Protocol Of Target Tracking And Simulation Of Distributed Detection For Wireless Sensor Networks

Target tracking is an important application in wireless sensor networks (WSN). In WSN, target tracking should be considered with the characteristics of WSN, such as self-organization, low storage, low computing power, communication latency, reliability, etc. To save the energy of the sensors, get more accurate results and prolong the life of WSN, we should propose a protocol of target tracking, which can not only solve all of these questions but get good results.In this thesis, we propose a dynamic clustering for target tracking in WSN. We envision a hierarchical sensor network that is composed of CHs and low-end sensors. The proposed protocol overcomes several drawbacks of traditional static cluster architecture, such as the perspective of fault tolerance and sharing information. To deal with the problem of collision, we propose a two-phase broadcast mechanism and random delay mechanism. The dynamic system models are established and the computer simulations are performed using OMnet. The simulation results confirm the effectiveness of the proposed method, which could make a more accurate estimation of the target's location. Furthermore, we use Monte Carlo to analyze two distributed detection schemes, they are person-by-person optimization scheme in the presence of nonideal channels and distributed detection in a bandwidth-constrained sensor network. The two schemes consider the design of local decision rules and fusion decision rule in the presence of nonideal transmission channels between the sensors and the fusion center.