A Novel IMU Extrinsic Calibration Method for Mass Production Land Vehicles.

Vicent Rodrigo Marco,Jörg Raisch,Thomas Seel,Jens Kalkkuhl

doi:10.3390/s21010007

Vicent Rodrigo Marco, Jörg Raisch + Show 2 more

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https://doi.org/10.3390/s21010007

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Abstract

Multi-modal sensor fusion has become ubiquitous in the field of vehicle motion estimation. Achieving a consistent sensor fusion in such a set-up demands the precise knowledge of the misalignments between the coordinate systems in which the different information sources are expressed. In ego-motion estimation, even sub-degree misalignment errors lead to serious performance degradation. The present work addresses the extrinsic calibration of a land vehicle equipped with standard production car sensors and an automotive-grade inertial measurement unit (IMU). Specifically, the article presents a method for the estimation of the misalignment between the IMU and vehicle coordinate systems, while considering the IMU biases. The estimation problem is treated as a joint state and parameter estimation problem, and solved using an adaptive estimator that relies on the IMU measurements, a dynamic single-track model as well as the suspension and odometry systems. Additionally, we show that the validity of the misalignment estimates can be assessed by identifying the misalignment between a high-precision INS/GNSS and the IMU and vehicle coordinate systems. The effectiveness of the proposed calibration procedure is demonstrated using real sensor data. The results show that estimation accuracies below 0.1 degrees can be achieved in spite of moderate variations in the manoeuvre execution.

Highlights

Received: 17 November 2020 Accepted: 16 December 2020 Published: 22 December 2020Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.Accurate and reliable information of the vehicle ego-motion is pivotal for the proper operation of active safety and automated driving functionalities
The present paper addresses the extrinsic calibration of a vehicle equipped with series chassis sensors and an automotive-grade inertial measurement unit (IMU)
It proposes a method to estimate the misalignment between the IMU and vehicle coordinate systems

Summary

Introduction

Received: 17 November 2020 Accepted: 16 December 2020 Published: 22 December 2020Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.Accurate and reliable information of the vehicle ego-motion is pivotal for the proper operation of active safety and automated driving functionalities. In order to meet the high accuracy and reliability demands, multi-modal sensor fusion has become ubiquitous in the field of vehicle motion estimation [1,2,3]. In a multi-modal sensor fusion set-up, the individual information sources supply motion quantities that generally relate to different points within the vehicle and are expressed in different coordinate systems. From our experience, in car mass production, IMU mounting errors of few millimetres and two to three degrees can be expected These inaccuracies in the transformations between the individual coordinate systems deteriorate the performance of fusion algorithms and may even cause the estimator to diverge [4]. Many applications require calibration procedures that estimate the transformations between the different coordinate systems This process is known in the literature by extrinsic calibration [5,6]

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