Title :
Application of Ensemble Detection and Analysis to modeling uncertainty in non stationary processes
Author_Institution :
NASA Goddard Space Flight Center, USA
Abstract :
Characterization of non stationary and nonlinear processes is a challenge in many engineering and scientific disciplines. Climate change modeling and projection, retrieving information from Doppler measurements of hydrometeors, and modeling calibration architectures and algorithms in microwave radiometers are example applications that can benefit from improvements in the modeling and analysis of non stationary processes. Analyses of measured signals have traditionally been limited to a single measurement series. Ensemble Detection is a technique whereby mixing calibrated noise produces an ensemble measurement set. The collection of ensemble data sets enables new methods for analyzing random signals and offers powerful new approaches to studying and analyzing non stationary processes. Derived information contained in the dynamic stochastic moments of a process will enable many novel applications.
Keywords :
radiometers; signal detection; stochastic processes; Doppler measurement; calibration architecture; climate change modeling; dynamic stochastic moment; ensemble detection; hydrometeor; microwave radiometer; nonlinear process; nonstationary process; Calibration; Fluctuations; Noise; Radiometers; Receivers; Stochastic processes; Uncertainty; Radiometer calibration; empirical mode decomposition; ensemble detection and analysis; measurement uncertainty; non stationary processes; observation theory;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4244-9565-8
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2010.5650690