Research On Intelligent Reflecting Surface Aided Localization Algorithm Based On Convex Optimization

Target localization is an important research problem in the field of signal detection and parameter estimation,and it has a wide range of applications in the fields of wireless networks,intelligent transportation,and smart homes.According to the different positioning processing methods,the target positioning method can be roughly divided into two types: two-step positioning method and direct positioning method.The basic idea of the two-step positioning method is to first use positioning signals to obtain distance parameters between nodes,such as receiving angle,transmission delay,and received signal strength.Then,according to the relevant distance measurement,trilateral positioning or multilateral positioning are used to determine the position parameters of the target.Compared with the two-step positioning method,the direct positioning method uses the received signal waveform to establish the optimization problem of the target airspace parameters.The position parameters of the target are obtained directly by solving the optimization problem,thereby avoiding the measurement problems of intermediate parameters such as receiving angle and transmission delay and simplifying the algorithm steps.The direct positioning method constructs the optimal problem of the target position parameter,while the optimization problem of the two-step positioning method is often sub-optimal.At present,domestic and foreign scholars have proposed many effective positioning algorithms based on direct positioning or two-step positioning.These algorithms usually assume that there is a line-of-sight link between nodes.However,in the actual scene,due to the occlusion of tall buildings and other reasons,it is not guaranteed that the line of sight path between nodes must exist.In the absence of such a line-of-sight path,the positioning performance of traditional algorithms will usually be significantly reduced or invalidated.Therefore,target parameter estimation under the condition of missing line-of-sight path is the difficulty and focus in target positioning research.In recent years,as an emerging wireless communication technology,intelligence reflecting surfaces have received extensive attention in the fields of communication and signal processing.The outstanding advantage of the intelligence reflecting surface is the ability to customize wireless channels.Specifically,when the signal transmission path between nodes is blocked,the phase or amplitude parameters of the intelligence reflecting surface unit can be set to establish a reflecting path between the transceiver node and the intelligence reflecting surface to ensure the reliable transmission or realization of information Target positioning when the line-of-sight is occluded.Even if the line-of-sight path exists,the reflection path established by the intelligence surface can also increase the channel gain,thereby enhancing the information transmission capacity of the system or improving the accuracy of parameter estimation.In summary,the study of target positioning assisted by intelligent reflecting surfaces is very beneficial to enhance the parameter estimation performance or solve the target parameter estimation problem in the scene with missing line-of-sight paths.Therefore,this paper uses convex optimization theory as a mathematical method to study the target positioning algorithm assisted by intelligent reflecting surfaces.The specific work is as follows:(1)Analyze the current situation of target positioning research at home and abroad,summarize the classic two-step positioning and direct positioning algorithms.In particular,simulation analysis of positioning algorithms based on optimization theory and sparse representation,such as-SVD and SPICE,are carried out,and the parameter estimation performance of these algorithms under various conditions is discussed.(2)Aiming at the situation where the line-of-sight path of the target node and anchor node is missing due to obstacles,an intelligent reflecting surface-assisted direct positioning algorithm based on convex optimization is proposed.The algorithm consists of three steps: first,determine the optimal phase control matrix of the intelligence reflecting surface according to the mapping relationship between the received signal energy and the phase parameters of the intelligence reflecting surface;secondly,use the threshold detection algorithm to estimate the transmission between the intelligence reflecting surface and the target node Time delay parameters are used to determine the area of the target node and divide the location grid;finally,according to the determined target area and location grid,a convex optimization problem of parameter estimation is established and the target parameters are solved.The simulation results of the algorithm show that the proposed algorithm can effectively estimate the location parameters of the target node when the line-of-sight path is missing.(3)Aiming at the coexistence of the line-of-sight path and the intelligence reflection path,this article extends the aforementioned intelligence reflection surface positioning algorithm to this application scenario.The basic idea of the algorithm is to establish the target parameter estimation optimization problem by constructing the target function about the target position and direction angle and the corresponding position and angle area constraints.This optimization problem is a second-order cone programming problem,which can be effectively solved by the convex optimization toolbox.Simulation experiments prove that this method can reliably estimate the position parameters of the target node.