Skip to main content
SpringerLink
Log in

High resolution processing techniques for temporal and spatial signals

  • Conference paper
  • First Online:
High-Resolution Methods in Underwater Acoustics

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 155))

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Bibliography

  1. H. C. Andrews and C. L. Patterson, “Outer Product Expansions and Their Uses in Digital Image Processing”, American Math. Monthly, Vol.82, No.1, January 1975, pp. 1–13

    Google Scholar 

  2. H. C. Andrews and C. L. Patterson, “Singular Value Decomposition (SVD) Image Coding”, IEEE Trans. on Communications, April 1976, pp. 425–432

    Google Scholar 

  3. O. Arikan and D.C. Munson, Jr., “A tomographic formulation of bistatic synthetic aperture radar,” in W.A Porter and S.C. Kak, Editors, Proceedings of the 1988 international conference on advances in communication & control systems, Dept. of Electrical and Computer Engineering, Louisiana State University, Baton Rouge, LA 70803, October 19–21, 1988, Baton Rouge, LA, pp. 418–431

    Google Scholar 

  4. William P. Ballance, “The Singular Value Decomposition: An Introduction”, Conference Record of the eighteenth Asilomar Conference on Circuits, Systems & Computers, held at Pacific Grove, California, Nov.5–7, 1984, IEEE Catalog No.85CH22200-4, pp. 148–157

    Google Scholar 

  5. M. Bernfeld, Chirp Doppler radar, Proc. IEEE Lett., Vol 72, No.4, April 1984, pp. 540–541

    Google Scholar 

  6. G. S. Bienvenu, “Influence of the Spatial Coherence of the Background Noise on High Resolution Passive Methods”, ICASSP 79 Record, pp. 306–309

    Google Scholar 

  7. Boashash, B. and H.J. Whitchouse, “Seismic Applications of the Wigner-Ville Distribution”, Proceedings of IEEE International Symposium on Circuits and Systems, Vol. 1 of 3, pp. 34–37, San Jose, USA, May 1986

    Google Scholar 

  8. B. Boashash and H.J. Whitehouse, “High Resolution Wigner-Ville Analysis”, Onzième Colloque GRETSI, Nice, 1–5 June, 1987, pp. 205–208

    Google Scholar 

  9. Boashash, B. and P. Black, “An efficient real time implementation of the Wigner-Ville Distribution”, IEEE transactions on Acoustics, Speech and Signal Processing, Vol. 35, pp. 1611–1618, November, 1987

    Google Scholar 

  10. Boashash, B. “Time-Frequency Signal Analysis and Synthesis — the choice of a Method and its Application”, Proc. of SPIE Conference, Advanced Algorithms and Architectures, San Diego, Vol. 975, pp. 164–185, Aug. 1988

    Google Scholar 

  11. Boashash, B., “Note on the Use of the Wigner Distribution for Time Frequency Signal Analysis”, IEEE Trans. on ASSP, Vol. 36, pp. 1518–1521, September, 1988

    Google Scholar 

  12. Boashash, B. and H. J. Whitehouse, “High Accuracy Time-Frequency Analysis of FM Signals using an Autoregressive Wigner-Ville Distribution”, submitted to the IEEE Transactions on Acoustics, Speech, and Signal Processing

    Google Scholar 

  13. B. R. Breed and T. E. Posch, “A Range and Azimuth Estimator Based on Forming the Spatial Wigner Distribution”, Proc. ICASSP '84, paper 41B9

    Google Scholar 

  14. Y. Bressler and A. Macovski, “Exact Maximum Likelihood Parameter Estimation of Superimposed Exponential Signals in Noise”, IEEE Trans. on Acoustics, Speech, and Signal Processing, Vol. ASSP-34, No.5, Oct. 1986, pp. 1081–1089

    Google Scholar 

  15. Burg, J.P., “Maximum Entropy Spectral Analysis”, Proc. 37th Meet. Soc. of Exploration Geophysicists, Oklahoma City, OK, 1967

    Google Scholar 

  16. J. A. Cadzow, “A High Resolution Direction-of-Arrival Algorithm for Narrow-Band Coherent and Incoherent Sources”, IEEE Trans. on Acoustics, Speech, and Signal Processing, Vol.36, No.7, July, 1988, pp. 965–979

    Google Scholar 

  17. J. Capon, R. Greenfield, and R. J. Kolker, “Multidimensional Maximum-Likelihood Processing of a Large Aperture Seismic Array”, Proc. IEEE, Vol.55, p.192–211, Feb. 1967

