Wireless Sensor Network Node Localization Algorithm Based On Hop Count Classification And Local Information

With the development of computer and semiconductor industry,wireless sensor network has become the focus of popular computer related direction.As one of the core and support technology,location has been widely used in many related fields,such as geological survey,agricultural production and field monitoring.In these applications,the collection of data is often meaningless if there is no spatial and temporal coordination of the collected data.Now many related location algorithms mostly focus on the location information recognition by using the whole range of global information.This method does not make full use of the local information between neighbor nodes,and is vulnerable to the influence of node density and node distribution.In this paper,we will focus on the local information localization method of nodes,and use the local information between nodes to depict the distance between nodes,which can overcome the limitation of using global information to locate unknown nodes.And this method is vulnerable to nodes distribution and network density.The work and main contents of this article are as follows:(1)Firstly,we focus on the classic DV-Hop algorithm in Range-free location,including related improvement methods,and analyze the existing problems of the algorithm and some factors that affect the positioning accuracy.After focusing on the related localization algorithm,an improved strategy is proposed to reduce the influence of different hop average hop distance on the overall positioning results.Then we introduce the weighted least squares method to fit the nonlinear variation of cumulative error,which can be better control the different weight in the different.And then it makes the positioning error further reduce,and has better adaptability for different node density.(2)At present,the localization method based on global information has some limitations,and the localization method based on local information can better overcome these limitations.Then this paper focuses on the positioning of local information and deficiency of existing algorithms based on the research and the corresponding improvement measures.And then we put forward a kind of forward distance localization algorithm based on prediction of the lower limit of the local information,which only need to use the connectivity of nodes that can be estimated by the number neighbor nodes.And it can decrease the effect of node density on the localization error.(3)In improved positioning algorithm,many localization algorithms based on local information and some need to obtain the energy of the received signal,but the signal energy is easily influenced by environment,different experimental scene and real scene,leading the algorithm of error increase.And then aiming at these problems,we focus on the application of local information in the localization algorithm.This paper proposes a method to depict the distance between nodes by using local information of nodes.Moreover,the estimation of the distance between nodes can be obtained without acquiring the information of the received signal,enhancing the robustness of localization algorithm.