Self-localication Algorithm For Wireless Sensor Networks

Wireless sensor networks, which integrate technologies of micro-electro-mechanism, sensing, embedded computing, distributed information processing and wireless communication, lead to a new pattern of information gathering and processing. It has wide application foreground, can be widely used in military, environment, medical treatment and health care, space exploring and various business applications. Determine the location of the incident or the location of access to information nodes is the prerequisite for many applications, this is also a key technology which the sensor network studies the node localization question.Node self-localization is a prerequisite to other objective positioning. The basic node localization means is: the deployment of a small number of beacon node and the other unknown node calculate their coordinates by measuring the distance to the reference node, angle, or pursuant to the relative location, network connectivity.In this paper, we discussed the relevant node localization technology, focusing on analysis and simulation to the DV-Hop algorithm based on the multi-hop routing, and pointed out the impact that the network topology layout, layout beacon node, node beacons bring to the positioning accuracy, analyzed the localization error and error distribution of the algorithm.Proposed improving suggestions based on the original algorithm, mainly embodied in the following three aspects: to use the mean of the average distance of the jump each time, and set up the reception threshold in nodes, using weighted least squares method to calculate the estimated location of nodes. Simulated to improved algorithm, the results show that any improvement can improve the localization accuracy in varying degrees. In order to reduce the amount of computation, the paper also proposed using Min-max algorithm to calculate coordinates.Finally, position estimation algorithms which will determine the location of the node by solving hyperbolic equations were discussed, mainly referred to Taylor series expansion method.