    Google Scholar 

  18. J. Capon, “High Resolution Frequency-Wavenumber Spectrum Analysis”, Proc. IEEE, Vol. 57, pp. 1408–1418, Aug.1969

    Google Scholar 

  19. Cohen, L., “Time-Frequency Distributions: A Review”, Proc. IEEE, July 1989

    Google Scholar 

  20. P. J. Eberlein, “On the Schur Decomposition of a Matrix for Parallel Computation”, IEEE Trans. on Computers, Vol. C-36, No.2, Feb. 1987, pp. 167–174

    Google Scholar 

  21. M. Feder and E. Weinstein, “Optimal Multiple Source Location Estimation via the EM Algorithm”, ICASSP 85 Proceedings, Vol.4, paper 45.6, pp. 1762–1765

    Google Scholar 

  22. E. Feig and F.A Grünbaum, “Tomographic methods in range-Doppler radar,” Inverse Problems, Vol. 2, pp. 185–195, 1986

    Google Scholar 

  23. P. Flandrin, “A Time-Frequency Formulation of Optimum Detection”, IEEE Trans. on Acoustics, Speech, and Signal Processing, Vol.36, No.9, September 1988, pp. 1377–1384

    Google Scholar 

  24. G. H. Golub and C. F. Van Loan, Matrix Computations, Johns Hopkins University Press, Baltimore, 1983, third printing, with corrections, 1985

    Google Scholar 

  25. I. J. Good, “Some Applications of the Singular Decomposition of a Matrix”, Technometrics, Vol.11, No.4, November 1969, pp. 823–831

    Google Scholar 

  26. S. Haykin (Ed.), Nonlinear Methods of Spectral Analysis, Springer-Verlag, 1979

    Google Scholar 

  27. D. H. Johnson and S. R. De Graaf, “Improving the Resolution of Bearing in Passive Sonar Arrays by Eigenvalue Analysis”, IEEE Trans. on Acoustics, Speech, and Signal Processing, Vol. ASSP-30, No.4, pp. 638–647, August 1982

    Google Scholar 

  28. Kailath, T.(Ed.), Modern Signal Processing, Hemisphere Publishing Corporation, 1985

    Google Scholar 

  29. F. T. Luk, “A Parallel Method for Computing the Generalized Singular Value Decomposition”, Journal of Parallel and Distributed Computing, Vol2, 1985, pp. 250–260

    Google Scholar 

  30. M. T. Ma, Theory and Applications of Antenna Arrays, John Wiley & Sons, 1974

    Google Scholar 

  31. R. N. McDonough, “Application of the Maximum-Likelihood Method and Maximum Entropy Method to Array Processing”, Chapter 6 of Nonlinear Methods of Spectral Analysis, edited by S. Haykin, Springer-Verlag, 1979

    Google Scholar 

  32. J. G. McWhirter and T. J. Shepherd, “Efficient minimum variance distortionless response processing using a systolic array”, Proc. SPIE, Vol.975, paper 975-39, pp. 385–392

    Google Scholar 

  33. Makhoul, J., “Linear Prediction: A Tutorial Review”, Proc. IEEE, Vol. 63, No.4, pp. 561–580, April, 1975

    Google Scholar 

  34. Marple, S.L., Digital Spectral Analysis — with applications, Prentice Hall Inc, 1985

    Google Scholar 

  35. S. L. Marple, Digital Spectral Analysis, Prentice-Hall, 1987

    Google Scholar 

  36. G. E. Martin, “Signal subspace processing of experimental radio data”, SPIE Proceedings Vol.975, paper 975-11, pp. 101–107, 1988

    Google Scholar 

  37. W. Mecklenbräuker, “A Tutorial on Non-Parametric Bilinear Time-Frequency Signal Representations”, in Les Houches, Session XLV, 12 Août-6 Septembre 1985, Traitment du Signal / Signal Processing, edited by J. L. Lacoume, T. S. Durrani, and R. Stora, Elsevier Science Publishers, B. V., 1987, pp. 277–336

    Google Scholar 

  38. M. I. Miller and D. R. Fuhrmann, “An EM Algorithm for Direction-of-Arrival Estimation for Narrowband Signals in Noise”, Proc. SPIE, Vol.826, pp. 101–103 (1987)

    Google Scholar 

  39. Minami, K., Kawata, S. and Minami, S., “Superresolution of Fourier Transform Spectra by Autoregressive Model Fitting with Singular Value Decomposition”, Appl. Optics, Vol. 24, no. 2, pp. 162–167, Jan. 1985

