Aaron Lanterman’s Publications
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Journal & conference papers, theses,
technical reports, etc.
Some of these entries
have links
to the actual document
and/or the publishing organization’s home page. Enjoy! If you find
anything here useful, drop me a line:
lanterma@ece.gatech.edu
Phase retrieval and nonnegative inverse problems
K. Choi, A.D. Lanterman, and R. Raich, On Convergence of the Schulz-Snyder
Phase Retrieval Algorithm to Local Minima,
submitted to the Journal
of the Optical Society of America A, Jan. 2005. (Revision of Stagnation
Problems in the Snyder-Schulz Phase Retrival Algorithm, originally submitted
May 2004).
(PDF)
K. Choi and A.D. Lanterman, An Iterative Deautoconvolution Algorithm for
Nonnegative Functions,
Inverse Problems, accepted for publication
Feb. 2005, in press.
(PDF, updated 3/6/05)
K. Choi, A.D. Lanterman, and M. Fozunbal, Channel Input Distribution
Estimation Using a Minimum I-divergence Algorithm,
submitted to IEEE Trans. on Communications,
Jan. 2005. (PDF)
Target tracking
M. Tobias and A.D. Lanterman, Probability Hypothesis Density-Based
Multitarget Tracking with Bistatic Range and Doppler Observations,
IEE Proc. – Radar, Sonar, and Navigation,
accepted for publication Feb. 2005, in press.
(PDF, updated 3/15/05)
W.F. Leven and A.D. Lanterman,
Unscented Kalman Filters for Multiple Target Tracking with Symmetric
Measurement Equations,
submitted to IEEE Trans. on Automatic Control, Jan. 2005.
(PDF)
M. Tobias and A.D. Lanterman,
Multitarget Tracking using Multiple Bistatic Range
Measurements with Probability Hypothesis Densities,
Signal Processing, Sensor Fusion, and Target Recognition XIII,
Proc. SPIE 5429, Ed: I. Kadar, April 12-16, 2004.
(PDF)
W.F. Leven and A.D. Lanterman, Multiple Target Tracking
with Symmetric Measurement Equations using Unscented Kalman
and Particle Filters, 36th IEEE Southeastern Symposium
on System Theory, Atlanta, GA, March 14-16, 2004.
(PDF)
M. Tobias and A.D. Lanterman, A Probability
Hypothesis Density-Based Multitarget Tracker
using Multiple Bistatic Range and Velocity
Measurements, 36th IEEE Southeastern Symposium
on System Theory, Atlanta, GA, March 14-16, 2004.
(PDF)
A.D. Lanterman, Tracking and recognition of airborne targets via
commercial television and FM radio signals, in Acquisition, Tracking, and
Pointing XIII, Proc. SPIE 3692, Eds: Michael K. Masten and Larry A. Stockum,
Orlando, FL, April 1999, pp. 189-198.
(gzipped postscript)
Target recognition with radar data
Journal papers
L.M. Ehrman and A.D. Lanterman,
Automatic Target Recognition via Passive Radar,
Using Precomputed Radar Cross Sections and a Coordinated Flight Model,
submitted to IEEE Trans. on
Aerospace and Electronic Systems, Nov. 2003.
(PDF)
L.M. Ehrman and A.D. Lanterman, Estimation of Aircraft
Orientation from Flight Paths Using a
Coordinated Flight Model,
submitted to IEEE Trans. on Aerospace and Electronic Systems,
Nov. 2002.
(PDF)
Student theses
L.M. Ehrman, Automatic Target Recognition Using Passive Radar Data
and a Coordinated Flight Model, M.S. Thesis, Georgia Institute of
Technology, Fall 2003.
(PDF)
Conference papers
L.M. Ehrman and A.D. Lanterman, Robust Algorithm for
Automated Target Recognition using
Precomputed Radar Cross Sections,
Automatic Target Recognition XIV,
Proc. SPIE 5426, Ed: F.A. Sadjadi, April 12-16, 2004.
(PDF)
L.M. Ehrman and A.D. Lanterman, A Robust
Algorithm for Automatic Target Recognition
using Passive Radar,
36th IEEE Southeastern Symposium on System Theory,
Atlanta, GA, March 14-16, 2004.
(PDF)
L.M. Ehrman and A.D. Lanterman, Target Identification
Using Precomputed Radar Cross Sections and a
Coordinated Flight Model,
Third Multinational Conference on Passive and Covert Radar,
Ed: P. Kurzenhauser and B. Spickler,
Univ. of Washington Applied Physics Laboratory, Oct. 21-23, 2003.
