Research On Indoor Positioning Based On Ellipse Localization Algorithm

Wireless sensor positioning technology is another major research hotspot following the maturity of GPS positioning technology.In the military field,the security protection system has a wide range of applications.Among them,in the indoor positioning technology based on wireless sensor devices,the positioning effect is more affected by the multipath effect,and the improvement of the positioning quality has attracted much attention.Therefore,the indoor positioning has become a key and difficult point in the wireless sensor positioning technology..In the current indoor positioning technology,there are still some problems that need to be improved.For example,the positioning cost is high,the positioning time is still too long after the accuracy is reduced,and the positioning accuracy is affected by the hardware of the device.To address the shortcomings of localization algorithms,the paper designs ellipse positioning and MPBL algorithm to complete multi-node and single-node positioning tasks faster.At the same time,in a single point positioning algorithm,it also has the advantages of low cost and controllable precision.Based on the existing defects and deficiencies in indoor positioning,the paper analyzes the positioning algorithm and feature principle,sets up a simulation model,improves the localization algorithm for single node and multi-node positioning problems and simulates the experiment,and finally presents the corresponding solution.According to the basic principle of RSSI traditional location algorithm,the paper improves and improves the trilateration algorithm,introduces the Newton Leibniz method to derivation,finally designs the ellipse positioning method and realizes the single node positioning.According to the ellipse positioning algorithm,the ideal experimental environment was simulated,and many kinds of positioning effects such as good flexibility were verified.Multiple experiments were run to test the ellipse positioning algorithm.We found that the algorithm was inadequate and analyzed its causes.The algorithm was analyzed and deduced and proved by geometry.A more complete single node positioning solution was further proposed and the feasibility of the solution was verified by experiments.In order to solve the problem of multi-node real-time location,this paper analyzes the base station information and Huawei’s experimental data,and designs a positioning method based on Lagrange multiplier method named MPBL algorithm to solve the problem of multi-nodal fast positioning.In addition,the paper analyzes the positioning of other non-traditional hardware devices,introduces CSI fingerprint positioning technology,and designs a non-traditional device positioning technology.Combining big data and cloud computing related technologies and assisting with machine learning algorithms,the scientific optimization direction of positioning is proposed.For the ellipse positioning algorithm,by analyzing the data of the simulation experiment,we verified that the positioning node obeys the two-dimensional Gaussian distribution,and then solves and draws the error cumulative distribution map corresponding to the positioning node.Based on the improved algorithm,a positioning algorithm with many advantages such as good accuracy,low cost,and good flexibility is proposed.And constructing model simulation location experiment verification algorithm is feasible.The paper uses the MPBL algorithm in combination with the experimental environment and location data of the experimental location set up by Huawei.The experiment verifies that the algorithm has the characteristics of high speed and good positioning quality.Then optimize Huawei’s positioning experiments,including but not limited to base station number optimization,base station screening algorithm,analyze and draw a function diagram of the number of base stations and positioning accuracy,and study the relationship between connection degree and positioning accuracy,and give the function The diagram shows that the MPBL algorithm has superior positioning effect compared with the traditional algorithm,and finally provides a cost-effective positioning solution.