Resource Allocation Of Interfered Wireless Localization Network

Recently,with the development of wireless communication technology,wireless localization technology has gradually become one of the hot topics in academia and industry.The fundamental goal of wireless localization technology is to obtain the location information of targets quickly and accurately.Localization accuracy is not only affected by the network topology,environmental noise,localization methods and interference of surrounding networks,but also determined by resources allocation strategy.Therefore,the squared positioning error bound is taken as the evaluation index to study resources allocation of interfered wireless localization network.Firstly,interfered non-cooperative wireless localization network is investigated.After obtaining the closed form of the squared positioning error bound,two optimization models are established based on whether the signal-to-interference-and-noise ratio is considered.Since these optimization problems are non-convex,successive convex approximation based Polynomial Compression algorithm and Improved Complete Taylor Linearization algorithm are proposed to solve them.Simulation results show that both algorithms can converge fast,and the resources allocation strategies in this thesis are superior to the traditional allocation strategies.Secondly,resources allocation strategy of interfered cooperative wireless localization network is investigated in the case that anchors cannot cover the whole network.The problem that the squared positioning error bound of the cooperative wireless localization network has no mathematical expression is solved by estimating the upper bound of localization error.Two optimization models are established according to whether the resources of targets can be allocated.Boundary Relaxation Particle Swarm Optimization algorithm and Improved Boundary Relaxation Taylor Linearization algorithm are proposed to solve them.Boundary Relaxation Particle Swarm Optimization algorithm requires few mathematical characteristics of the optimization problems and has strong practicability.Simulation results show that the Boundary Relaxation Particle Swarm Optimization algorithm can achieve better localization accuracy and Improved Boundary Relaxation Taylor Linearization algorithm is more efficient.In addition,an interfered asynchronous radar localization network is also studied.To be more realistic,it is assumed that not all nodes in the network are synchronized.In this thesis,the Fisher information matrix of joint localization and clock deviation is firstly derived for interfered asynchronous radar localization network.The optimization problems of clock offset estimation and localization are established respectively.The optimal topology of the asynchronous interfered radar localization network is also studied,which is useful for the practical deployment of the network.Finally,due to the error between the estimated target location and the actual location,the actual location based resource allocation strategy is not robust enough.A simple and robust resources allocation strategy based on improved far field condition is proposed.Simulation results show that the proposed strategy can improve the stability of localization compared with the above localization strategies.