Research And Application Of Strapdown Inertial Navigation Initial Alignment Algorithm On Track Inspection Trolley

With the rapid development of China’s high-speed railway,the orbital inspection work during the operation period is facing the severe challenge of high-speed rail operation with short window period and high efficiency requirements.At present,the high-speed railway track detection mainly adopts the track inspection trolley measurement system.The traditional track inspection trolley has relatively low detection efficiency.How to improve the work efficiency of the track inspection trolley has become an urgent problem to be solved.The Strapdown Inertial Guide Inspection Vehicle Measurement System adopts high-precision strapdown inertial navigation to locate the absolute positioning of the trolley and the total station assisted positioning.It can realize the continuous detection of the orbital geometry and improve the detection efficiency.The initial alignment provides the necessary initial attitude matrix for the strapdown inertial navigation system,which is an important guarantee for achieving high-precision navigation and positioning.This paper studies and verifies the initial alignment algorithm of Strapdown inertial navigation system based on the Strapdown Inertial Guided Track Inspection Vehicle Measurement System,which is currently being developed by the research group.The main research work is as follows:(1)Introduced the basic composition of the traditional track inspection trolley and the strap-on inertial guide rail inspection vehicle.Based on the characteristics of strapdown inertial navigation,the design scheme of strapdown inertial guide inspection car was designed.The measurement principle of the free station method is studied and the mathematical model of the adjustment is derived.(2)The Strapdown Inertial Navigation Algorithm is studied,and the attitude update equation,velocity update equation and position update equation are derived.Based on this,the disturbance term is added to obtain the attitude,velocity and position error equations of the strapdown inertial navigation,which provides the basis for the initial alignment of Kalman filter observation equations.(3)The measurement data outputted by the inertial sensing element IMU contains a large amount of random noise,which has a certain influence on the accuracy and efficiency of the initial alignment.In this paper,the wavelet transform threshold denoising method is used to preprocess the original data.The simulation results of denoising effect by hard threshold function method and soft threshold function method show that the soft threshold function method has better denoising effect.(4)Since the initial alignment environment of the strapdown inertial track inspection car is relatively stable when applied to the track detection,this paper designs the static base initial alignment algorithm.Calculating coarse pose matrix by using analytical coarse alignment.On this basis,the attitude misalignment angle is accurately estimated by the precise alignment Kalman filtering algorithm,and the coarse attitude matrix is corrected to obtain the accurate attitude matrix.The simulation experiment is carried out to verify the static pedestal initial alignment algorithm.The results show that the error and alignment time between the three attitude angles and the true attitude angle of the initial alignment meet the requirements.(5)The Strapdown Custom Rails Carriage,which is currently being developed by the research group,is used as a verification platform to collect five sets of data in two different poses for static base initial alignment algorithm verification.The results show that wavelet transform data preprocessing can effectively improve the efficiency of initial alignment.The estimation error of the misalignment angle eventually converges near the theoretical value.The standard deviation of the attitude angle obtained by initial alignment of multiple sets of data in the same attitude satisfies the tolerance requirement.And prove the stability and applicability of the design algorithm in the strap-down inertial track inspection vehicle.