Data Fusion of Multiª²Target Tracking in
Wireless Sensor Networks
Wang Huanzhao£¬Fan Lin£¬Wang Hai£¬Li Zengzhi
£¨School of Electronics and Information Engineering£¬Xi'an¡¡Jiaotong¡¡University£¬Xi'an
710049£¬¡¡China£©
Abstract£ºAccording to the study on the data fusion problem of multiª²target tracking
in wireless sensor networks£¬ an improved fuzzy cluster mean (FCM) algorithm is proposed
and the corresponding centralized fusion scheme is provided. Firstly in the algorithm£¬
each batch of sensed data is divided according to association threshold of the estimated
position of the tracks. Then the fuzzy association is carried out for the collected data
in the track and the corresponding threshold respectively£¬ and the data that has the
highest associated degree is assigned to each track and regarded as the practical
position. The idea of the data fusion scheme is to delete all data within the association
threshold and the track starting module is processed again for the rest of data.
Simulation experiments show that the proposed scheme can solve the mistracking and surge
problem of multiª²target tracking£¬ furthermore£¬ it effectively avoids the problem of
missing targets and repeated tracking targets£¬ since the scheme can not only save the
usable data but also delete redundant data.
Keywords£ºwireless sensor network£» multiª²target tracking£» data fusion£» fuzzy
cluster mean