Distributed fusion architectures are often used in multi-sensor target tracking as they are more robust and more flexible than centralized architectures. Furthermore, they allow for a reduction in the required communication bandwidth with only limited effect on the estimation performance. The trade-off between bandwidth and performance is analyzed in detail for the special case of a decentralized Kalman filter. As a result of this study, a conservative fusion approach for such systems with a reduced communication rate is proposed.