RSSI-GA-Base Static Node And Improved MCL-Base Mobile Node Localization Algorithm For Wireless Sensor Networks

Wireless Sensor Network (WSN) is made up of a large number of sensor nodes which deploy in a monitoring region. Sensor nodes within the region construct a multi-hop Ad hoc self-organization network system through wireless communication, and they sense, collect and process environment data, send the corresponding data to users. WSN is developing quickly with the development of sensor technology, embedded computing technology, distributed information Processing technology, communication technology and micro-motor technology. And WSN is a new technology which is widely used in agriculture, military defense, environmental monitoring areas and so on.In the Wireless Sensor Network, the event location or the node location which can collection data is one of the basic functions. Localization in the Wireless Sensor Networks is a key technology and research hotspot. The paper researches some basic theoretical knowledge of the wireless sensor network and node localization. And then based on the RSSI-GA static node localization algorithm is proposed. Finally, a kind of improved MCL mobile node localization algorithm is proposed.Firstly, the wireless sensor networks and the basic knowledge node of node localization is studied. Some typical localization algorithm is analyzed, including static node localization algorithm with mobile node localization algorithm.Secondly, based on RSSI localization algorithm and genetic algorithm are discussed in detail. The advantages and disadvantages of the algorithm are analyzed. According to the actual problems of localization in the WSN, the node location algorithm of WSN combing with the genetic algorithm and RSSI is proposed. The theoretical analysis shows good performance of the algorithm. The simulation result shows that the proposed algorithm is able to determine the accurate position of the unknown nodes currently. And then comparing to the RSSI and other algorithm, the proposed algorithm has lower error which is also verified by the simulation.Finally the mobile node localization algorithm based on MCL is researched and discussed. We analyze advantages and disadvantages. And then a kind of improved MCL algorithm is proposed. The proposed algorithm reduces the sampling range using the "anchor" and "sampling box" theory, filters sampling points by movement forecast model, and regulates sampling number according to the sampling range. The simulation result shows that the proposed algorithm is able to determine the accurate position of the unknown nodes currently. And comparing to MCL, the improved MCL algorithm has lower error.