A WSN Range Method Based On The Frequency Difference Measurement

With the quick development of information technology, as one of the most important new technologies, wireless sensor network (WSN) attracts more and more attention. And with its application technology being more mature, the range of application being more widely, WSN is smoothly changing the existing working patterns. Compared to WIFI, Bluetooth, and Ad hoc, it has greater advantages and more superior characteristics in communication distance, energy consumption, and etc.The wireless sensor network (WSN) consists of a set of intelligent sensor nodes that communicate in a wireless ad hoc manner. These nodes can form a network automatically, collect object data collaboratively and send the data to viewers. But as the application conditions of WSN are too tough for people deploying the nodes, mostly the nodes have to be deployed in a random way without acquiring the location information ahead of time, thus leaving the data nonsense. So the automatic localization of the nodes becomes the base of lots of applications, such as target tracing, target monitoring and so on.This paper firstly introduces the basic concepts of automatic localization of the nodes and some of the existing localization methods. Secondly, this paper illustrates the evaluation indexes in the localization, and evaluates the existing localization algorithm according to the indexes.This paper proposes a new range algorithm based on the frequency-difference measurement. The algorithm is based on the linear frequency-modulation theory. In the network, the nodes which have localized themselves will send linear frequency modulation signals (LFM), and the unknown nodes will record the arrival time of different LFM signals. By demodulating the LFM signals received, the instant frequency can be computed. As the difference of the instant frequencies could reflect the distance difference of the unknown nodes, the unknown nodes can complete the localization after getting more than three LFM signals. In all, this method does not require strong time synchronization or great quantity of distribution of the anchor nodes. Besides, simulation results showed that the algorithm has low complexity and high precision. And it can be applied for both the2-D and3-D localization.