    Google Scholar 

  40. R. A. Monzingo and T. W. Miller, Introduction to Adaptive Arrays, John Wiley & Sons, 1980

    Google Scholar 

  41. J. C. Nash, Compact Numerical Methods for Computers, John Wiley & Sons, New York, 1979

    Google Scholar 

  42. U. Nickel, “Angle Estimation with Adaptive Arrays and Relation to Superresolution”, IEE Proc., Vol.134, Part II, pp. 77–82 (1987)

    Google Scholar 

  43. N. L. Owsley, „Sonar Array Processing“, Chapter 3 of Array Signal Processing, edited by S. Haykin, Prentice-Hall, 1985

    Google Scholar 

  44. C. C. Paige, “Computing the Generalized Singular Value Decomposition”, SIAM J. Sci. Stat. Comput., Vol.7, No.4, October 1986, pp. 1126–1146

    Google Scholar 

  45. A. Paulraj, R. Roy, and T. Kailath, “Estimation of Signal Parameters via Rotational Invariance Techniques-ESPRIT”, Conference Record of the Nineteenth Asilomar Conference on Circuits, Systems, and Computers, Nov.6–8, 1985, pp. 83–89

    Google Scholar 

  46. A. Paulraj, R. Roy, and T. Kailath, “A subspace rotation approach to estimating directions of arrival”, Proc. ICASSP 86, April 7–11, 1986, Vol.4, paper 47.2, pp. 2495–2498

    Google Scholar 

  47. A. Paulraj, R. Roy, and T. Kailath, “A subspace rotation approach to signal parameter estimation”, Proc. IEEE, July 1986, pp. 1044–1045

    Google Scholar 

  48. V. F. Pisarenko, “The Retrieval of Harmonics from a Covariance Function”, Geophys. J. R. astr. Soc., Vol.33, pp. 347–366, (1973)

    Google Scholar 

  49. S. S. Reddi, “On a Spatial Smoothing Technique for Multiple Source Location”, IEEE Trans. on Acoustics, Speech, and Signal Processing, Vol. ASSP-35, No.5, May, 1987, p.709

    Google Scholar 

  50. R. Roy, A. Paulraj, and T. Kailath, “Comparative Performance of ESPRIT and MUSIC for Direction-of-Arrival Estimation”, ICASSP 87, IEEE Order No. CH2396-0/87, Volume 4, paper 54.12, pp. 2344–2347

    Google Scholar 

  51. R. Roy and T. Kailath, “Invariance Techniques and high-resolution null steering”, Advanced Algorithms and Architectures for Signal Processing III, SPIE Vol. 975, (1988), paper 975-35, pp. 358–367

    Google Scholar 

  52. R. O. Schmidt “Multiple Emitter Location and Signal Parameter Estimation”, Proceedings of the RADC Spectrum Estimation Workshop, Rome Air Development Center, pp. 243–257, Oct.3–5, 1979

    Google Scholar 

  53. R. O. Schmidt, A Signal Subspace Approach to Multiple Emitter Location and Spectral Estimation, Ph.D. Dissertation, Dept. of Electrical Engineering, Stanford University, November, 1981

    Google Scholar 

  54. R. Schreiber and P. J. Kuckes, “Systolic Linear Algebra Machines for Digital Signal Processing”, in VLSI and Modern Signal Processing, edite by S. Y. Kung, H. J. Whitehouse, and T. Kailath, Prentice Hall, 1985, pp. 389–405

    Google Scholar 

  55. T. J. Shan, M. Wax, and T. Kailath, “On Spatial Smoothing for Direction of Arrival Estimation of Coherent Signals”, IEEE Trans. on Acoustics, Speech, and Signal Processing, Vol.ASSP-33, No.4, Aug. 1985, pp. 806–811

    Google Scholar 

  56. S. D. Silverstein, “Robust Spectral Estimation: Autocorrelation Based Minimum Free Energy Method”, Twenty-Second Asilomar Conference on Signals, Systems & Computers, Oct. 31–Nov. 2, 1988

    Google Scholar 

  57. D. L. Snyder, L. J. Thomas, Jr., and M. M. Ter-Possian, “A Mathematical Model for Positron Emission Tomography Systems Having Time-of-Flight Measurements”, IEEE Trans. on Nuclear Science, Vol. NS-28, pp. 3575–3583, June 1981

