| Wireless sensor netw orks is a ne w technology to gain and m anage information,and it is highly integrated and given birth to by m any technologies that are the sensor technology, the embedde d computing technology,the distributed information processing technology,the communication technology and so on. Wireless sensor networks is considered to be one of the powerful technology in the 21 st century,that is because that it has great appl ication value and applicatio n prospect in the traffic management,the environmental monitoring,the national defense military the people’s daily lives and so on.However,that some coverage blind area will often appear in the wireless sensor networks(W SN) is leaded to that the deploym ent of sensor nodes is not unifor m due to various co nditions,and the energy is consumed continually in the long tim e work,in addition,the wireless communication distance is limited,and the reliability is poor and the node size is too big.That will seriously affect the function of the sensor networks and the role of the sensor.To solve the problem,the node location technolo gy is the k ey.Therefore,this article will research the nod e localization algorithm in wireless sensor networks.The main content of this paper is as follows:First,the two-phase positioning algorithm has been improved in this paper.In the initial phase,the trilateral centriod algorithm replaces th e Hop-TERRAIN algorithm,that provides a better in itial value for the circulating refinem ent stage.The weighted least square algorithm is replaced by the weighted triangle center of gravity algorithm in the loop refinement stage.Second,the PSO algorithm has been improved in this paper.Sampling efficiency for MCL algorithm is not high and the particles are easily degraded,therefore,the original sampling area is lim ited to the public area of the ad jacent beacon nodes,that improves sampling efficiency and reduces th e amount of calculation of the particle filter algorithm in the p rocess of sampling and resam pling. This paper estim ates the position of the mobile node using the motion model of the mobile nodes and MCL algorithm,then the position correction func tion of the m obile nodes is confirm ed according to the estim ated position and th e distance of the node and beacon nodes.Then the position correction function is quickly optimized by using the PSO algorithm in order to confirm the optimal location of the pending mobile nodes. |
