An Improved Data Association Based on the D-S Theory In the Passive Senor Networks

To associate the information of multi-target in the passive senor networks, a new association method based on Dempster Shafer theory is proposed in this paper. With the characteristics of the passive senor network (irregular time interval and fuzzy description), this algorithm builds 6 evidence for calculation（including speed changing, Course changing, Time changing, possibility of the observe, attribute member, and Undefined member）. By using the power of different evidence which is calculated from self correlation function, percentage of each member in the association algorithm can be adaptively coordinated by each evidence power and its own belief function. And the association result will be decided by the mulity layer judgement function. The simulation shows that the association improved by the self correlation function based on Dempster Shafer theory in the passive senor networks not only can restrain the obstacle caused by evidence which conflict to other member in evidence group, but also can reduce the calculation time of the association algorithm. It is effective in association with large scale information which is irregular time interval and fuzzy description.and oberversly to prove that this association is better than FCM or traditional Dempster Shafer theory association.