MAC delay in belief consensus for distributed tracking

In target tracking applications where many sensors must have a common view of the target's state, distributed particle filtering with belief consensus is an attractive solution. It allows for a fully distributed, scalable solution, guarantees consensus in connected networks, and converges fast for network with high connectivity. However, for medium access control, high connectivity is detrimental, possibly leading to a different convergence/performance trade-off. We study the delay/performance trade-off of distributed particle filtering with belief consensus in the presence of time division medium access control. We found that for small networks, (i) the impact of max-consensus should be accounted for; (ii) a simple round-robin schedule combined with a large communication range gives the best delay/performance trade-off.