| Wireless Sensor Networks(WSN)has been an important part among people’s life in the area of flood prevention even disaster prevention,medical care and military operations.WSN integrates wireless communication technology,micro-sensor system technology,information distribution and integration technology and so on,and realizes the collection,analysis and processing of information in the target area through mutual cooperation between nodes.There are many aspects of wireless sensor network technologies waiting to be studied and developed.Node positioning technology is the foundation and key technology of WSN.Accurate and efficient positioning lays a foundation for providing information for various detection positions.Therefore,it is necessary to design an effective and low energy consumption node location algorithm for specific scenarios of dense and node computation.In this research,the merits and demerits of monte Carlo localization algorithm are compared with rencently mainstream localization algorithm in WSN.Two algorithms which are become better are come up with the conventional algorithm,which can improve the localization accuracy by changing the filtering conditions and optimizing the weight of the algorithm.The mostly important research substances include these following contents:(1)Describes the development background and practical significance of wireless sensor network,and discusses the basic working principle,structure and related terms of WSN.This paper introduces the research status of WSN at home even abroad,and finally gives the performance evaluation criteria to judge the strengths and shortcomings among the algorithms.(2)Introduces a typical location algorithm based on non-ranging: Monte Carlo location algorithm.An improved Particle swarm optimization Monte Carlo Localization algorithm-IPSOMCL was proposed to analyze the shortcomings of traditional algorithms.The convergence of the algorithm is accelerated,and the filtering stage of the algorithm is improved,and crossover mutation operation is added to prevent it from falling into local optimization.The simulation proves which the accuracy of impove algorithm is improved 15 percent,the accuracy improves 21 percent when the anchor is arisen.(3)In the case of collinear anchor nodes of Monte Carlo positioning algorithm,positioning error increases,and after the resamping stage,sample diversity decreases due to the same weight given to sample points.The anchor node screening mechanism is introduced to calculate the collinearity value of anchor nodes so as to avoid collinearity.On this basis,Mean Shift vector of sample points is calculated to update the weight of samples and improve the diversity of samples.The results of simulation display the improved algorithm can improve the positioning accuracy and network coverage validly,decrease the number of void nodes,and improve the performance of the algorithm. |
