000151437 001__ 151437
000151437 005__ 20190316234848.0
000151437 037__ $$aCONF
000151437 245__ $$aAcoustic node calibration using helicopter sounds and Monte Carlo markov chain methods
000151437 269__ $$a2004
000151437 260__ $$c2004
000151437 336__ $$aConference Papers
000151437 520__ $$aA Monte-Carlo method is used to calibrate a randomly placed sensor node using helicopter sounds. The calibration is based on using the GPS information from the helicopter and the estimated DOA's 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.
000151437 6531_ $$aTracking
000151437 6531_ $$aTargets
000151437 6531_ $$aArrays
000151437 700__ $$aMcClellan, J. H.
000151437 700__ $$g199128$$aCevher, Volkan$$0243957
000151437 7112_ $$dAugust, 2004$$cTaos Ski Valley, NM$$aIEEE DSP Workshop
000151437 8564_ $$uhttps://infoscience.epfl.ch/record/151437/files/ACOUSTIC%20NODE%20CALIBRATION%20USING%20HELICOPTER%20SOUNDS%20AND%20MONTE%20CARLO.pdf$$zn/a$$s295687$$yn/a
000151437 909C0 $$xU12179$$0252306$$pLIONS
000151437 909CO $$qGLOBAL_SET$$pconf$$ooai:infoscience.tind.io:151437$$pSTI
000151437 917Z8 $$x199128
000151437 917Z8 $$x199128
000151437 937__ $$aEPFL-CONF-151437
000151437 973__ $$rNON-REVIEWED$$sPUBLISHED$$aOTHER
000151437 980__ $$aCONF