A GNSS Aided Initial Alignment Method for MEMS-IMU Based on Backtracking Algorithm and Backward Filtering

02/28/2022
by   Xiaokang Yang, et al.
0

To obtain a high-accuracy position with SINS(Strapdown Inertial Navigation System), initial alignment needs to determine initial attitude rapidly and accurately. High-accuracy grade IMU(Inertial Measurement Uint) can obtain the initial attitude indenpendently, however, the low-accuracy grade gyroscope doesn't adapt to determine the heading angle, hence the initial attitude matrix will not be obtained. If using large misalignment angle model to estiamting heading angle, the convergence time will become much longer. For solving these two problems, a novel alignment algorithm combined backtracking algorithm and reverse navigation updating method with GNSS(Global Navigation Satellite System) aiding is proposed herein. The simulation and land vehicle test were finished to evaluate the alignment accuracy of the proposed algorithm. The horizontal misalignment is less than 2.3 arcmin and the heading misalignment is less than 10.1 arcmin in test. The proposed algorithm is a feasible and practical alignment method for low-cost IMU to obtain initial attitude in short term and large misalignment condition aided by GNSS.

READ FULL TEXT

page 1

page 7

page 8

research
09/18/2023

GHNet:Learning GNSS Heading from Velocity Measurements

By utilizing global navigation satellite system (GNSS) position and velo...
research
06/27/2022

A Novel Unified Self-alignment Method of SINS Based on FGO

The self-alignment process can provide an accurate initial attitude of S...
research
02/25/2021

Strapdown Inertial Navigation System Initial Alignment based on Group of Double Direct Spatial Isometries

The task of strapdown inertial navigation system (SINS) initial alignmen...
research
02/24/2021

A Trident Quaternion Framework for Inertial-based Navigation Part II: Error Models and Application to Initial Alignment

This work deals with error models for trident quaternion framework propo...
research
05/15/2022

Learning Car Speed Using Inertial Sensors

A deep neural network (DNN) is trained to estimate the speed of a car dr...
research
08/06/2022

Log-linear Error State Model Derivation without Approximation for INS

Through assembling the navigation parameters as matrix Lie group state, ...
research
12/10/2022

MountNet: Learning an Inertial Sensor Mounting Angle with Deep Neural Networks

Finding the mounting angle of a smartphone inside a car is crucial for n...

Please sign up or login with your details

Forgot password? Click here to reset