Research On Passive TDOA Location Algorithm Of High-Speed Unmanned Aerial Vehicle

In passive TDOA location,the observation station does not send electromagnetic wave signals,but only receives electromagnetic wave signals from radiation sources.Therefore,its concealment is stronger than that of active location.It is widely used in radar,radio communication and other fields.This thesis studies the location algorithm of high-speed unmanned aerial vehicle based on TDOA information,discusses and studies the location principle and classical algorithm of TDOA,the minimization of the number of unmanned aerial vehicle observation stations,how to fuse the target position by multiple measurements for high-speed unmanned aerial vehicle is discussed and studied,and puts forward the corresponding solutions.The specific research contents of this thesis are as follows:1.The basic principle of TDOA location and the classical Chan algorithm of TDOA are studied.The non solution area and fuzzy area of the algorithm are discussed and simulated,and the corresponding solutions are given.2.The localization algorithm based on the minimization of the number of UAV observation stations is studied.When TDOA information is used for localization,two stage weighted least square(TSWLS)requires five observation stations in three-dimensional space to complete TDOA localization due to the introduction of a new variable.Although the Taylor series iterative method can realize four station positioning,it needs a more appropriate initial value to drive the Taylor series for iteration.When the initial value of the target of the radiation source to be measured deviates greatly from the real value,the Taylor series may diverge,that is,the position value of the target to be measured cannot be obtained.In view of the above problems,this thesis studies a closed Taylor algorithm,which can realize four station positioning in three-dimensional space,and does not need an initial value to drive the algorithm like Taylor series iteration method.First,the closed Taylor algorithm is similar to the Chan algorithm in dealing with the intermediate variables.The intermediate variables are regarded as known numbers,and then a univariate quadratic equation is constructed by using the geometric relationship between the intermediate variables and the target to be measured.After solving,the initial value of the target to be measured can be obtained,and then the initial value of the target to be measured can be corrected by the error estimation function,so as to improve the positioning performance.3.By comparing the CRLB under the condition that the position of the observation station is accurate and there is base address error in the position of the observation station,it can be found that the base address error of the observation station will reduce the positioning accuracy.Then comparing the positioning performance of the iterative method and the analytical method,it can be concluded that when the base address error is large,the initial iterative value of the iterative method deviates from the real value greatly,resulting in large positioning error,and its positioning performance is not as good as that of the analytical method.Then,under the passive TDOA location model of high-speed unmanned aerial vehicle,the factors affecting the location performance are analyzed,such as the layout of observation stations,the spacing of observation stations and the base address error of observation stations.Finally,based on the high-speed unmanned aerial vehicle model,a positioning method is proposed.The UAV observation station calculates the approximate area of the target according to the initial formation,then changes the observation station twice according to the initial value,and finally fuses the position parameters of the target after multiple measurements and formation transformation.The simulation results show that the positioning results of the UAV observation station through this flight mode are close to the cramero boundary.