The Research On Self-localization Of Node In Wireless Sensor Network

Wireless sensor network (WSN) is now becoming a new approach of information collecting. Self-localization technique of sensor nodes is an important branch of WSN. Usually data collected are valuable only when positions of corresponding sensor nodes are known; many object tracking applications of WSN require the positions of sensor nodes in advance;and many routing protocols and topology management of WSN are based on the knowledge of geographic position of sensor nodes.Therefore, locating nodes is one of the basic functions of WSN and it is critical for validity of application of WSN.The thesis describes the basic theories and technologies about the localization system in WSN, including the basic principle, measurement technique and class. Based on these discriptions, we study the range based algorithms and quantitatively analyse their performance. Subsequently, we propose an improved Malguki algorithm (Malguki-MDS) combining Malguki with MDS against Malguki's characteristics of selecting the best of many computed results due to strong randomicity, and compare it with Malguki and MDS-MAP on localization precision and complexity of computation. Simulated results indicate that, Malguki-MDS's localization precision is far higher than Malguki's, and is higher than MDS-MAP's when measure distance error is higher than 10%. Malguki-MDS's complexity of computation is 30% of Malguki's, and close to MDS-MAP's.Another research work of the thesis is trying to apply GA to self-localization of nodes in WSN and constructing corresponding model based on analysing the basic principle of GA.we adopt real-code, select GA operators corresponding to the special application, and establish simulation environment on MATLAB, statistically analyse the effection of several factors on the performance of GA, and compare its performance with existent five range based algorithms. Simulated results demonstate that, GA's localization precision is worse than CMA-MDS's, and better than Malguki's, LMS's and CMA's.When the measure distance error is higher or the number of anchor nodes is larger, GA's localization precision is better than MDS-MAP's. The computation complexity of GA is close to that of Malguki, higher than that of MDS-MAP and LMS, lower than CMA's; When the measure distance error is higher or the number of anchor nodes is smaller, GA's computation complexity is lower than CMA-MDS's.Therefore, GA is suitable for the situation which demands more anchor nodes, bigger measure distance error and lower localization precision, furthermore, it fits central localization.