Communication constraints and asynchronous measurements in Decentralized Kalman Filters

Decentralized Kalman Filters are often used in multi-sensor target tracking as such a distributed fusion architecture has several advantages compared with centralized ones. On the other hand, distributed fusion is not only conceptually more complex but the required bandwidth is also likely to be a lot higher. However, a trade-off between bandwidth and performance is possible. In this work, the quantitative amount of performance degradation due to infrequent communication between the fusion nodes is investigated in a typical tracking scenario. Furthermore, as a conclusion, a simple approach to deal with asynchronous measurements is proposed.