scispace - formally typeset
Open Access

An introduction to inertial navigation

TLDR
This work introduces inertial navigation, focusing on strapdown systems based on MEMS devices, and concludes that whilst MEMS IMU technology is rapidly improving, it is not yet possible to build a MEMS based INS which gives sub-meter position accuracy for more than one minute of operation.
Abstract
Until recently the weight and size of inertial sensors has prohibited their use in domains such as human motion capture. Recent improvements in the performance of small and lightweight micromachined electromechanical systems (MEMS) inertial sensors have made the application of inertial techniques to such problems possible. This has resulted in an increased interest in the topic of inertial navigation, however current introductions to the subject fail to sufficiently describe the error characteristics of inertial systems. We introduce inertial navigation, focusing on strapdown systems based on MEMS devices. A combination of measurement and simulation is used to explore the error characteristics of such systems. For a simple inertial navigation system (INS) based on the Xsens Mtx inertial measurement unit (IMU), we show that the average error in position grows to over 150 m after 60 seconds of operation. The propagation of orientation errors caused by noise perturbing gyroscope signals is identified as the critical cause of such drift. By simulation we examine the significance of individual noise processes perturbing the gyroscope signals, identifying white noise as the process which contributes most to the overall drift of the system. Sensor fusion and domain specific constraints can be used to reduce drift in INSs. For an example INS we show that sensor fusion using magnetometers can reduce the average error in position obtained by the system after 60 seconds from over 150 m to around 5 m. We conclude that whilst MEMS IMU technology is rapidly improving, it is not yet possible to build a MEMS based INS which gives sub-meter position accuracy for more than one minute of operation.

read more

Content maybe subject to copyright    Report

Citations
More filters
Posted Content

AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles

TL;DR: A new simulator built on Unreal Engine that offers physically and visually realistic simulations for autonomous vehicles in real world and that is designed from the ground up to be extensible to accommodate new types of vehicles, hardware platforms and software protocols.
Book ChapterDOI

AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles

TL;DR: In this paper, the authors present a new simulator built on Unreal Engine that offers physically and visually realistic simulations for autonomous vehicles in real-world environments, including a physics engine that can operate at a high frequency for real-time hardware-in-the-loop (HITL) simulations with support for popular protocols (e.g., MavLink).
Journal ArticleDOI

A Survey of Indoor Inertial Positioning Systems for Pedestrians

TL;DR: It is concluded that PDR techniques alone can offer good short- to medium- term tracking under certain circumstances, but that regular absolute position fixes from partner systems will be needed to ensure long-term operation and to cope with unexpected behaviours.
Journal ArticleDOI

Activity identification using body-mounted sensors — a review of classification techniques

TL;DR: This article reviews the different techniques which have been used to classify normal activities and/or identify falls from body-worn sensor data and illustrates the variety of approaches which have previously been applied.
Proceedings ArticleDOI

Pedestrian localisation for indoor environments

TL;DR: This paper looks at how a foot-mounted inertial unit, a detailed building model, and a particle filter can be combined to provide absolute positioning, despite the presence of drift in the inertial units and without knowledge of the user's initial location.
References
More filters
Book

Strapdown inertial navigation technology

TL;DR: In this paper, the physical principles of inertial navigation, the associated growth of errors and their compensation, and their application in a broad range of applications are discussed, drawing current technological developments and providing an indication of potential future trends.
Journal ArticleDOI

Pedestrian tracking with shoe-mounted inertial sensors

TL;DR: The NavShoe device provides not only robust approximate position, but also an extremely accurate orientation tracker on the foot, which can greatly reduce the database search space for computer vision, making it much simpler and more robust.
Dissertation

Inertial and magnetic sensing of human motion

TL;DR: This thesis deals with ambulatory position and orientation measurements of human body segments using inertial and magnetic sensing and actuation on the body, motion analysis can be performed anywhere, without the need for an expensive lab.