Research On NLOS Recognition In Wireless Positioning

As technology continues to advance,positioning technology has become increasingly important in various fields,including intelligent navigation,virtual reality,target tracking,and more.These applications have placed higher demands on wireless positioning technology,requiring high accuracy and real-time performance.However,indoor environments present significant challenges due to complex structures and physical composition,as well as obstacles that can block the straight path between the transmitter and receiver.When the direct path is blocked,the signal can only be received through diffraction,reflection,or refraction,resulting in non-line-of-sight（NLOS）propagation problems.This leads to increased ranging errors,which can significantly impact positioning accuracy.As a result,it is crucial to develop high-performance target localization methods that are suitable for both line-of-sight（LOS）and non-line-of-sight environments.This paper takes"when NLOS errors exist in multilateral positioning,how to identify NLOS errors and eliminate the impact of NLOS errors on positioning accuracy"as a scientific problem,"Virtual high-dimensional coordinates of fixed anchor points"as a driving force,the NLOS recognition technology in wireless positioning is described and studied.The specific research content is as follows:The VHDR_NLOS model has several advantages over traditional non-line-of-sight positioning models.Firstly,it does not require additional measurement equipment,which reduces the cost and complexity of the system.Secondly,it can accurately identify non-line-of-sight signals,which helps to improve positioning accuracy.Thirdly,by extending the coordinates of fixed anchor points to higher dimensions,the VHDR_NLOS model can better capture the complexity of the indoor environment and provide more accurate positioning information.For VHDR_NLOSmodel,this paper uses the Taylor algorithm and the nonlinear equations with constraints algorithm to realize the NLOS recognition and optimize the positioning accuracy.aylor algorithm based on Virtual High-dimensional NLOS Recognition Model(VHDR_NLOS-Taylor),based on the Taylor series expansion,uses the initial iteration value to estimate,and then according to the position obtained from the previous iteration estimate the local least squares solution of the iterative error,and update the position of the target node according to the recursive conditional threshold.The recursive conditional threshold of the algorithm is based on the position deviation obtained by the least squares method to continuously correct the position of the target node to be located.The iteration is terminated after reaching the threshold.The comparison simulation experiment and analysis of a single NLOS recognition scene and multiple NLOS recognition show that:It can realize NLOS recognition and optimization of positioning accuracy.In both positioning scenarios,the positioning accuracy is improved by at least 7cm.For the Nonlinear Equations with Constraints algorithm based on Virtual High-dimensional NLOS Recognition Model(VHDR_NLOS-Non Es Cs),the nonlinear equation is used as the optimization problem,and thedual under the constraints,the model is solved by extreme value optimization and global optimization until the optimal solution is obtained.By applying the VHDR_NLOS-Non Es Cs method to a single NLOS and multiple NLOS simulation environments for different positioning scenarios and from the comparative experiments of other algorithms,it can be concluded that whether in a single non-line-of-sight or multiple non-line-of-sight simulation environments,compared with the multilateral positioning algorithm,the positioning error of the VHDR_NLOS-Non Es Cs method is greater than 8cm.Compared with the SR-WLS and Chan algorithms,the VHDR_NLOS-Non Es Cs method has a positioning error improvement greater than 10cm in a single non-line-of-sight and multiple non-line-of-sight simulation environments;.Finally,the positioning accuracy and performance of the two methods for solving the VHDR_NLOS model are simulated and analyzed,and the following conclusions can be drawn:the VHDR_NLOS-Non Es Cs method has better robustness and stability.VHDR_NLOS-Taylor method has better accuracy when there are enough fixed anchor nodes,and the positioning accuracy of the two methods is qualitatively improved compared with the previous methods.