Aaron Lanterman's Publications

Main Publications Radar Project Teaching Likes & Links

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