Research On Target Localization And Tracking Technology In Random Access Wireless Sensor Networks

Wireless sensor networks are often used to monitor physical or environmental parameters such as temperature,sound,speed,and are widely used in military,environmental,medical and industrial fields.For applications that require long-term monitoring,data collection with resource(power,bandwidth)limited is a challenging challenge.Based on the above scenario,this thesis studies the energy-efficient realization of target l localization and tracking in wireless sensor networks.Firstly,the research background and research status of the research are summarized,and the related technologies of target localization and tracking in wireless sensor networks are introduced.The basic theory,key technologies and applications of compression perception are introduced emphatically.The main target localization and tracking algorithms in wireless sensor networks are briefly introduced.Then,the research on target localization technology based on random access wireless sensor networks is studied.The system model of wireless sensor networks is proposed,and a random access compressed sensing scheme is discussed.The scheme uses a compressed sensing technology to make the network have high energy efficiency under a combination of random sensing and random channel access.The above scheme is used in target localization in wireless sensor networks,and the target localization is limited to the problem of sparse recovery,through the technology normalization and minimization of l1 to achieve localization.The simulation results show that the proposed method can make the target localization in the sensor networks with high precision by using less data.Finally,the problem of target tracking in random access wireless sensor networks is studied.Based on the target localization technology of random access wireless sensor networks,a new target tracking algorithm with low complexity is proposed.The algorithm introduces an adaptive mechanism that makes the loss of target trigger a new round of localization.The simulation results show that the proposed target tracking algorithm achieves the same accuracy by using less data than the target localization.