Research And Optimization Of 3DDV-Hop Localization Method In Wireless Sensor Networks

Wireless Sensor Networks(WSNs)is a technology that integrate node information collection,transmission,and processing.If the node location information cannot be obtained and processed timely,the collected location information will be meaningless.Three-Dimensional Distance Vector Hop(3DDV-Hop)localization algorithm based on range-free measurement does not require additional equipment and has low complexity,it is widely used,but there are problems of low localization accuracy and high energy consumption.How to improve node localization accuracy,optimize localization algorithm performance,and reduce energy consumption is a hot issue in WSNs localization technology research.The main research work and contributions of this thesis are as follows:(1)For purpose of decreasing the hop size errors and algorithm overhead,a 3DDVHop localization method based on optimal anchor node set to correct hop size is proposed.The anchor node set that is closest to the unknown node in the non-collinear and noncoplanar area is selected by the set method;Combined with the Received Signal Strength Indicator(RSSI)ranging model,the optimal anchor node set,and the hop count correction method,the hop size calculation method is refined based on the hop count of 1 and multi hop counts.Experimental results show that the proposed algorithm has high positioning accuracy in basin and mountain application scenarios.Due to the influence of coverage holes in basin terrain,the localization accuracy is not ideal,and its energy consumption is higher than that of mountain terrain,but the overall energy consumption is lower.(2)For purpose of decreasing localization errors and improve localization performance,a 3DDV-Hop localization method based on hop count and location optimization is proposed.The four-communication radius method is used to divide the communication radius into four spheres with different radii and redivide the hop count;The unit vector is used to construct a correction vector,and the maximum likelihood estimation is used to optimize the coordinates of the unknown nodes;The radio irregularity model is introduced to evaluate the localization accuracy of the improved algorithm in different application scenarios.Experimental results show that,in basin and mountain application scenarios,the localization accuracy of the proposed algorithm is higher than the other three algorithms.In basin terrain,the frequency and efficiency of communication between nodes in the coverage hole area are enhanced by using the fourcommunication radius,which reduces the localization errors and optimizes the localization performance.(3)The K-means clustering algorithm is used to improve the sparrow search algorithm.During population initialization,due to the random distribution,there are some problems such as incomplete solution space and coverage holes.A 3DDV-Hop localization method based on improved sparrow search is proposed.Sparrow roles are classified by K-means clustering algorithm,and scrounger positions are updated by sine and cosine optimization algorithm;The objective function is reset and the optimal solution of unknown nodes is calculated iteratively.According to the convergence curves of 20 benchmark functions,the convergence rate of this algorithm is better than that of SSA and LSSA.In basin and mountain terrain,the localization accuracy fluctuates smally,and the growth of energy consumption is slow.The localization accuracy of mountain terrain is superior to that of basin terrain.