The Research On Multi-target Location Algorithms And Tracking Algorithm Based On Wireless Sensor Network

Wireless sensor network(WSN)has important applications,for wireless sensor network(WSN),it is very important information for the location of its nodes,so the research of the location and tracking technology for wireless sensor network has great significance.In many applications,people need to obtain the location information of WSN nodes,it is very important.Without location information,the collected data is meaningless.At present,people require the location-based services,but there are many limitation of the traditional methods,the traditional location methods are complex in calculation and low in accuracy,so the effect is not ideal when facing practical application.This paper focuses on the research of target location and tracking algorithm based on wireless sensor network.The goal is to improve the performance of the algorithm and the accuracy of its location and tracking.(1)This paper analyzes the development,research background and main applications of indoor wireless sensor network location and tracking technology,and summarizes the typical location and tracking methods.(2)Compressed sensing is a relatively new theory developed in recent years,which has been successfully applied in speech signal processing,image processing and so on.At present,the theory has been applied in indoor positioning.This paper studies the matching pursuit algorithm(MP),and then further introduces the orthogonal matching pursuit algorithm(OMP).On this basis,it focuses on the stomp algorithm.This method is based on the classification algorithm of non ranging,through optimization to achieve positioning,combined with QR decomposition preprocessing,in the premise of a small amount of improving the positioning accuracy,the speed of WSN positioning target will be greatly improved.(3)In the aspect of wireless sensor network tracking,the classical Kalman filter method and its improved algorithm are studied firstly,and then the simulation experiments are carried out under uniform and non-uniform motion.Next,particle filter algorithm and particle filter algorithm based on artificial bee colony optimization are studied.The role of artificial bee colony algorithm is to optimize the position of particles and the resampling stage to improve the tracking performance.In this paper,in wireless sensor network tracking,simulation experiments are carried out,in order to verify the performance of the optimized particle filter algorithm.