Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32718
Error Correction Method for 2D Ultra-Wideband Indoor Wireless Positioning System Using Logarithmic Error Model

Authors: Phornpat Chewasoonthorn, Surat Kwanmuang


Indoor positioning technologies have been evolved rapidly. They augment the Global Positioning System (GPS) which requires line-of-sight to the sky to track the location of people or objects. In this study, we developed an error correction method for an indoor real-time location system (RTLS) based on an ultra-wideband (UWB) sensor from Decawave. Multiple stationary nodes (anchor) were installed throughout the workspace. The distance between stationary and moving nodes (tag) can be measured using a two-way-ranging (TWR) scheme. The result has shown that the uncorrected ranging error from the sensor system can be as large as 1 m. To reduce ranging error and thus increase positioning accuracy, we present an online correction algorithm using the Kalman filter. The results from experiments have shown that the system can reduce ranging error down to 5 cm.

Keywords: Indoor positioning, ultra-wideband, error correction, Kalman filter.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 447


[1] Klepeis, N.E., et al., The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants. 2001. 11(3): p. 231-252.
[2] Indooratlas. A 2016 Global Research Report on the Indoor Positioning Market, 2016.
[3] Mautz, R., Indoor positioning technologies. 2012.
[4] Allen, B., et al. Ultra wideband: Applications, technology and future perspectives. 2005. international workshop on convergent technologies (IWCT).
[5] Decawave APS013 Application Note, The implementation of two way ranging with the DW1000, 2018.
[6] Hindermann, P., et al., High precision real-time location estimates in a real-life barn environment using a commercial ultra wideband chip. 2020. 170: p. 105250.
[7] Poulose, A., J. Kim, and D.S.J.A.S. Han, A sensor fusion framework for indoor localization using smartphone sensors and Wi-Fi RSSI measurements. 2019. 9(20): p. 4379.
[8] Haggenmiller, A., M. Krogius, and E. Olson. Non-parametric error modeling for ultra-wideband localization networks. in 2019 International Conference on Robotics and Automation (ICRA). 2019. IEEE.