Research On Localization Technology Of Wireless Sensor Network Under Complicated Industrial Environment

With the fast development of wireless sensor network, the function and the degree of reliability of wireless sensor network conform to the demand of majority industrial grade applications. The benefits of wireless sensor network are gradually valued, as it’s standard specialized in industrial systems come out. Among wireless sensor network, the location technique is one of the important applications with enormous value in research.There are many different kinds of industrial production field, complex and changeable, papers with mine as an example, discusses the positioning demand research. Mine as a distinctive characteristic of the industrial scene, the traditional underground testing technology can not meet the needs of today’s underground production.This study focused on different environmental characteristics for mine roadway and goaf were selected RSSI and DV-Hop algorithm as an object of study, and proposed optimization solutions.Firstly, in the mine roadway environment, affect the position of the main cause of interference and signal attenuation.In view of this, this paper proposes an improved RSSI location algorithm based on dynamic fading Index.This kind of algorithm obtains path weak index in real environment by given information. Based on it, we can choose a number of beacon nodes with maximum intensity value to obtain their path weak index when mobile node needs locating. Then we can estimate the distance between mobile node and beacon node with path attenuation model and get unknown nodes’ coordinate with least square method. The simulation shows that the location precision has improved a lot without adding extra hardware equipment.Secondly, in the mined-out area environmental impact of the mine is targeting the main cause of the uneven distribution of nodes.it’s ill-considered to think about average hop size with traditional DV-Hop positioning algorithm. Original algorithm only considered one beacon node’s estimated average hop size with minimum distance. However, the distribution of nodes in industrial field is extremely uneven. The average hop size calculated by single beacon node can’t reflect exactly the real average hop size in network. According to this kind of characteristic, we can consider average hop size calculated by several beacon nodes and then do weighted processing with high weights at short range and low weights in remote distance. This kind of average hop size with weighted processing can be served as right reference to unknown notes. The last simulation results show that the location precision has improved.