Research Of Location Optimization Algorithm Based On WSN

Wireless Sensor Networks（WSN） is one of the most important technologies in the21th century. According to the analysis of the media, WSN is in the first place in the topten emerging technologies which have far-reaching impact on human life. It has a greatbroad application prospect in the military, environment, medical treatment and buildingmonitoring etc..In sensor networks’ various applications of events’ monitoring, it always needs topay attention on where the event happened. At present, there are a lot of locationalgorithms, such as centroid algorithm, DV-hop algorithm and so on.But the locationaccuracy is often not good because of the defects of the algorithm and the influence ofexternal environment.This paper first introduces some basic knowledge and relevant content of WSN, thenanalyses some relevant concepts, classfication, evaluation of location technology of WSNand describes some localization algorithms which are commonly used at present. Aiming atdefects of the existing localization algorithms, this paper proposes a new localizationoptimum algorithm based on Particle Swarm Optimization (PSO). Using PSO to optimizea number of LQI（which exist some deviation）which unknown nodes received from sinknode and proving the feasibility of the algorithm. And on that basis, aiming at the defectsthat the PSO may fall into the local optimum when disposing the disperse data, this paperproposes a localization optimum algorithm based on RSSI which is called Quantum PSO(QPSO). It can improve the accuracy and accelerate the convergence speed. In order to testthe algorithm’s optimized result, we proceed simulation experiments and compare theresult with generic localization algorithms’ results and it proved the superiority of thisalgorithm. Finally, we use maximum likelihood estimation (MLE) to the coordinate setting.This paper uses JN5139-Z01-M02as radio modules which made by Jennic Companyto design a set of ZigBee nodes as experiment equipment.There have there kinds of nodes,coordinate nodes, relaying nodes and terminal nodes, and they using different codes toimplement their functions and accomplish the collection of unknown nodes’ LQI receivedfrom sink nodes.The entire system has characteristics of low comsuption, easy expansionand high reliability. The result shows that the QPSO improve the localization accuracy andcan be applied to many applications.