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用于全球导航卫星系统/惯性测量单元（GNSS/IMU）导航的不同等级微机电系统（MEMS）惯性测量单元（IMU）传感器噪声评估

Assessment of Noise of MEMS IMU Sensors of Different Grades for GNSS/IMU Navigation.

作者信息

Suvorkin Vladimir, Garcia-Fernandez Miquel, González-Casado Guillermo, Li Mowen, Rovira-Garcia Adria

机构信息

Rokubun S.L., Paral·lel 88-1, 08015 Barcelona, Spain.

Research Group of Astronomy and Geomatics (gAGE), Universitat Politècnica de Catalunya (UPC), Campus Nord, Jordi Girona 1-3, 08034 Barcelona, Spain.

出版信息

Sensors (Basel). 2024 Mar 19;24(6):1953. doi: 10.3390/s24061953.

DOI:10.3390/s24061953
PMID:38544217
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10975684/
Abstract

Inertial measurement units (IMUs) are key components of various applications including navigation, robotics, aerospace, and automotive systems. IMU sensor characteristics have a significant impact on the accuracy and reliability of these applications. In particular, noise characteristics and bias stability are critical for proper filter settings to perform a combined GNSS/IMU solution. This paper presents an analysis based on the Allan deviation of different IMU sensors that correspond to different grades of micro-electromechanical systems (MEMS)-type IMUs in order to evaluate their accuracy and stability over time. The study covers three IMU sensors of different grades (ascending order): Rokubun Argonaut navigator sensor (InvenSense TDK MPU9250), Samsung Galaxy Note10 phone sensor (STMicroelectronics LSM6DSR), and NovAtel PwrPak7 sensor (Epson EG320N). The noise components of the sensors are computed using overlapped Allan deviation analysis on data collected over the course of a week in a static position. The focus of the analysis is to characterize the random walk noise and bias stability, which are the most critical for combined GNSS/IMU navigation and may differ or may not be listed in manufacturers' specifications. Noise characteristics are calculated for the studied sensors and examples of their use in loosely coupled GNSS/IMU processing are assessed. This work proposes a structured and reproducible approach for working with sensors for their use in navigation tasks in combination with GNSS, and can be used for sensors of different levels to supplement missing or incorrect sensor manufacturers' data.

摘要

惯性测量单元（IMU）是包括导航、机器人技术、航空航天和汽车系统在内的各种应用的关键组件。IMU传感器特性对这些应用的准确性和可靠性有重大影响。特别是，噪声特性和偏置稳定性对于执行组合GNSS/IMU解决方案的适当滤波器设置至关重要。本文基于不同IMU传感器的阿伦方差进行分析，这些传感器对应于不同等级的微机电系统（MEMS）型IMU，以评估其随时间的准确性和稳定性。该研究涵盖了三个不同等级（升序）的IMU传感器：Rokubun Argonaut导航传感器（InvenSense TDK MPU9250）、三星Galaxy Note10手机传感器（意法半导体LSM6DSR）和NovAtel PwrPak7传感器（爱普生EG320N）。通过对在静态位置收集的一周数据进行重叠阿伦方差分析来计算传感器的噪声分量。分析的重点是表征随机游走噪声和偏置稳定性，这对于组合GNSS/IMU导航最为关键，并且可能不同或可能未在制造商的规格中列出。计算了所研究传感器的噪声特性，并评估了它们在松耦合GNSS/IMU处理中的使用示例。这项工作提出了一种结构化且可重复的方法，用于处理与GNSS结合用于导航任务的传感器，并且可用于不同级别的传感器，以补充缺失或不正确的传感器制造商数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2837/10975684/b9e1b34f2436/sensors-24-01953-g014.jpg
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