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Research Of WSN-Based Localization And Navigation System For Fire Fighters

Posted on:2012-04-20Degree:MasterType:Thesis
Country:ChinaCandidate:S F ChenFull Text:PDF
GTID:2348330482957008Subject:Pattern Recognition and Intelligent Systems
Abstract/Summary:PDF Full Text Request
In recent years, large-scale construction disasters happen frequently, the casualties and economic losses of which are staggering. According to the survey, because the environment of fire scene is abominable and the internal structure of large building is complex, many fire fighters can't get reliable information from the fields. The fire fighters can't find the escape routes and may even lose their precious lives. Therefore, wireless sensor network is applied in the localization for the fire fighter, two effective localization algorithms are proposed, and a system of localization and guidance towards the fire fighters based on wireless sensor network is researched and designed in this thesis.The localization algorithm based on received signal strength (RSSI) for wireless sensor networks is researched in this thesis. For the large error of RSSI ranging localization, the localization algorithm based on the probability distribution model is proposed. Firstly, the distance based on RSSI ranging is revised. Secondly, the common communication region is divided into grids, and the confidence degrees of unknown nodes in every grid are calculated. Finally, the coordinates of unknown nodes are calculated according to the centroid of spatial grids. Simulation results show that the localization accuracy of the algorithm is better than the traditional methods based on RSSI.The hypothesis testing localization algorithm based on Extended Kalman filter is proposed. As the fire scenes are almost non line of sight, the problem of the mobile node localization under NLOS environment is studied in this thesis. Moreover, both the wireless signal ranging model and the signal strength probability model respectively under the environments of the line of sight and non line of sight are established. Furthermore, hypotheses test of the NLOS environment is implemented and the nonlinear state estimation is applied with the extended Kalman filter. Finally, the results of hypothesis testing are fusioned with the probability and the localization of the mobile node is calculated using the maximum likelihood estimation algorithm. Simulation results show that, compare with the extended Kalman filter localization algorithm, hypotheses testing localization algorithm based on extended Kalman filter has higher localization accuracy.The system of localization and guidance towards the fire fighters Orientation is designed. For the need of the actual function, the application program is developed under the Windows CE operating system platform, and the proposed location algorithms are transplanted to the system of localization and guidance. Experimental results show that the walking track of the fire fighter is displayed in the terminal unit, so as to help fire fighters to escape.
Keywords/Search Tags:Wireless sensor networks, fire fighter, localization and guidance, received signal strength indicator, extended Kalman filter
PDF Full Text Request
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