Considering the characteristics of energy constrained of sensor node itself in wireless sensor networks

a combination of data fusion algorithm was proposed base on D-S evidence theory.Firstly

the current value of Sensor network data was classified to some cluster based on the standard deviation

and then each category of data sets was fused by using D-S evidential reasoning algorithm

and the result would be treated as a virtual sensor node data.Finally

the outlier of virtual node data vectors was obtained by calculating Mahalanobis distance and weighted integration was completed via the outlier.Simulation results demonstrate that the credibility of identifying the target with the algorithm is higher than D-S reasoning method

and the algorithm in computational complexity has also a clear advantage.