An energy efficient prediction based protocol for target tracking in wireless sensor networks

Target tracking is one of the most attractive applications of wireless sensor networks, used for estimating the moving target's position accurately. A primary challenge in this domain is achieving precise target path estimation while conserving energy resources. This paper introduces an energy-efficient target tracking protocol in wireless sensor networks, considering both accuracy and reduced energy consumption. The protocol uses the Kalman filter to estimate the target's position and predict the subsequent step of its path. In each step of target tracking, a selected sensor, named the 'leader' performs computations for position estimation and path prediction, while two other sensors, known as 'assistants' help the leader in the tracking process. Leader selection within the protocol is performed in two phases: an initial phase occurring upon the target's entry to the network and a subsequent phase named the forced handoff phase. The forced handoff phase performs the selection of a new leader when either the target exits the sensing range of the current leader or the leader's energy decreases significantly. Although the proposed protocol is a new work, it can be considered as an improvement of the PPCP protocol by adding several changes and also replacing the binary variational filter with the Kalman filter. The efficiency of the proposed protocol is evaluated through simulations in Matlab. Results demonstrate the protocol's ability to achieve high-precision target tracking while maintaining low energy consumption. Comparative analysis shows its energy efficiency, which significantly increases the network lifetime.