Adaptive Consensus-Based Distributed System for Multisensor Multitarget Tracking

In this article, a new comprehensive system for distributed multisensor multitarget tracking is proposed. All of its functions, including track initiation, confirmation, maintenance and termination, and track-to-track association and fusion, are built around the concept of the probability of target existence (PTE). A new track maintenance algorithm is composed of the correction part, with data association requiring computations linearly depending on the number of measurements and tracks, and the prediction part, containing an adaptive consensus scheme, coping with limited sensor observability. A new track-to-track association and fusion algorithm based on an approximation of track association probability is also proposed, ensuring consistency and continuity of individual tracks. Track initiation and termination algorithms are derived on the basis of local PTEs. Stability of the proposed system is studied for the steady state and time-varying regimes. The system as a whole achieves high performance close to the centralized solution, outperforming all the comparable existing state-of-the-art approaches, keeping much lower communication and computation requirements.