A robust position estimation algorithm for a local positioning measurement system

Author

Pfeil, R. ; Schuster, S. ; Scherz, P. ; Stelzer, A. ; Stelzhammer, G.

Author_Institution

Linz Center of Mechatron. (LCM), Linz, Austria

fYear

2009

fDate

24-25 Sept. 2009

Firstpage

1

Lastpage

4

Abstract

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.

Keywords

least mean squares methods; nonlinear equations; position measurement; time-of-arrival estimation; Bancroft algorithm; TDOA; closed-form solution; least median-of-square algorithm; local positioning measurement system; nonlinear range measurement equation; robust position estimation algorithm; time-difference-of-arrival-based LPM; Chirp; Conferences; Least squares approximation; Microwave Theory and Techniques Society; Position measurement; Radar tracking; Radiofrequency identification; Robustness; Transponders; Wireless sensor networks; Bancroft; LMS; local positioning; robust estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

Cavtat

Print_ISBN

978-1-4244-5060-2

Electronic_ISBN

978-1-4244-5062-6

Type

conf

DOI

10.1109/IMWS2.2009.5307893

Filename

5307893