Improved diffusion Kalman algorithm with packet-dropping in wireless sensor networks
Guangyue Lu · 2013
In this paper,an improved diffusion Kalman filter algorithm in connection of the problem for data fusion in wireless sensor networks is proposed and an improved scheme is achieved.When packet-dropping exists,the nodes with packet-dropping from their neighbor nodes sets are excluded by the improved algorithm in order to reduce the bad effect of packet-dropping on estimated values.In profile of the data fusion,nodes are designed to readjust the fusion weights and to reduce the bad impacts of the packet-dropping on the estimated values.Simulation results show that the improved algorithm has a better performance than the traditional one.This mainly reflects on the lower average error bias under several certain circumstances.Besides,leader nodes turn to have greater effects on the estimated value of the system than general nodes.Therefore,the problem can be improved by choosing the nodes with enough energy as leadership or strengthening the maintenance of those leader nodes.