Research On UAV Navigation Technology In Signal Barrier Area

In the inspection of transmission lines,special environments such as high altitude and unmanned area is often encountered.The resulting signal blockage makes it impossible for the GPS/SINS to guarantee the normal operation of UAV.In order to solve the above problems,this paper studies the Sandia inertial terrain assisted navigation(SITAN)in depth.At the same time,in order to improve the accuracy of the algorithm,particle filter(PF)applied to nonlinear system is adopted to replace Kalman Filter(KF),and an adaptive scaling method of digital elevation map(DEM)is incorporated into the SITAN.In addition,taking into account the actual engineering,the error of the inertial device used by the UAV platform is relatively large.Therefore,in the absence of GPS,this paper calibrates and compensates the deterministic error of inertial devices in the inertial navigation system to improve the overall navigation accuracy from the perspective of hardware.The main work of this article:1.Make an in-depth analysis of the research background of this article,explain the necessity of this study,and introduce the relevant theories in detail,namely terrain-aided navigation(TAN),nonlinear filtering technology,and the scale-down algorithm,both at home and abroad.2.Briefly introduce the terrain height-aided matching principle and its subsystem composition in TAN,study the current classical algorithm SITAN in detail.We establish a state model based on SINS inertial error equations,and then calculate the error parameters by KF to compensate the error of SINS.3.Conduct a detailed study of the basic principles of SINS,and establish the error model of sensors,speed,position and platform angle respectively.We make a calibration experiment of inertial devices,accelerometers and gyroscopes,test and analysis the result.At the same time,we simulate the inertial navigation system,and compare the reference positon curve with curve achieved after the error compensation to verify the validity of the device error calibration.4.In order to improve the accuracy of SITAN,PF and adaptive scale down algorithm are introduced.We analysis the advantages of PF,study the basic principles and calculation steps in detail.We compare and analysis commonly used linear interpolation methods.Mearwhile,the principle of wavelet transform adopted to solve the problem of edge sawing caused by bilinear interpolation is studie.In addition,we simulate the scaling algorithm by matlab.5.We use the electrical parameters at the start time of the UAV achieved by several tests to set the initial state of the aircraft.Based on the real flight trajectory of the drone,we compare and analysis the navigation accuracy obtained by different algorithms after simulation under matlab.In order to improve TAN’s accuracy,we introduce PF and adaptive scaling in this paper.The results of simulation prove that SITAN can improve the accuracy more than 90% compared to a single INS.The latitude and longitude accuracy of SITAN based on PF are 35.1m and 28.6m.After introducing the bilinear interpolation method,the latitude and longitude precisions are 19.3m and 19.4m respectively.After introducing the wavelet transform,the latitude and longitude precisions reach 8.6m and 12.1m respectively.