An overview of non-centralized Kalman filters

for state-estimation has recently gained increasing attention due to its cost effectiveness and feasibility. One of the major challenges of state-estimation via WSNs is the distribution of the centralized state-estimator among the nodes in the network. Sig-nificant emphasis has been on developing non-centralized state-estimators considering communication, processing-demand and estimation-error. This survey paper presents different method-ologies to obtain non-centralized state-estimators and focuses on the estimation algorithms and their implementation. The tem-perature distribution of a bar is used as a benchmark to assess the non-centralized state-estimators in terms of estimation-error and communication requirements. Index Terms—Wireless Sensor Networks, distributed state-estimation, Kalman filter