LMB filter. • The proposed solution is insensitive to the instantaneous disturbance and outliers. • The theoretical analyses of the stability are provided. [ABSTRACT FROM AUTHOR]