    Google Scholar 

  58. D.L. Snyder, H.J. Whitehouse, J.T. Wohschlaeger, R.C. Lewis, “A New Approach to RADAR/SONAR Imaging”, Proceedings of the SPIE 30th Annual Technical Symposium, San Diego, CA, August 1986

    Google Scholar 

  59. J. M. Speiser, H. J. Whitehouse, and N. J. Berg, “Signal Processing Architectures using Convolutional Technology”, Proc. SPIE Vol.154, pp. 66–80, 1978

    Google Scholar 

  60. Speiser, J., Bromley, K., and Whitehouse, H.J., “Signal Processing Applications for Real-Time Matrix Operations”, in Advanced Computer Concepts, LJI Conference Proceedings, La Jolla Institute, Editor J.C. Solinsky, pp. 35–46, 1981

    Google Scholar 

  61. J. M. Speiser, “Progress in Eigenvector Beamforming”, SPIE Proceedings Vol.564, paper 564-01, 1985

    Google Scholar 

  62. J. M. Speiser, “Signal Processing Computational Needs”, Proc. SPIE, Vol.696, pp. 2–6 (1986)

    Google Scholar 

  63. J. M. Speiser, “Some Observations Concerning the ESPRIT Direction Finding Method”, Proc. SPIE, Vol.826, pp. 178–185, (1987)

    Google Scholar 

  64. J. M. Speiser, “An Overview of Matrix-Based Signal Processing”, Conference Record of the Twenty-First Asilomar Conference on Circuits, Systems, and Computers, held at Pacific Grove, CA, Nov.2–4, 1987, IEEE Computer Society Order No. 760, pp. 284–289

    Google Scholar 

  65. B. D. Steinberg, Principles of Aperture and Array System Design, John Wiley & Sons, 1976

    Google Scholar 

  66. A. L. Swindlehurst and T. Kailath, “Near-field source parameter estimation using a spatial Wigner distribution approach”, Advanced Algorithms and Architectures for Signal Processing III, SPIE Vol. 975, (1988), paper 975-09, pp. 86–92

    Google Scholar 

  67. H.H. Szu, “Two-dimensional optical processing of one-dimensional acoustic data”, Optical Engineering Vol. 21, 1982, pp. 804–813

    Google Scholar 

  68. Tufts, D.W. and Kumaresan, R., “Singular value decomposition and improved estimation using linear prediction”, IEEE Trans ASSP, vol.30, no.4, Aug 1982

    Google Scholar 

  69. H.L. Van Trees, Detection, Estimation, and Modulation Theory, Part III, Radar-Sonar Signal Processing and Gaussian Signals in Noise, John Wiley and Sons, New York, 1971

    Google Scholar 

  70. R. A. Wagstaff and A. Baggeroer (editors), High Resolution Spatial Processing in Underwater Acoustics, Naval Ocean Research and Development Activity, NSTL

    Google Scholar 

  71. D.R. Wehner, High Resolution Radar, Artech House, 1987

    Google Scholar 

  72. A. J. Weiss, A. S. Willsky, and B. C. Levy, “Maximum Likelihood Array Processing for the Estimation of Superimposed Signals”, em Conference Record of the Twenty-First Asilomar Conference on Signals, Systems, and Computers, held at Pacific Grove, CA, Nov.2–4, 1987, Vol.2, pp. 845–848

    Google Scholar 

  73. H. J. Whitehouse and B. Boashash, “Signal Processing Applications of Wigner-Ville Analysis”, SPIE Vol.696 Advanced Algorithms and Architectures for Signal Processing (1986), pp. 156–162

    Google Scholar 

  74. Whitehouse, H. J., “Interpretation of radar imaging in terms of the Wigner-Ville distribution”, presented at Advanced Algorithms and Architectures in Signal Processing, SPIE International Symposium, San Diego, Calif, August 15–17, 1988

    Google Scholar 

  75. H. J. Whitehouse and B. Boashash, “Delay-Doppler Radar/Sonar Imaging”, presented at EUSIPCO 88, Grenoble, France, 5–9 Sept, 1988

    Google Scholar 

  76. H. J. Whitehouse and L. B. White, “Resolution Enchancement in Time-Frequency Signal Processing Using Tomographic Imaging”, to appear in ICASSP 89, May 23–26, 1989, Glascow, Scotland

    Google Scholar 

  77. I. Ziskind and M. Wax, “Maximum Likelihood Localization of Multiple Sources by Alternating Projection”, IEEE Trans. on Acoustics, Speech, and Signal Processing, