Title :
R-means localization: A simple iterative algorithm for range-difference-based source localization
Author :
Ono, Nobutaka ; Sagayama, Shigeki
Author_Institution :
Grad. Sch. of Inf. Sci. & Technol., Univ. of Tokyo, Tokyo, Japan
Abstract :
In this paper, we present a simple iterative algorithm for range-difference (RD) based localization. The RD-based localization is a kind of nonlinear optimization problem and generally it has no closed-form solution. Through auxiliary function approach, we derive iterative update rules without any tuning parameters, which just consists of 1) averaging source-sensor distances, 2) averaging the source positions estimated by updating source-sensor distance on each sensor with the source-direction fixed. Due to the resemblance of the iterative averaging to k-means clustering, we call it r-means localization. The convergence of the algorithm is guaranteed. The acceleration of the convergence is also investigated.
Keywords :
distance measurement; distributed sensors; iterative methods; microphone arrays; optimisation; pattern clustering; position measurement; sensor placement; R-means localization; auxiliary function; averaging source-sensor distance; distributed sensor network; iterative algorithm; k-means clustering; microphone array; nonlinear optimization problem; range-difference-based source localization; source position estimation; Acceleration; Closed-form solution; Clustering algorithms; Convergence; Information science; Iterative algorithms; Iterative methods; Microphone arrays; Signal processing algorithms; Surveillance; acceleration; auxiliary function; k-means clustering; range difference; source localization;
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2010.5496228
