title: Multisensor-Based Periodic Estimation in Sensor Networks With Transmission Constraint and Periodic Mixed Storage.
abstract: In this paper, we consider a periodic estimation problem in sensor networks with a shared communication channel. The transmission constraint is inevitable in a single-channel-based sensor network if the sensors are heterogeneous or deployed far away from each other. A novel stochastic competitive transmission strategy is presented to deal with the transmission constraint, such that the sensors communicate with the fusion center (FC) in a strict asynchronous manner. A periodic mixed storage strategy combing the zero-input and the hold-input mechanisms is presented to describe periodic updating of the stored information in the sensors' buffers. A recursive Kalman filtering algorithm is derived for the FC to periodically generate estimates of state variables describing an object by using a linear continuous-time stochastic model. Two simulation examples are presented to show the effectiveness of the proposed results.
authors.forename: Haiyu
authors.initials: H
authors.lastname: Song
authors.forename: Wen-An
authors.initials: WA
authors.lastname: Zhang
authors.forename: Li
authors.initials: L
authors.lastname: Yu
authors.forename: Bo
authors.initials: B
authors.lastname: Chen