Research On Energy Optimization Of Wireless Sensor Networks For Target Detection And Tracking

Wireless sensor network is an intelligent communication network,which is composed of a large number of micro-sensors in a multi-hop self-organizing manner.It can overcome the spatial constraints and obtain accurate information of the target in real time.However,each node's energy is limited and usually deployed in a complex and dangerous environment.It is difficult to maintain them properly.Once the node runs out of energy,it will lose its monitoring function and decrease the overall monitoring performance of the network.Therefore,how to effectively reduce the network's energy consumption and extend the network's lifetime has become a core problem for most researchers in this field.In this paper,the cooperative monitoring target of wireless sensor network is taken as the research background.The classical clustering routing LEACH protocol is used as the theoretical basis.The extended kalman filter algorithm,taylor series expansion and gaussian approximation and so on are used as the technical means.The dormancy strategy of the node is designed in different state constraints of the motion target,which combine with the impact of the target's motion state on the network's energy consumption.Then improve the energy consumption model of the network and cluster head selection strategy.The result can reduce the energy consumption of the network and prolong the network's lifetime.The main contributions of this paper are as follows:Aiming at the problem that it has not considered the impact of the stationary target and environmental factors on the network's energy consumption in the cooperative detection system of the wireless sensor network,an improved algorithm LEACH-STC based on the stationary target constraint is proposed.Firstly,according to the network's detection performance under the impact of the stationary target,the monitoring performance parameter of the network is constructed,which relate to the environmental factors and the node's hardware.Secondly,according to the monitoring performance parameter of the network,the circular coverage area of the working nodes is determined.Then the node's dormant strategy under the stationary target constraint is designed.Finally,the strategy of the cluster head selection is used to select cluster head in the set of the working nodes.The simulation result shows that LEACH-STC algorithm can effectively balance the network's load,improve the survival rate of the network node by nearly 50%,and increase the residual energy of the network under the premise of satisfying the network detection accuracy.Aiming at the problem that the motion state of the target affects the network's energy consumption,when the wireless sensor network cooperatively track the target,an improved algorithm LEACH-MTC based on the prediction information of the motion target is proposed.Firstly,the extended kalman filter is used to predict the state of the nonlinear motion target.Secondly,combined with the target's prediction information and the network's monitoring performance parameter,the elliptical coverage area of the working nodes is constructed.It is in accordance with the direction of the motion target.Then the dormant strategy of the node is designed with the prediction information constraint of the motion target.Finally,combined with the prediction information of the target to improve the cluster head selection strategy of the LEACH-STC algorithm.The simulation result shows that the improved algorithm LEACH-MTC not only ensures the consistency between the coverage area of the working nodes and the motion trendency of the target,but also effectively improves the number of survival nodes and the network's residual energy.Aiming at the impact of the motion target's time variation on the network's energy consumption,an improved algorithm LEACH-SMTC based on different motion state constraints of the target is proposed.Firstly,based on the LEACH-STC and LEACH-MTC algorithms,the dormancy strategy of the network nodes with resource optimization is designed.It is combined with the target's motion factor and the node's distance parameter.Secondly,the real-time motion state of the target is classified according to the state switch,and the corresponding improved dormancy strategy of the node is executed.Finally,according to the result of the motion target state's classification,the corresponding strategy of cluster head selection is further executed.The simulation result shows that the improved algorithm LEACH-SMTC can satisfy the state time variation of the motion target,and select different strategies in real time to optimize the network's energy consumption,and save the network's resources.