We are currently experiencing intermittent issues impacting performance. We apologize for the inconvenience.
By Topic

A robust position estimation algorithm for a local positioning measurement system

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Pfeil, R. ; Linz Center of Mechatron. (LCM), Linz, Austria ; Schuster, S. ; Scherz, P. ; Stelzer, A.
more authors

Precise position estimation has always been a challenging but highly requested task in many technical problems. The time-difference of arrival (TDOA) based local position measurement system LPM uses the well-known Bancroft algorithm, which computes a closed-form solution to the non-linear range measurement equations. A critical issue of this computation method is that outliers in the measurements will decrease the quality of the position estimate significantly. In this contribution a least median of squares (LMS) algorithm for position estimation is developed which delivers an appropriate position estimate even if the raw data contain corrupted measurements.

Published in:

Wireless Sensing, Local Positioning, and RFID, 2009. IMWS 2009. IEEE MTT-S International Microwave Workshop on

Date of Conference:

24-25 Sept. 2009