MODEL-BASED SIGNAL PROCESSING: An Innovations Approach

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24 Νοε 2013 (πριν από 3 χρόνια και 6 μήνες)

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MODEL
-
BASED SIGNAL PROCESSING:

A
n Innovations Approach


UNIVERSITY OF CAMBRIDGE

Signal Processing
Reader’s
Lecture

2/2006


James V. Candy


Professor, Electrical & Computer Engineering Department, University of California (UC ) Santa Barbara

Chief Scientis
t for Engineering
, UC
Lawrence Livermore National Laboratory




After a brief background discussion of model
-
based signal processing, we introduce the
idea of t
he innovations approach
. It is shown that this method of deriving the processor

provides a

large


amount of insight into the development and eventual design of practical
model
-
based
schemes
. By first starting with the batch minimum variance solution to the
state estimation problem, we show that by reformulating the problem in terms of an
orthogonal
transformation leads naturally to the innovations sequence. With the batch
solution in hand, we then show how it evolves to a recursive formulation and to the linear
MBP or equivalently the Kalman filter

in the linear gaussian case.
. We provide a brief
ove
rview of the
entire
filter derivation. Next we investigate properties of the innovations
sequence and show how they provide
insight

to the optimal design of the MBP. Practical
statistical tests are then presented and demonst
r
ated on a simple example to ill
ustrate the
idea of
the minimum variance
design and

analysis using the innovations
approach.


Biography of

James V. Candy


James V. Candy

is the Chief Scientist for Engineering and was Director of the Center for
Advanced Signal & Image Sciences at the Un
iversity of California, Lawrence Livermore
National Laboratory. Dr. Candy received a commission in the USAF in 1967 and was a
Systems Engineer/Test Director from 1967 to 1971. He has been a Researcher at the
Lawrence Livermore National Laboratory since 1
976 holding various positions including
that of Project Engineer for Signal Processing and Thrust Area Leader for Signal and
Control Engineering. Educationally, he received his B.S.E.E. degree from the University
of Cincinnati and his M.S.E. and Ph.D. degr
ees in Electrical Engineering from the
University of Florida, Gainesville. He is a registered Control System Engineer in the state
of California. He has been an Adjunct Professor at San Francisco State University,
University of Santa Clara, and UC Berkele
y, Extension teaching graduate courses in
signal and image processing. He is an Adjunct Full
-
Professor at the University of
California, Santa Barbara. Dr. Candy is a Fellow of the IEEE and a Fellow of the
Acoustical Society of America (ASA) as well as a
member of Eta Kappa Nu and Phi
Kappa Phi honorary societies. He was elected as a Distinguished Alumnus by the
University of Cincinnati. Dr. Candy received the IEEE Distinguished Technical
Achievement Award for the “development of model
-
based signal process
ing in ocean
acoustics.” He has published over 200 journal articles, book chapters, and technical
reports as well as written two texts in signal processing, "Signal Processing: the Model
-
Based Approach," (McGraw
-
Hill,1986) and "Signal Processing: the Moder
n Approach,"
(McGraw
-
Hill,1988).
He has completed a new text entitled, “Model
-
Based Signal
Processing,” (Wiley/IEEE Press,

2006
).
He has presented short courses sponsored by the
IEEE and ASA in Applied Signal Processing, Spectral Estimation, Advanced Digi
tal
Signal Processing and Model
-
Based Ocean Acoustic Signal Processing for IEEE Oceanic
Engineering Society. He has also presented short courses in Applied Model
-
Based Signal
Processing for the SPIE Optical Society. He is currently the IEEE Chair of the T
echnical
Committee on "Sonar Signal and Image Processing" and was the Chair of the ASA
Technical Committee on "Signal Processing in Acoustics" as well as being an Associate
Editor for Signal Processing of ASA (on
-
line). His research interests include
Ba
yesian
estimation, identification, spatial estimation, signal and image processing, array signal
processing, tomography and biomedical applications.