Research And Design Of Localization Algorithm In Wireless Sensor Networks

Wireless Sensor Network (WSN) consists of large numbers of cooperating small-scale disposable low-powered nodes. These nodes can supervise, collect and disposal all information in their communication range and then send results to net user. Now, WSN is wildly used in national defence, circumstance inspecting, traffic control etc. Most of these applications are based on position information of nodes. Localization plays an important role in these areas and also routing of WSN.Based on SCIN(Supervisory & Controlling Intelligent Networks) nodes designed by ourselves, this dissertation suggested an improved range-based localization algorithm - RMIC (RSSI-Margin & Improved Chan) which suggested using BP-loss model to decrease ranging error.Firstly, this dissertation introduced the structure and applications of WSN and then describes the basic theory of localization algorithm, like ranging theory, typical localization algorithm and current status in WSN.Specially, this dissertation classified localization error into three parts: system error, signal loss error and computing error. And then it found ways to decrease each of them to improve the whole performance of localization algorithm. Based on the research about propagation theory of radio wave and a large number of RSSI date collected by SCIN, this dissertation compared three signal loss models through simulation test and suggested a BP-loss model to get smaller ranging error. Then, considering the character of SCIN, this dissertation suggested an improved range-based localization algorithm-RMIC. When sink node sent localization order, target node broadcasted localization request to all neighbor nodes. Anchor nodes who received the request can get the RSSI of target node and then estimated the distance from target node to them by BP-Loss model. Especially, this algorithm took the margin of these distances and solved the non-linear equation by optimized Chan algorithm to improve the accuracy. When the net has enough anchor nodes, each anchor node was treated as target nodes separately. They all had different anchor nodes choice to keep smaller error. We got the number collection of anchor nodes corresponding to every anchor nodes. When localization really begun, target nodes found the anchor node which has the strongest RSSI. Then it chose the suitable anchor nodes from the collectionDetailed simulation experiments were operated step by step and the results indicated RMIC localization algorithm had better performance than classical RSSI algorithm.Finally, this dissertation introduced the SCIN and shows the results of mechanism validation and demonstration.