SIGNAL PROCESSING

The Signal Processing group at ARCON maintains an exceptionally strong capability in electromagnetic and acoustic signal processing algorithm development and implementation. Some examples of our expertise in this field are given in the following partial listing of our technical activities.

Development and implementation of adaptive signal processing schemes for non-Gaussian clutter cancellation
Constant false alarm rate (CFAR) techniques for correlated non-Gaussian interference backgrounds
Development and implementation of model-based signal processing algorithms for space-time adaptive processing (STAP) in non-Gaussian radar clutter
Statistical analysis of experimental bistatic radar clutter data
Development and implementation of advanced radar signal detection algorithms
Structured covariance matrix estimation for Gaussian and spherically invariant processes
Development of spectral estimation techniques for spherically invariant non-Gaussian noise phenomena
Endogenous models for non-Gaussian noise processes and their computer generation
Modeling, simulation and distribution approximation of non-Gaussian noise using spherically invariant random processes (SIRP)
Ambiguity function analysis for bistatic radar

Representative Publications List:

Journal Publications

"Non-Gaussian random vector identification using spherically invariant random processes,'' M. Rangaswamy, D. D. Weiner and A. Ozturk, IEEE transactions on Aerospace and Electronic Systems, AES-29 (1), January 1993, pp. 111-124.

"Computer generation of correlated non-Gaussian radar clutter,'' M. Rangaswamy, D.D. Weiner and A. Ozturk, IEEE transactions on Aerospace and Electronic Systems, AES-31, (1), January 1995, pp. 106-116.

"Distribution identification of correlated non-Gaussian radarclutter characterized by spherically invariant random processes,'' A. Ozturk, M. Rangaswamy and D.D. Weiner, submitted for publication to IEEE transactions on Aerospace and Electronic Systems.

"Multichannel detection for correlated Non-Gaussian random processes based on innovations,'' M. Rangaswamy, J.H. Michels, D.D. Weiner, IEEE transactions on Signal Processing, Vol. 43, No.8, August 1995, pp. 1915-1922.

"Maximum likelihood estimation of AR parameters for spherically invariant random processes,'' M. Rangaswamy, Submitted for publication to the IEEE Signal Processing Letters.

"Adaptive detection of signals in spherically invariant noise,'' R.S. Raghavan, X. Luo, M. Rangaswamy and D.J. McLaughlin, Submitted for publication to the IEEE Transactions on Signal Processing.

"A Parametric Detection Algorithm for Space-Time Adaptive Processing in Correlated Non-Gaussian Radar Clutter Backgrounds," M. Rangaswamy, J.H. Michels, Signal Processing, 1998 (To appear, Sept. 1998).

Conference Publications

"Simulation of correlated non-Gaussian clutter for radar signal detection,'' M. Rangaswamy, D.D. Weiner and A. Ozturk presented at the Twenty-fifth Asilomar conference on signals, systems and computers, Pacific Grove, CA, Nov 1991.

"Distribution identification of spherically invariant random vectors,'' Aydin Ozturk, Muralidhar Rangaswamy and Donald Weiner, presented at the Twentysixth Conference on Information Sciences and Systems, Princeton, NJ, March 1992.

"Innovations based detection algorithm for correlated non-Gaussian random processes,'' M. Rangaswamy, D.D. Weiner, J.H. Michels, presented at the Sixth SP Workshop on Statistical Signal and Array Processing, Victoria, British Columbia, October 1992.

"Multichannel detection for correlated non-Gaussian random processes,'' M. Rangaswamy, D.D. Weiner, J.H. Michels, presented at the SPIE International Symposium on Optical Engineering and Photonics in Aerospace and Remote Sensing, Orlando, FL, April 12-16, 1993.

"On the multichannel innovations based detection algorithm for correlated non-Gaussian random processes,'' M. Rangaswamy, D.D. Weiner, J.H. Michels, Twenty-seventh Asilomar conference on signals, systems and computers, Pacific Grove, CA, Nov 1993.

"Spherically invariant random processes for modeling Non-Gaussian radar clutter,'' M. Rangaswamy, invited paper at the Twenty-seventh Asilomar conference on signals, systems and computers, Pacific Grove, CA, Nov 1993.

"A parametric model-based multichannel detection algorithm,'' J.H. Michels and M. Rangaswamy, Adaptive sensor array processing conference, MIT Lincoln Laboratory, Lexington, MA, March 15-17, 1994.

"Maximum likelihood estimation of AR parameters for spherically invariant random processes,'' M. Rangaswamy, IEEE Dual use technology conference, Utica, NY, May, 1995.

"Distribution of scattered power from small clutter cells,'' L.M. Mockapetris and M. Rangaswamy, IEEE AP-S international symposium and URSI Radio Science Meeting, Baltimore, MD, July 1996.

"A parametric multichannel detection algorithm for correlated non-Gaussian random processes,'' M. Rangaswamy and J. H. Michels, IEEE national radar conference, Syracuse, NY, May 1997.

"Space-Time adaptive processing (STAP) in airborne radar applications," J. H. Michels, T. Tsao, B. Himed and M. Rangaswamy, Proceedings of the IASTED International Conference on Signal Processing and Communications, Canary Islands, Spain, February 1998.

"Signal detection performance of principal components inverse (PCI) for strong low rank non-Gaussian interference," B.E. Freburger, D.W. Tufts and M. Rangaswamy, in Proceedings of the 32^nd Conference on Information Sciences and Systems, Princeton, NJ, March 1998.

"Adaptive processing in non-Gaussian noise backgrounds," M. Rangaswamy and J.H. Michels, in Proceedings of the 9^th IEEE-SSAP Workshop, Portland, OR, September 1998.

"A unified framework for space-time adaptive processing," M. Rangaswamy, in Proceedings of the 9^th IEEE-SSAP Workshop, Portland, OR, September 1998.