Research On UAV Wireless Positioning Algorithm Based On TDOA

With the increasing popularity of fifth-generation mobile communication,infrastructure construction is becoming more and more perfect,and commercial coverage is becoming more extensive.Low-altitude Unmanned Aerial Vehicle is also included in the layout of commercial scenarios by many industries because of their advantages of small size,high flexibility,low cost,etc.The wireless positioning technology of the UAV,as the key technology of the UAV application,also brings a series of technical challenges.The TDOA-based UAV wireless positioning method is widely used because of its simplicity and efficiency.However,the traditional TDOA positioning algorithm has low positioning accuracy in complex environments and cannot meet the application requirements of UAVs in 5G scenarios.Therefore,this paper conducts an in-depth study on the high-precision positioning algorithm of UAVs suitable for the current 5G coverage.Firstly,We propose a joint TDOA-based minimum residual weighted Chan-Taylor algorithm under line-of-sight propagation conditions.The method of screening and combining base stations in position estimation by Chan algorithm is improved by using the principle of minimum residual error,and different weights are assigned in the weighting process to increase the degree of group discrimination.Taking the estimated coordinates solved by the improved algorithm as the initial value of the Taylor algorithm,the final positioning result is solved iteratively.Secondly,to address the severe degradation of localization accuracy under nonvisual propagation conditions,we propose an improved genetic ant colony hybrid localization algorithm based on TDOA based on the above algorithm.The algorithm optimizes the generation process of the initial pheromone of the ant colony algorithm using the genetic algorithm.Take the estimated coordinates obtained by the improved Chan algorithm as the node position.By improving the efficiency and convergence of the algorithm in the solution space,the problem of poor positioning accuracy of TDOA algorithm in non line of sight is improved.Finally,we proposed a tracking and positioning algorithm using a combination of an improved genetic ant colony hybrid algorithm and extended Kalman filtering,where the estimated value processed by extended Kalman filtering is used to correct the bias positioning.Then the trajectory tracking of the UAV can be completed according to the precise position coordinates.