Data Fusion Algorithm for Water Environment Monitoring Based on Recursive Least Squares

In recent years, Wireless Sensor Networks (WSNs) has been successfully applied to the water environment monitoring field. But due to the large area of the monitored waters, the great number of sensor nodes and the vast amount of information collected, the redundancy of data is easy to cause network congestion. In these circumstances, data fusion is essential to WSNs-based water environment monitoring system. Data fusion reduces the energy consumption of communications, but at the same time increases the computational energy consumption. For the purpose of saving energy consumption and prolonging network lifetime, it is necessary and significant to study how to reduce the computation complexity of data fusion. This paper establishes a water environment monitoring network model and a data fusion model in the cluster. On the basis of recursive least squares, the forward and backward recursive algorithms are proposed in order to reduce the computation complexity of data fusion, and the advantages of the new algorithms are analyzed in detail.