Attitude-Estimation-Free GNSS and IMU Integration

04/20/2023
by   Taro Suzuki, et al.
0

A global navigation satellite system (GNSS) is a sensor that can acquire 3D position and velocity in an earth-fixed coordinate system and is widely used for outdoor position estimation of robots and vehicles. Various GNSS/inertial measurement unit (IMU) integration methods have been proposed to improve the accuracy and availability of GNSS positioning. However, all of them require the addition of a 3D attitude to the estimated state in order to fuse the IMU data. This study proposes a new optimization-based positioning method for combining GNSS and IMU that does not require attitude estimation. The proposed method uses two types of constraints: one is a constraint between states using only the magnitude of the 3D acceleration observed by an accelerometer, and the other is a constraint on the angle between the velocity vectors using the amount of angular change by a gyroscope. The evaluation results with simulation data show that the proposed method maintains the position estimation accuracy even when the IMU mounting position error increases and improves the accuracy when the GNSS observations contain multipath errors or missing data. The proposed method could improve the positioning accuracy in experiments using IMUs acquired in real environments.

READ FULL TEXT
research
12/29/2022

Trajectory Smoothing Using GNSS/PDR Integration Via Factor Graph Optimization in Urban Canyons

Accurate and smooth global navigation satellite system (GNSS) positionin...
research
09/18/2023

GHNet:Learning GNSS Heading from Velocity Measurements

By utilizing global navigation satellite system (GNSS) position and velo...
research
12/19/2020

A Comparison of Three Measurement Models for the Wheel-mounted MEMS IMU-based Dead Reckoning System

A self-contained autonomous navigation system is desired to complement t...
research
01/05/2020

Position Dilution of Precision: a Bayesian point of view

The expected position error in many cases is far from feasible to be est...
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
01/05/2020

Position Dilution of Precision and Bayesian Model of the Observation Error

The expected position error in many cases is far from feasible to be est...
research
09/07/2020

Improving Maritime Traffic Emission Estimations on Missing Data with CRBMs

Maritime traffic emissions are a major concern to governments as they he...

Please sign up or login with your details

Forgot password? Click here to reset