Title :
Acoustic node calibration using helicopter sounds and Monte-Carlo Markov chain methods
Author :
Cevher, Volkan ; McClellan, James H.
Author_Institution :
Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
A Monte-Carlo method is used to calibrate a randomly placed sensor node using helicopter sounds. The calibration is based on using GPS information from the helicopter and the estimated DOAs at the node. The related Cramer-Rao lower bound is derived and the effects of the GPS errors on the position estimates are derived. Issues related to the processing of the field data, e.g., time synchronization and data nonstationarity, are discussed. The effects of the GPS errors are shown to be negligible under certain conditions. Finally, the results of the calibration on field data are given.
Keywords :
Global Positioning System; Markov processes; Monte Carlo methods; acoustic arrays; acoustic signal processing; array signal processing; calibration; direction-of-arrival estimation; synchronisation; target tracking; Cramer-Rao lower bound; DOA estimation; GPS information; Monte-Carlo Markov chain methods; Monte-Carlo method; acoustic arrays; acoustic node calibration; data nonstationarity; helicopter sounds; position estimation; sensor node; target tracking; time synchronization; Acoustic arrays; Acoustic measurements; Calibration; Delay estimation; Direction of arrival estimation; Estimation error; Global Positioning System; Helicopters; Sampling methods; Yttrium;
Conference_Titel :
Digital Signal Processing Workshop, 2004 and the 3rd IEEE Signal Processing Education Workshop. 2004 IEEE 11th
Print_ISBN :
0-7803-8434-2
DOI :
10.1109/DSPWS.2004.1437973
