Dissertation > Industrial Technology > Radio electronics, telecommunications technology > Wireless communications > Mobile Communications

Research and Improvement on Tracking Algorithm in Wireless Sensor Networks

Author ZhangZhenYu
Tutor WangLiSong
School Nanjing University of Aeronautics and Astronautics
Course Applied Computer Technology
Keywords Wireless sensor networks Tracking Particle filter Prediction mechanism
CLC TN929.5
Type Master's thesis
Year 2009
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Target tracking based on sensor networks have broad application prospects, such as wildlife, medical research and military intelligence gathering , earthquake relief and other areas are of great significance. Goal of this study is to make these applications we can accurately grasp the real-time location tracking target , as well as in the context of limited energy of nodes extending sensor network lifetime . The main work is as follows : ( a ) respectively, based on the binary sensor network model and the network model based on precise positioning sensors under both architectures tracking algorithm analysis and research. ( 2 ) focus on two different architectures Typical tracking algorithm OccamTrack and Cluster-based predictive tracking algorithm mechanisms are inadequate to start from the structural characteristics of sensor networks , target tracking accuracy, energy consumption point of view of the shortcomings of the algorithm and proposed improved method feasible . ( 3 ) the use of the idea of ??particle filtering for binary sensor network model characteristics and geometry of OccamTrack algorithm is studied and improved, presents a new particle filter based geometry processing algorithms. ( 4 ) for precise positioning based clustering model WSN target tracking algorithm, using Bayesian estimation improved distributed cluster head node prediction mechanism and made a recovery track failure tracking mechanism . ( 5 ) to build simulation program simulation platform and writing , respectively, of the two algorithms to improve the simulation results and detailed comparative analysis of the results seen from the simulation , two improved algorithm in target tracking accuracy, the angle of the energy consumption better than the original algorithm .

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