Information fusion under network constraints

In this paper, various techniques for information fusion in distributed sensor applications are presented. In the considered scenarios a number of challenges exist due to limitations on the communication between sensor nodes. Firstly, the challenge of delayed data processing is addressed in order to present solutions for optimal state estimation when out of sequence data is received at the fusion center. Secondly, solutions for Measurement Fusion and Track-to-Track Fusion in distributed sensor applications with the challenge of constrained communication are summarised. In a simulative evaluation the behaviour of several approaches under conditions of a reduced probability of successful communication is investigated. It is found that decorrelated distributed tracking performs better than a central Kalman filter when communication is constrained.