A multi-sensors data fusion method based on the augmented support degree
Jia Yang, Gong Fengxun, Ma Yanqiu · 2010
Due to data fusion with a large number of data on some characteristic index, an improved online data fusion method is proposed. At first, it used a fuzzy-index function to measure the mutual support degree of the observation values. Then an augmented matrix was defined as the criterion for integrated support degree of data from various sensors. According to this augmented matrix's maximum modulus eigenvectors, corresponding weight coefficients of all the observation values were allocated, hence, the final expression of data fusion and estimation was obtained. Finally, an experiment and a simulation were used to compare the proposed method with other two similar fusion methods. Simulation shows that this method is likely have higher precision and strong ability of stableness, and can be employed in uncertain environment with variable sensors.