ZigBee Node Locating Technology Based On Genetic Algorithm

Wireless sensor network (WSN) technology has been great concern academics, because it have scientific research value and application prospect on many important areas, such as National Defense Science and Technology, Urban Transportation, Biomedical, Environmental testing, etc., is currently a hot issue. ZigBee technology is the most mature WSN, and positioning technology is one of the basic supporting technologies.Firstly the dissertation summarizes the WSN node location technology's significance and development status, analyzes ZigBee technical system, network structure and the topological. The basic principle of node location, methods, and classifications are introduced. And on the basis, analyzes several the Range-Based localization algorithms and the Range-Free localization algorithms.In order to meet the cost of wireless sensor networks, power conditions, etc., the dissertation propose a method, which use RSSI measuring the distance between unknown node and anchor node, use genetic algorithm to optimize it, finally use least-square multilateral measuring method to calculated the unknown node's location.In the stage of the RSSI ranging: In the actual transmission, wireless signals attenuation different with the free space path loss model, because of the influence of multi-path, obstacle, etc. The dissertation selects the Path Loss Model, and measurement the path loss indexη.In the stage of the Ranging results optimization: Node localization problem is essentially an optimization problem. Genetic algorithms is an optimization algorithm which simulate the natural evolution, simple operation, easy to implement and has strong global search performance.In the last, Node location calculation: There is always error in the measurement, this paper according to the least square principle, use multilateral measurement, it makes the model error be the smallest.Finally, part of the circuit and the software modules are designed based on CC2530 and CC2431. And the new algorithm and do not use of optimization algorithm and localization algorithm to the test. The experimental results show that the improved algorithm can improve location accuracy. Compared with other algorithms, it reduced the cost.