(PDF)
L.M. Ehrman and A.D. Lanterman,
Automated Target Recognition using Passive Radar and
Coordinated Flight Models,
Automatic Target Recognition XIII,
Proc. SPIE 5094, Ed: F.A. Sadjadi, April 2003.
(PDF)
Minimum description length and stochastic complexity
A.D. Lanterman, Schwarz, Wallace, and Rissanen: Intertwining
Themes in Theories of Model Order Estimation,
International Statistical Review, Vol. 69, No. 2, August 2001,
pp. 185-212.
(PDF)
Radar imaging
A.D. Lanterman and D.C. Munson, Jr.,
Deconvolution Techniques for Passive Radar Systems,
in Algorithms for Synthetic Aperture Radar Imagery IX,
Proc. SPIE 4727, Ed: E.G. Zelnio,
Orlando, FL, April 2002, pp. 166-177. Added 5/17/02.
(pdf)
Y. Wu, A. Lanterman, and D. C. Munson, Jr., Multistatic passive
radar imaging of aircraft: A feasibility study using FISC, Proc. URSI
National Radio Science Meeting, Boulder, CO, January 9 – 11, 2002.
A.D. Lanterman, Efficient implementation of an expectation-maximization
algorithm for imaging diffuse radar targets,
Algorithms for Synthetic Aperture Radar Imagery VIII,
Proc. SPIE, Vol. 4382, Ed. E.G. Zelnio, Orlando, FL, April 2001,
pp. 49-59.
(PDF)
A.D. Lanterman, Maximum-Likelihood Estimation for Hybrid Specular/Diffuse
Models of Radar Imaging and Target Recognition, submitted to IEEE
Trans. on Aerospace and Electronic Systems, May 2000.
(gzipped postscript)
A.D. Lanterman, Statistical Radar Imaging of Diffuse and Specular Targets
Using an Expectation-Maximization Algorithm,
in Algorithms for Synthetic Aperture Radar Imagery VII,
Proc. SPIE 4053, Ed: E.G. Zelnio,
Orlando, FL, April 2000, pp. 20-31.
(PDF)
M.D. DeVore, A.D. Lanterman, J.A. O’Sullivan,
ATR Performance of a Rician Model for SAR Images,
in Automatic Target Recognition X,
Proc. SPIE 4050, Ed: E.G. Zelnio,
Orlando, FL, April 2000, pp. 34-45.
(postscript)
A.D. Lanterman, Radar Imaging with Variations of an
Expectation-Maximization Algorithm, Proc. 1999 IEEE
Workshop on Detection,
Estimation, Classification, and Imaging, Santa Fe, NM, 24-26 February 1999,
p. 51.
(formal
one-page paper for conference proceedings, gzipped postscript,
informal four-page extended version,
gzipped postscript)
Inverse scattering
M. Brandfass, A.D. Lanterman, and K.F. Warnick,
A Comparison of the Colton-Kirsch Inverse Scattering Methods with
Linearized Tomographic Inverse Scattering, Inverse Problems, Vol. 17,
No. 6, Dec. 2001, pp. 1797-1816.
(PDF)
Texture analysis
A.D. Lanterman, U. Grenander, and M.I. Miller,
Bayesian Segmentation via Asymptotic Partition Functions,
IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 22, No. 4,
April 2000, pp. 337-347.
(gzipped postscript)
Radio astronomy
A.D. Lanterman, Statistical Imaging in Radio Astronomy via an
Expectation-Maximization Algorithm for Structured Covariance Estimation,
in Statistical Methods in Imaging: In Medicine, Optics, and
Communication, a festschrift in honor of
Donald L. Snyder’s
65th birthday, Ed.
J.A. O’Sullivan,
Springer-Verlag, to appear.
(PDF)
A.D. Lanterman,
Application of an Expectation-Maximization Algorithm for
Structured Covariance Estimation to Radio Astronomy, URSI
National Radio Science Meeting,
Univ. of Colorado, Boulder, CO, 4-8 January 2000, p. 197.
Automatic target recognition for infrared and laser radar data
Doctoral dissertation
A.D. Lanterman, Modeling Clutter and Target Signatures for
Pattern-Theoretic Understanding of Infrared Scenes,
Doctoral dissertation, Washington
University, August 1998.
