Optimization Of Wireless Sensor Network Positioning Algorithm Based On Improved DV-Hop

Nowadays,wireless sensor network technology is developing rapidly and is widely used in many fields,localization technology is the fastest growing and most promising branch of information technology in recent years.In many WSN applications,sensed data must be combined with location information,data without location content is often useless,hence node localization becomes one key issue for WSN.Localization algorithms can be classified into two categories: range-based and range-free,based on whether it is required to measure the actual distance or angle information between nodes.Although range-free algorithms provide less accuracy compared to range-based schemes,they are still adopted in many applications,because such algorithms do not require extra hardware and are simple to be implemented.Therefore,improving the range-free algorithms localization accuracy has become the focus of research on node localization.This paper chooses the DV-Hop algorithm of range-free localization algorithm as the research object,the paper proposes an optimization plan by analyzing the source of error,combines simulation experiments to verify the performance of the proposed algorithm,the main work includes:1.The errors of DV-Hop may come from two stages: the stage of estimating the hop distance and the stage of localization.It is proposed an improved DV-Hop localization algorithm based on ranging.First,the anchor node uses three communication radius to broadcast its own location information,other nodes receives the data packet and records the receiving radius value,then uses the distance variable to obtain the ranging correction factor according to the node distribution,and corrects the distance value by the recorded radius value,in the stage of localization,we still use maximum likelihood estimation algorithm.Comparing the experimental error results,the IDV-Hop-RL algorithm can reduce the average localization error by 58.6% compared with the DV-Hop algorithm.2.Aiming at the problem of the accumulation of errors caused by the maximum likelihood estimation algorithm in the stage of localization,DE algorithm is introduced,it can transform the localization problems into an intelligent optimization problems,but DE algorithm has slow convergence speed and premature phenomenon,therefore,the two parameters of the mutation factor and the crossover probability factor are optimized,and dynamically adjusted with the number of iterations,it reach the dynamic balance of global search and local search.So a dynamic parameters differential evolution localization algorithm is proposed,namely DPDE algorithm.The simulation results show that the improved algorithm not only satisfies the diversity of the population,but also achieves the purpose of fast convergence and high accuracy.3.Combining DPDE algorithm with IDV-Hop-RL algorithm,an algorithm is designed which is Improved DV-Hop Ranging-Based Dynamic Parameters Differential Evolution Localization Algorithm,namely IDV-Hop-DPDEL algorithm.It can improve the efficiency and accuracy of optimization.To verify the effectiveness of the algorithm,the localization parameters in the simulation remains unchanged other than the three parameters vary within a certain range,i.e.,the total number of nodes in the network,the proportion of the anchor nodes,and the communication radius.The experimental results show that IDV-Hop-DPDEL can reduce the average localization error by 50.2% compared with the IDV-Hop-RL algorithm,and the proposed algorithm has better performance than the other two classical improved DV-Hop algorithms.