Research And Realize On Optimization Techniques In Wireless Sensor Network Localization

In the study of localization in wireless sensor networks.The localization based on mobilebeacon node got more and more attention because it had higher positioning accuracy and hig-her flexibility and could save the hardware cost a lot. Dynamic path planning of mobile beac-on node is the focus of the research in this field. The precision problem of convex positionhad been restricting its application in more occasions. Therefore, it is necessary to improve it-s accuracy for this algorithm.The RSSI range-based location had been widely applied withoutthe need for additional hardware cost.But the RSSI value need to be processed for its instabil-ity.This paper focused on optimization technology in three aspects which are the dynamic pat-h planning for mobile beacon position,the precision improvement for convex algorithm and the RSSI value process in RSSI range-based localization.In the aspect of path planning of mobile beacon node this paper put forward a six direct-ion model.The model include the moving path of mobile beacon,the positioning algorithm co-mbined with this path and the moving decision of mobile beacon.The guiding node concept h-ad been put forward in the research of dynamic path planning. The unknown node which ha-d already been localized and in the communication area of the beacon node in current timed-eserved to upgrade for a navigation node.We devided the guiding node into different types a-ccording to its positioning accuracy and positioning information of its neighbour nodes and gi-ved them different weights.Finally it used the guiding node which has the largest weight toassist the mobile beacon complete its moving decision.In order to solve the problem of low precision of convex algorithm.This paper put forwa-rd a positioning strategy which combines the RSSI and Convex. This algorithm narrows theexistence region of unknown nodes one step further by comparing the RSSI valve to each be-acon and by means of the relationship between RSSI and distance. Through this way it coul-d promote the positioning accuracy effectively.According to the problem that the RSSI value is easily affected by the environment duri-ng RSSI range-based positioning process.This paper presented the Kalman filter to be appliedto handle the RSSI value. It had constructed the iterative model and corresponding parametersas well.It recursed in "forecast-Test-revision" order. According to the observed value to e-liminate the random interference in RSSI system and reappear the original state of reproducedsignal.The experiment result shows that the output processing results using Kalman filter is cl-oser to the true value compared with the traditional processing methods such as moving aver-age filter and the Gauss filter. It could guarantee the accuracy of distance conversion and po-sitioning cation results.