IMU/5G Millimeter Wave Integrated Positioning Method For Driverless Cars

In recent years,driverless car has developed rapidly.As the basis of decision,planning and motion control,positioning technology has become a research hotspot in the field of driverless car.At present,the positioning methods used in driverless car have problems such as low accuracy,high cost and susceptibility to environmental influences.Nowadays,5G communication technology is becoming popular.Its characteristics of low delay,high speed and wide coverage can greatly improve the accuracy and real-time performance of driverless car positioning,which has broad application prospects.On the basis of 5G key technology,the positioning method of driverless car in 5G environment is studied in this thesis,a 5G millimeter wave positioning method based on angle of arrival(AOA)is proposed,and the positioning of driverless car in 3D navigation coordinate system is realized.Aiming at the problem that 5G millimeter wave cause large positioning errors due to non-line-of-sight transmission,a positioning method of driverless car based on the combination of IMU and 5G millimeter wave is proposed,which improves the positioning accuracy and positioning reliability of driverless car.Firstly,the advantages and disadvantages of common wireless location methods are analyzed in this thesis.According to the technical characteristics of 5G,AOA location is selected as the location method of 5G millimeter wave;aiming at the requirement of AOA positioning for the accuracy of DOA estimation,a two-dimensional estimation of signal parameters via rotational invariance techniques(ESPRIT)algorithm based on total least squares(TLS)is proposed under the technical background of 5G massive MIMO antenna,considering the influence of two subspace errors at the same time,an iterative method is designed to estimate the rotation factor’s similarity matrix.Compared with the traditional two-dimensional ESPRIT algorithm,the estimation accuracy of signal azimuth and pitch angle is improved.Secondly,based on the angle of arrival obtained by the improved two-dimensional ESPRIT algorithm,an AOA three-dimensional positioning model of driverless car based on 5G millimeter wave is established.Aiming at the strong nonlinear characteristics of the positioning model,Gauss Newton method is used to estimate the position of driverless cars iteratively,and the iterative expression of the Gauss Newton positioning algorithm is derived.Considering that Gauss Newton method is sensitive to the iterative initial value,the weighted least square estimation of the driverless car position is realized by linear transformation of the nonlinear positioning model.The estimation result of the weighted least square method is selected as the iterative initial value,which avoids the Gauss Newton positioning algorithm converging to the local optimal solution and improves the accuracy of 5G millimeter wave positioning.Finally,aiming at the requirements of the stability and reliability of the driverless car positioning,the IMU/ 5G millimeter wave integrated positioning method for driverless car is proposed.By analyzing the advantages and disadvantages of different data combination methods and system filtering methods,an integrated positioning system scheme based on loose combination and indirect filtering is constructed;according to the scheme of the integrated positioning system,the state equation and measurement equation of the system are established,and the integrated positioning algorithm based on Kalman filter is designed to realize the IMU / 5G millimeter wave integrated positioning of the driverless car.The simulation results show that the problem of IMU positioning error accumulation is overcome by IMU / 5G millimeter wave combined positioning method,and the positioning accuracy of driverless car is improved under non-line-of-sight transmission of 5G millimeter wave signals.