Abstract

An inertial measurement unit (IMU) typically has three accelerometers and three gyroscopes. The output of those inertial sensors is used by an inertial navigation system to calculate the navigation solution–position, velocity and attitude. Since the sensor measurements contain noise, the navigation solution drifts over time. When considering low cost sensors, multiple IMUs can be used to improve the performance of a single unit. In this paper, we describe our designed 32 multi-IMU (MIMU) architecture and present experimental results using this system. To analyze the sensory data, a dedicated software tool, capable of addressing MIMUs inputs, was developed. Using the MIMU hardware and software tool we examined and evaluated the MIMUs for: (1) navigation solution accuracy (2) sensor outlier rejection (3) stationary calibration performance (4) coarse alignment accuracy and (5) the effect of different MIMUs locations in the architecture. Our experimental results show that 32 IMUs obtained better performance than a single IMU for all testcases examined. In addition, we show that performance was improved gradually as the number of IMUs was increased in the architecture.

Highlights

  • Inertial Navigation System (INS) is a system that uses Inertial Measurements Unit (IMU) sensors to calculate the orientation, velocity and position of a platform using the combination of accelerometers and gyroscopes of the IMU

  • The experiment made were focused on examining the effect of MIMU system on the calibration performance

  • A 32 based MIMU architecture was designed and used for field experiments. Those were focused on the benefit of using MIMU for calibration of inertial sensors

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Summary

Introduction

Inertial Navigation System (INS) is a system that uses Inertial Measurements Unit (IMU) sensors to calculate the orientation, velocity and position of a platform using the combination of accelerometers and gyroscopes of the IMU. Since the IMUs measurements are not accurate and have significant errors that causes the navigation solution to drift over time [2]. As in the MIMU architecture, a gyro-free (GF) INS has multiple accelerometers, but no gyroscopes [5]. Using the MIMU software and hardware we focus on sensor calibration differences between a single IMU and a 32 based MIMU. Results show that the latter is preferred in terms of accuracy and time to converge.

Problem Formulation-Theoretical Background
Experiments and Results
IMU without Calibration
Discussion and Conclusions

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