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Research on Multi-Sensor two Level Fusion Algorithm Based on Neural Network

Data fusion technology is the key technology of wireless sensor network, which Can reduce the amount of transmission of the sensor data; which can significantly improve the network's perceived performance, extend the network life cycle, reduce the time delay. Multi-sensor data fusion can obtain more accurate information than single sensor. This paper estimates the monitoring variables from the measurement data with noise, proposes a multi-level fusion algorithm based on the neural network. Simulation results show that the fusion results of the proposed algorithm are better than the mean value estimation algorithm and adaptive weighted fusion algorithm in precision and fault tolerance, which Can better adapt to the requirements of data accuracy in today's large data environment.