Research on Multi-sensor Data Fusion at Boar Station Based on Chaotic Thoughts

Multi-sensor information fusion refers to the handling for the uniform form of expression obtained by calibration, alliance, correlation and merging towards the data from multiple sensors. Compared with a single sensor, for the solution of the target states or the judgment of target characteristics, multi-sensor information fusion technology can enhance the reliability of the data, improve the accuracy and increase instantaneity of the systems and information utilization, etc. Multi-sensor data can supplement each other, but it may also have lower confidence coefficient and become redundancy. Therefore, the adjustment process for the measured data by the means of fusion algorithm is a key to obtain the accurate data. Based on the algorithm of chaotic thoughts, an algorithm which fused the data of temperature and humidity at a boar station was put forward to carry out an experiment in this paper. The experiment proved that this algorithm was effective to extract the useful information from different fusion data and it obtained a good fusion effect.