Fusion performance in long-haul sensor networks with message retransmission and retrodiction
In a long-haul sensor network, sensors are remotely deployed over a large geographical area to perform certain tasks. We consider a class of such networks where sensors take measurements of one or more dynamic targets and send state estimates of the target(s) to a fusion center via satellite links. The severe loss and delay inherent over the satellite channels render insufficient the number of estimates successfully arriving at the fusion center, thereby limiting the potential fusion gain and resulting in suboptimal accuracy performance of the fused estimates. The system can adopt certain retransmission-based transport protocols so that lost messages can be recovered over time. However, excess delay may be incurred that can potentially violate the deadline for reporting the estimate. For many applications, though, retrodiction/smoothing techniques can be applied so that the chances of incurring such excess delay are greatly reduced. In this work, we analyze the extent to which retrodiction, along with message retransmission, can improve the performance of delay-sensitive state estimation tasks. Results of numerical and simulation studies of an illustrative example and a ballistic target tracking application are shown in the end to demonstrate the validity of our analysis.