Robust geolocation estimation using adaptive RANSAC algorithm

Author

Luo, Chenchi ; McClellan, James H.

Author_Institution

Center for Signal & Image Process., Georgia Inst. of Technol., Atlanta, GA, USA

fYear

2010

fDate

14-19 March 2010

Firstpage

3862

Lastpage

3865

Abstract

This paper deals with location estimation in the presence of unreliable measurements (outliers) in large scale geolocation systems. In order to find a way of identifying these outliers, we propose an adaptive RANSAC (Random Sample Consensus) algorithm that maintains a consensus set which iteratively includes inliers and rejects outliers. Numerical experiments are performed to apply the proposed algorithm to linearized TDOA (time difference of arrival) and AOA (angle of arrival) geolocation systems to quantify the location performance versus the least-squares estimate.

Keywords

direction-of-arrival estimation; least squares approximations; radio direction-finding; time-of-arrival estimation; adaptive RANSAC algorithm; angle of arrival estimation; geolocation estimation; least-squares estimate; location performance; random sample consensus; time difference of arrival estimation; Base stations; Image processing; Interference; Iterative algorithms; Large-scale systems; Navigation; Nonlinear equations; Robustness; Signal processing; Time difference of arrival; AOA; RANSAC; TDOA;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on

Conference_Location

Dallas, TX

ISSN

1520-6149

Print_ISBN

978-1-4244-4295-9

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2010.5495817

Filename

5495817