Research On Location Algorithm Of Wireless Sensor Network Based On Compressed Sensing

As a large and complex network,wireless sensor networks are widely used in various fields.As one of the core technologies,the node localization technology is playing an increasingly important role in practical application.However,because of the shortcomings of low carrying capacity and poor computing ability,many existing node positioning technologies had great limitations.Therefore,it is very important to design a high-precision,low-power location algorithm for wireless sensor networks.Location,also known as location awareness,is a process of inducing stationary targets or moving targets based on existing beacon nodes already known in the sensing area and known position coordinates.In this paper,the node localization algorithm is studied with the background of wireless sensor networks with limited energy and low computing power.The main research contents are as follows:(1)The existing positioning technology of wireless sensor network is analyzed,and some improvement ideas are put forward according to the problems appearing in the positioning process.(2)Aiming at the limited energy and computing power of sensor nodes,a multi level localization algorithm based on compressed sensing is designed to reduce the consumption of node resources in the localization process.The algorithm considers the advantages and disadvantages of range free localization algorithm and localization algorithm,the positioning process using different positioning algorithms,the use of compressed sensing theory to the location of the unknown node process into a sparse signal reconstruction process,and ultimately determine the target location.The experimental results show that the multilevel localization algorithm can not only achieve the high-accuracy location of the unknown nodes,but also effectively reduce the energy consumption of the positioning process.(3)In this paper,a new location precision lifting algorithm based on multi resolution analysis is designed to improve the location error in the positioning process.The algorithm further divides the target grid into multiple areas with equal area,and continuously iterates backtracking and the change of the center value of the target.After comparing with the custom threshold,it achieves the goal of estimating the location continuously moving to the real location.(4)A data compression algorithm based on distributed source coding is designed to make data transmission work after localization process continue to possess the excellent characteristics of low resource consumption of sensor nodes.This algorithm is based on the sensing data exist time and spatial correlation,the joint sparsity model respectively for a data compression in a single sensor node and cluster head node,ensure each process is in the amount of data transmission,finally on the sink node using compressed sensing theory of compressed data reconstruction.Experimental results show that different data compression on different nodes can not only guarantee the integrity of sensing data,but also greatly reduce the energy consumption of data transmission process.