A Waist-Attached PNS Algorithm Based on MIMU

Qi Fan Zhou; Hai Zhang; You Ze Mao; Yan Hong Chang

doi:10.4028/www.scientific.net/AMR.562-564.1272

Paper Titles

A New EV Energy Control System under V2G Mode
p.1252

A High Speed Stacker Regulating Algorithm Based on Wireless Sensor Network
p.1256

The Design of Millimeter-Level Ultrasonic Distance Measurement Circuit
p.1260

A Computation Method for Symmetry
p.1266

A Waist-Attached PNS Algorithm Based on MIMU
p.1272

Research on the Parameter Estimating Algorithms of Image Edge Detection
p.1279

The Optimal Switched Law Methods Analysis and Research on Switched Linear Systems
p.1286

The Study of Wireless Sensor Networks Based On-Line Monitoring System for Fire
p.1292

An Energy-Efficient QoS Routing Algorithm for Wireless Sensor Networks
p.1297

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 562-564A Waist-Attached PNS Algorithm Based on MIMU

A Waist-Attached PNS Algorithm Based on MIMU

Abstract:

Pedestrian Navigation System (PNS) is a system aims at determining the current location of person, recording the walking trajectory. This paper presents an algorithm of PNS based on lowperformance MEMS-IMU attaching to the waist of people. The algorithm consists of step detection, model identification, stride, heading determination and position estimation. A method to identify a user’s status, calibrate the length coefficient K by Least-Squares and update K online according to different models and acceleration is presented, which adaptively adjusts the calculation of stride length in case of different walking speeds and manners. The integration of INS and magnetic azimuth for heading direction is put forward and the walking trajectory is calculated by Dead Reckoning (DR). Several tests have been conducted and the algorithm performed well.

You might also be interested in these eBooks

Materials Engineering and Automatic Control

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 562-564)

Pages:

1272-1278

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.562-564.1272

Citation:

Cite this paper

Online since:

August 2012

Authors:

Qi Fan Zhou, Hai Zhang, You Ze Mao, Yan Hong Chang

Keywords:

DR, Length Coefficient, MEMS-IMU, PNS, Step Detection

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Stirling, R. and J. Collin, An Innovative shoe-mounted pedestrian navigation system, GNSS. (2003).

Google Scholar

[2] Beauregard, S., A Helmet-Mounted Pedestrian Dead Reckoning System, IFAWC. 2006: TZI University Bremen, Germany.

Google Scholar

[3] Godha, S., G. Lachapelle and M.E. Cannon, Integrated GPS/INS System for Pedestrian Navigation in a Signal Degraded Environment, ION GNSS. (2006).

Google Scholar

[4] V, X.T.B., MTi and MTx User Manual and Technical Documentation. (2006).

Google Scholar

[5] Xu Rui, Research and Application on Navigation Algorithm of Pedestrian Navigation System., 2008, Nanjing University of Aeronautics and Astronautics: Nanjing.

Google Scholar

[6] Weinberg, H., Using the ADXL202 in Pedometer and Personal Navigation Applications., (2002).

Google Scholar

[7] Jang, J.W.K.H., A Step, Stride and Heading Determination for the Pedestrian Navigation System. Journal of Global Positioning Systems, 2004. 3(1-2): pp.273-279.

DOI: 10.5081/jgps.3.1.273

Google Scholar