Next Article in Journal
Direct Quantification of Cd2+ in the Presence of Cu2+ by a Combination of Anodic Stripping Voltammetry Using a Bi-Film-Modified Glassy Carbon Electrode and an Artificial Neural Network
Next Article in Special Issue
Optimizing the MAC Protocol in Localization Systems Based on IEEE 802.15.4 Networks
Previous Article in Journal
A Linear Birefringence Measurement Method for an Optical Fiber Current Sensor
Previous Article in Special Issue
A Sequential Optimization Calibration Algorithm for Near-Field Source Localization
Article Menu
Issue 7 (July) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(7), 1555;

Landmark-Based Drift Compensation Algorithm for Inertial Pedestrian Navigation

German Aerospace Center (DLR), Institute of Communications and Navigation, Oberpfaffenhofen, 82234 Wessling, Germany
Author to whom correspondence should be addressed.
Received: 20 April 2017 / Revised: 23 June 2017 / Accepted: 1 July 2017 / Published: 3 July 2017
Full-Text   |   PDF [13698 KB, uploaded 5 July 2017]   |  


The navigation of pedestrians based on inertial sensors, i.e., accelerometers and gyroscopes, has experienced a great growth over the last years. However, the noise of medium- and low-cost sensors causes a high error in the orientation estimation, particularly in the yaw angle. This error, called drift, is due to the bias of the z-axis gyroscope and other slow changing errors, such as temperature variations. We propose a seamless landmark-based drift compensation algorithm that only uses inertial measurements. The proposed algorithm adds a great value to the state of the art, because the vast majority of the drift elimination algorithms apply corrections to the estimated position, but not to the yaw angle estimation. Instead, the presented algorithm computes the drift value and uses it to prevent yaw errors and therefore position errors. In order to achieve this goal, a detector of landmarks, i.e., corners and stairs, and an association algorithm have been developed. The results of the experiments show that it is possible to reliably detect corners and stairs using only inertial measurements eliminating the need that the user takes any action, e.g., pressing a button. Associations between re-visited landmarks are successfully made taking into account the uncertainty of the position. After that, the drift is computed out of all associations and used during a post-processing stage to obtain a low-drifted yaw angle estimation, that leads to successfully drift compensated trajectories. The proposed algorithm has been tested with quasi-error-free turn rate measurements introducing known biases and with medium-cost gyroscopes in 3D indoor and outdoor scenarios. View Full-Text
Keywords: Landmark; inertial; pedestrian; navigation; pocket; drift; yaw; corners; stairs Landmark; inertial; pedestrian; navigation; pocket; drift; yaw; corners; stairs

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Munoz Diaz, E.; Caamano, M.; Sánchez, F.J.F. Landmark-Based Drift Compensation Algorithm for Inertial Pedestrian Navigation. Sensors 2017, 17, 1555.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top