This paper studies the problem of energy efficiently multiple objects tracking in wireless sensor network.Tracking a group of similar objects by trajectories clustering instead of tracking every single object can reduce the transmission energy and prolong network lifetime.However

due to hardware limitations of sensors

low sampling rate

as well as complex natures of surroundings

the locations of moving objects may not be precisely obtained

thus uncertainty inherently exists in trajectories.Ignoring the uncertainty will reduce the accuracy of the mining algorithms and affect the object tracking.This paper presents group objects tracking method based on uncertain trajectories clustering.In trajectory mining phase

we build Markov chain model for each uncertain trajectory and then give a new trajectory similarity measure.Finally

we present the uncertain trajectory clustering algorithm UTK-means to cluster the similar trajectories into groups.In group tracking phase

the locations of groups are transmitted to Base Station periodically.Experiments results demonstrate the good mining quality and energy-saving efficiency of our method.