Research On Node Localization Algorithms For Wireless Sensor Network

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. It covers sensor technology, embedded computing technology, distributed information processing technology, communication technology and micro-motor technology, and is of great value to application in military, industrial, medical, transportation, environmental protection and many other areas.Not only are the capabilities of sensor nodes in processing, storage, communication limited, but also their reliance on battery-power by-no-means negligible, for the battery is an irreplaceable resource which has a great impact on the lifetime of the network. All these specific properties of WSN mean great challenges to the researchers. At present, the main research areas of WSN include communication protocols, supporting technologies, network data processing and data management technologies.Localization technology is one of the key supporting technologies in wireless sensor network. As far as applications in WSN are concerned, the node location information is very important. It can be used in identifying the location of the monitoring data, network topology management, location-based route protocol, location-based data storage technologies and so on. In this paper, we mainly study the localization algorithm for wireless sensor networks, and get research achievements as follows:(1) In order to solve the large accumulated errors which exist in iterative localization algorithm, an Iterative Multilateral Localization Algorithm Based on Time Round (IMLBTR) is proposed. This algorithm introduces a triangular placement scheme for placing anchor nodes. Through the triangular placement, it can effectively reduce the number of iterations and correspondingly reduce accumulated errors caused by iterative localization. The algorithm also introduces time round mechanism to make localizing round after round, and limits the minimum number of beacon nodes that localization used in different rounds. So as to assure unknown nodes are localized by beacon nodes which their number of iterations is as few as possible, and by beacon nodes as many as possible. Therefore, it can reduce the localization errors and accumulated errors. Simulation results reveal that the algorithm, with high accuracy, costs fewer computation time and communication overhead. So this algorithm is an energy-efficient and high accurate localization algorithm. However, it requires special placement for anchor nodes.(2) When maximum likelihood estimation is applied to compute unknown nodes' coordinates, the localization error is large. In order to solve this problem, a Minimum Range Error Estimation Localization Algorithm (MREELA) is proposed. This algorithm formulates a function which presents the sum of range errors of an unknown node to its all neighbor beacon nodes, and applies Nelder-Mead simplex method to find the smallest value of the function. When the function obtains the minimum value, the values of independent variables are the locations of the unknown node. The algorithm improves localization accuracy from three aspects:(â…°) Applying the minimum range error estimation method(MREE) instead of traditional maximum likelihood estimation (MLE) to calculate unknown nodes'coordinates, the average localization error of MREE is far lower than that of MLE. (â…±) Adding a localization constraint to prevent applying beacon nodes whose locations are nearly collinear or proximity to each other to localize unknown nodes, localization accuracy is therefore improved; (â…²) By means of timer trigger, the algorithm uses anchors whose iterations are as few as possible to localize unknown nodes, so it reduces localization errors and accumulated errors caused by iterative localization. Simulation results reveal that the localization accuracy of this algorithm is slightly higher than IMLBTR, and it does not require special placements for anchor nodes. However, the computing time of MREE is more than that of MLE.(3) A two-Hop Collaborative Multilateral Localization Algorithm (CMLA) is proposed to solve the problem that the range error is large or sensor node does not support range technology. This algorithm is not only a range-based localization algorithm, but also a range-free localization algorithm. In the algorithm, we propose a new method which is used to estimate the distances between two hop sensor nodes, apply anchor nodes within two hops to localize an unknown node, and use the minimum range error estimation method to compute coordinates of the unknown nodes. When an unknown node can not be localized through two-hop anchor nodes, it is localized by anchor nodes and localized nodes within two hops through collaborative iterative method. Simulation results show that the localization accuracy of this algorithm is very good in larger range errors or without range technique. The algorithm does not require special placements for anchor nodes either.