Research On Sensor Selection Algorithm For Target Tracking In Wireless Sensor Networks

A wireless sensor network(WSN)is a multi-hop ad-hop network system consisting of a large number of tiny,low-cost sensor nodes,which are randomly deployed in a monitoring area,collaborative sense the environment and process the sensed data,communicate with each other through wireless communication,and transmit the results to the user.Wireless sensor networks have been widely used to military,intelligent transportation,environmental surveillance and health care.And target tracking is one of the most representative applications of WSNs.Since sensor node are densely distributed in the monitored area,if all the sensor nodes which can detect the target are used to the target tracking to achieve high tracking accuracy,energy consumption will reduce the lifetime of the network.The node selection algorithm is to select a subset from the candidate sensors to reduce the energy consumption and extend the network lifetime while meeting the tracking performance.Several selection algorithms are proposed for different target tracking environments.The main works and contributions are summarized as follows:1.A multi-step node selection algorithm is proposed based on the extended Kalman filter(EKF)for a moving target with low maneuverability.An objective function has been constructed by weighting the determinants of the multi-step prediction-error-covariance matrices,and a sensor subset is selected from the candidate sensors to maximize the function.The proposed algorithm has been compared with the one-step algorithm in terms of root-mean-square-error and average residual energy.2.A sensor selection algorithm based on the CRLB(Cramer-Rao lower bound)-like of extended H? filtering has been proposed for the case of having no knowledge of the statistics of sensor noises and the maneuvering properties of the target.The proposed algorithm is compared with the random selection algorithm and the NN(nearest neighbor)-based selection method in terms of tracking performance and energy consumption.3.In the centralized tracking applications,the leaders are required to spend huge communication and computational energy,which will cause the failure of the nodes.A target tracking algorithm is proposed based on the sequential processing of the extended Kalman filter,which allocates the energy consumption on communication and data processing among each sensors of the tracking cluster,without the requirement for a leader to receive and process the measurementdata from other sensors.The proposed algorithm has been evaluated in terms of computation time and tracking performance.In conclusion,this dissertation focuses on the sensor selection problem for the target tracking in wireless sensor networks.The results obtained have not only important theoretic values,but also extensive practical values.