This is a rather large document, so we have made it available
in four parts:
Compressed with gzip:
Part 1 (483K) |
Part 2 (743K) |
Part 3 (146K) |
Part 4 (667K)
Book chapters
A. Srivastava, A.D. Lanterman, U. Grenander, M. Loizeaux, and M.I. Miller,
Monte-Carlo Techniques for Automated Target Recognition,
in Sequential Monte Carlo Methods in Practice,
Eds.
Nando de Freitas,
Arnaud
Doucet,
and
Neil Gordon,
Springer-Verlag, New York,
Chapter 26, 2001, pp. 533-552.
(Alas, part of the agreement with Springer prevents us from
posting preprints of this on our web pages, but you can go to the
editors’
web site for the book)
Journal papers
A.D. Lanterman, Jump-Diffusion Algorithm for Multiple Target
Recognition using Laser Radar Range Data,
Optical Engineering, Vol. 40, No. 8, Aug. 2001, pp. 1724-1728.
(pdf)
A.D. Lanterman, Bayesian Inference of Thermodynamic State Incorporating
Schwarz-Rissanen Complexity for Infrared Target
Recognition,
Optical Engineering, Vol. 39, No. 5, May 2000, pp. 1282-1292.
(gzipped postscript)
A.D. Lanterman, J.A. O’Sullivan, M.I. Miller, Kullback-Leibler
Distances for Quantifying Clutter and Models, Optical Engineering,
Vol. 38, No. 2, Dec. 1999, pp. 2134-2146.
(gzipped postscript 787K)
A.D. Lanterman, M.I. Miller, D.L. Snyder,
General Metropolis-Hastings jump-diffusions for automatic target
recognition in infrared scenes, Optical Engineering,
Vol. 36, No. 4, April 1997, pp. 1123-1137. (This paper was derived
from my Master’s thesis. I don’t have it available on line, since some
substantial fixes were made in the galley proofs; please find the version
that appeared in Optical Engineering.)
Conference papers
S.C. Zhu, A.L. Yuille, A.D. Lanterman, ATR applications of minimax
entropy models of texture and shape,
Automatic Target Recognition XI,
Proc. SPIE, Vol. 4379, Ed. Firooz A. Sadjadi, April 2001, pp. 574-583.
(PDF)
A.D. Lanterman, M.L. Cooper, M.I. Miller, Efficient
estimation of thermodynamic state incorporating Bayesian model order
selection,
Automatic Target Recognition IX, Proc. SPIE, Vol. 3718,
Ed: Firooz A. Sadjadi, pp. 2-13.
April 1999. (gzipped postscript)
S.C. Zhu, A.D. Lanterman, M.I. Miller, Clutter Modeling and
Performance Analysis in Automatic Target Recognition, Proc. Workshop on
Detection and Classification of Difficult Targets,
U.S. Army Aviation and Missile Command, Restone Arsenal,
Alabama, June 1998, pp. 477-496.
A.D. Lanterman, M.I. Miller, D.L. Snyder,
Minimum description length understanding of infrared scenes,
in Automatic Object Recognition VIII, Proc. SPIE, Vol. 3371,
Ed: Firooz A. Sadjadi, April 1998, pp. 375-386.
(PDF – link fixed 5/26/03)
A.D. Lanterman,
Representations of
shape for structural inference in infrared scenes,
in Automatic Object Recognition VII, Proc. SPIE, Vol. 3069,
Ed: Firooz A. Sadjadi, April 1997, pp. 257-268.
(
PDF – link fixed 5/26/03)
A.D. Lanterman, M.I. Miller, D.L. Snyder,
Representations of thermodynamic variability
in the automated understanding of FLIR scenes,
in Automatic Object Recognition VI, Proc. SPIE, Vol. 2756,
Ed: Firooz A. Sadjadi, April 1996, pp. 26-37.
(PDF)
A.D. Lanterman, M.I. Miller, D.L. Snyder,
Automatic Target Recognition via the Simulation of Infrared
Scenes,
in Proc. of the Sixth Annual
Ground Target Modeling and Validation Conference,
Keweenaw Research Center, Michigan Tech. Univ.,
August 1995, p. 195-204.
(PDF)
A.D. Lanterman, M.I. Miller, D.L. Snyder,
The unification of detection, tracking, and recognition
for millimeter wave and infrared sensors,
in Radar/Ladar Processing, Proc. SPIE, Vol. 2562,
Ed. William J. Miceli, July 1995, pp. 150-161.
