Multi-sensor consistency data fusion algorithm in observation uncertainty

Aiming at data effective fusion process of multi-sensor information gathering system in observation uncertainty,a multi-sensor consistency data fusion algorithm is proposed.Mahalanobis distance is introduced to approximately estimate the consistency degree between two sensor observations.Combining with the properties of membership function in fuzzy theory,a new support degree function is defined to extract and utilize the local observation information,and the support degree matrix which can synthesize global observation datas is construction.By calculating support degree matrix to solve the weight of each sensor observation data in evaluation system state estimation to estimate the real value of system state by weight fusion.Theoretical analysis and simulation experimental results verify the efficiency of algorithm.