Research On Relative Positioning Method Of Mobile Self-organizing Sensor Network Based On TOA

Wireless self-organizing sensor network is a highly independent information network that integrates micro-electromechanical subsystems,overall system-level chip digital circuits,and various high-precision radio signal transmission,reception,and transmission sensors.Wireless self-organizing sensor networks originally originated from special small-scale mobile networks related to natural science research.They were deployed in the vast nature to achieve real-time observation and related data collection,such as forest fire detection,animal and plant growth detection,and atmospheric monitoring.Today,sensor networks have been widely used in other fields,such as logistics networks,vehicle networks,drone networks,service industries and agriculture and animal husbandry,smart homes and other industries.It is foreseeable that,whether in civilian,military,or other traditional or new industries such as unattended,wireless self-organizing sensor networks will gradually replace manual labor and play an increasingly important role.With the rapid development and innovation of wireless self-organizing sensor network disciplines year by year,this discipline technology has also begun to subdivide many related majors and various sub-disciplines in recent years.However,before conducting in-depth research on wireless sensor networks,the first and must be solved is the positioning problem of the sensor network.Only when the positioning problem of the sensor network is solved,the overall network topology can be constructed,and then the actual network can be analyzed.Planning,layout,communication between nodes,energy consumption,and other issues.Therefore,by referring to a large number of existing research results on sensor networks,as well as the latest research progress and directions at home and abroad,this paper focuses on the self-localization algorithm between nodes in the entire network,and through the traditional localization algorithm Based on the summary and comparison,a positioning model that compensates for the clock error is proposed.Through theoretical derivation and experimental proof,the correctness and feasibility of the model in this paper are verified.From the structure of the text,this article first gives an introduction to the wireless sensor network,and then briefly explains the research and development process of this subject technology,and then gives an overview of the TOA measurement method,TDOA measurement method and AOA measurement,etc.Then analyzed the related problems of the above measurement methods.The paper then introduced the current commonly used positioning algorithms,including classic traditional linear,or extended Kalman filtering algorithms that can be used in nonlinear environments,and a new multi-dimensional positioning method that has emerged in recent years.Next,the paper gives a common clock model to perform corresponding time correction and node time synchronization between nodes.By estimating the clock offset and clock skew of the TOA measurement value,the relevant clock correction and clock skew are performed on this basis.Synchronize to get a more accurate TOA measurement value.By combining the clock model of the node and the movement model between the node pairs,a new and more accurate measurement model is given.At the same time,the Kalman filter equation under this model is deduced,and another linearization method that is simpler and more feasible under nonlinear conditions is deduced.At the same time,the above-mentioned measurement model is also applied to the multi-dimensional scale algorithm.By solving the above-mentioned measurement information,the relative position between the nodes of the corresponding sensor network is obtained,and then translation and rotation are performed to convert the relative position estimation estimated in the algorithm.Estimation information for the absolute positioning of the network node.At the same time,this article also uses the position estimation method in the case of TOA measurement information is incomplete(ie,weak correlation network).Through the matching method of public nodes,it effectively improves the relative positioning accuracy in the case of incomplete node information.From the structure of the text,this article first gives an introduction to the wireless sensor network,and then briefly explains the research and development process of this subject technology,and then gives an overview of the TOA measurement method,TDOA measurement method and AOA measurement,etc.Then,after analyzing the above-mentioned measuring party paper,related simulation experiments were carried out through MATLAB software to realize the experimental construction of the related positioning system of the algorithm of this paper.The experimental results show that in the relative positioning problem of nodes under high-speed moving conditions,the problem in the paper is Compared with the existing GLS algorithm,the algorithm has better and stable properties.On the other hand,it also demonstrates the correctness and necessity of the clock error correction in this paper.