(gzipped
postscript 645K)
A.D. Lanterman, M.I. Miller, D.L. Snyder,
Implementation of jump-diffusion algorithms for
understanding FLIR scenes,
in Automatic Object Recognition V, Proc. SPIE, Vol. 2485,
Ed: Firooz A. Sadjadi, April 1995, pp. 309-320.
(gzipped
postscript 236K)
A.D. Lanterman, M.I. Miller, D.L. Snyder, and W.J. Miceli,
Jump-diffusion processes for the automated understanding of FLIR
scenes,
in Automatic Object Recognition IV, Proc. SPIE, Vol. 2234,
Ed: Firooz J. Sadjadi, April 1994, pp. 416-427.
(gzipped
postscript 56K)
Master’s thesis
A.D. Lanterman, Jump-diffusion algorithms for the automated understanding
of forward-looking infrared scenes, Master’s thesis, Washington
University, May 1995. This is a large document, so we have made it available
in four parts:
Uncompressed:
Part 1 (3842K) |
Part 2 (3970K) |
Part 3 (1983K) |
Part 4 (1626K)
Compressed with gzip:
Part 1 (137K) |
Part 2 (212K) |
Part 3 (221K) |
Part 4 (149K)
CCD image restoration
Journal papers
M. Faisal, A.D. Lanterman, D.L. Snyder and R. L. White,
Implementation of a modified
Richardson-Lucy method for image restoration on a
massively parallel computer to compensate for
space-variant point-spread of a charge-coupled-device camera,
Journal of the Optical Society of America A,
Vol. 12, No. 12, December 1995, pp. 2593-2603.
D.L. Snyder, C.W. Helstrom, A.D. Lanterman, M. Faisal, and R.L. White,
Compensation for read-out noise in
charge-coupled-device images, Journal of the Optical Society
of America A, Vol. 12, No. 2, February 1995, pp. 272-283.
Conference papers
D.L. Snyder, C.W. Helstrom, A.D. Lanterman, M. Faisal, and R.L. White,
Compensation for read-out noise in HST image restoration,
in
The Restoration of HST Images and Spectra II,
Proc. Image Restoration Workshop,
Space Telescope Science Institute,
Baltimore MD, Nov. 1993, pp. 139-154.
D.L. Snyder, C.W. Helstrom, A.D. Lanterman, and M. Faisal,
Evaluation of a function occurring in maximum-likelihood
image-restoration for CCD camera data,
Proc. 31st Annual Allerton Conf. on Communication, Control, and
Computing, Univ. of Illinois, Urbana IL, Sept. 1993, p. 492.
Medical imaging
M.I. Miller, C.S. Butler, A.D. Lanterman, T. Miller, D.L. Snyder,
and J.W. Wallis,
Enhanced resolution SPECT via 3D iterative reconstruction in
clinical time frames, ESSRL Monograph.
D.L. Snyder, A.D. Lanterman, M.I. Miller,
Regularizing images in emission tomography via an extention of
Good’s roughness penalty,
ESSRL Monograph, presented at the IEEE Medical Imaging Conference,
Orlando, Florida, Nov. 1993.
D.L. Snyder, A.D. Lanterman, M.I. Miller,
An extension of Good’s Roughness Penalty for Nonparametric
Density-Estimation,
Proc. 30th Annual Allerton Conf. on Communication, Control, and
Computing, Univ. of Illinois, Urbana IL, Sept. 1993.
A.D. Lanterman,
A new way to regularize maximum likelihood estimates for emission
tomography with Good’s roughness penalty,
ESSRL Monograph, presented at the IEEE Region 5 conference, San Antonio,
Texas, April 1992.
Selected Presentation Viewgraphs
Life Beyond Gauss:
Signal Processing with Alpha-Stable Distributions, a presentation prepared
for an independent study with Dan Fuhrmann at Washington University; also
given as a DSP seminar at Univ. of Illinois at Urbana-Champaign.
(gzipped postscript)
Statistical Radar Imaging of Diffuse and Specular Targets
Using an Expectation-Maximization Algorithm,
presented in Algorithms for Synthetic Aperture Radar Imagery VII,
at SPIE Aerosense 2000 in Orlando, FL, April 2000.
(gzipped postscript)
Tracking and recognition of airborne targets via
commercial television and FM radio signals, presented in
Acquisition, Tracking, and
Pointing XIII, at SPIE Aerosense 1999 in Orlando, FL, April 1999.
(gzipped postscript)
Last modified 3/6/05
Maintained by Aaron Lanterman
lanterma@ece.gatech.edu