Research On The Location Algorithm Of Wireless Sensor Networks

Wireless sensor network (WSN) is one of the important research fields of modern information technology.It is composed of a large number of nodes in the collaboration of data collection and processing to complete a specific task. As the rapid development of the micro sensor technology, computer technology and wireless network technology, wireless sensor network (WSN) will greatly change people’s life in the future. The research of wireless sensor network technology has become a big hot spots of current academia.Positioning technology in wireless sensor network applications is very important.It is the foundation of all functions. Low-cost low-power low configuration sensor nodes determine they cannot adopt the traditional GPS location and can only rely on existing resources in the network. Since the node positioning is one of the main research direction of wireless sensor network. For the static networks and mobile networks, the localization is very different.For the static network, this paper analyzes the positioning algorithm based on distance and without ranging localization algorithm. Two types of algorithms have their own several representative algorithms with advantages and disadvantages In general, the formor is more accurate but ranging accuracy links are greatly influenced by environmental factors, which is simple but the accuracy is limited. This algorithm was improved to foster strengths and circumvent weaknesses is the main research direction of the positioning algorithm. Based on centroid algorithm, this paper proposes a weighted centroid algorithm based on self-tuning beacon node which determine the weighted values through the beacon node for the correction, the introduction of beacon nodes, the concept of credibility, the credibility between the node and beacon node distance function in order to reduce the influence of network environment factors on the positioning accuracy. We simulate the new algorithm through the matlab software simulation, from the density of beacon node and node communication radius to compare the centroid algorithm, RSSI weighted centroid algorithm and positioning performance of the new algorithm.The result shows the new algorithm has better positioning accuracy.For mobile network, this paper mainly analyzes the MCL localization algorithm and proposes an Improved MCL algorithm. In mobile network, the mobile node is led to the dynamic change of network topology, and movement of the mobile node is not controllable additional difficulties for positioning.If the positioning method was used here in a static network, positioning error or conditions of use is higher and energy loss is also a problem. MCL algorithm provides the mobile node localization which uses node mobility through sampling prediction, filtering correction method to obtain the location of the mobile node coordinates. In this paper, Improved MCL algorithm gets the movement of the mobile node’s current speed and direction through interpolation of N historical information before to determine a fan-shaped area.Improved MCL effectively reduces the blindness of sampling compared with the circular sampling area of MCL. At last through software simulation, from node density, maximum speed, the density of beacon node three aspects,we compare the advantages and disadvantages of two kinds of algorithms, prove that Improved the MCL algorithm has a better location performance.