In order to solve the problem of the tradeoff between target tracking performance and sensors energy consumption in wireless sensor networks（WSNs）

a novel algorithm using belief reusing for energy-efficient tracking in WSNs is proposed.WSNs is modeled under dynamic uncertainty environment using partially observable Markov decision processes（POMDPs）

and the optimization of the tradeoff between tracking performance and energy consumption is transformed into solving the optimal function value of POMDPs.The maximum rewards heuristic search algorithm is used to approximate the optimal value with respect to tracking performance.A novel approach called the belief reusing（BR） is presented to avoid repeatedly acquiring belief states

this approach can effectively reduce sensors energy consumption during communication.The experimental results show that the proposed algorithm has its effectiveness in optimizing the tradeoff between tracking performance and energy consumption

so it can meet the requirement of high tracking performance with low energy consumption.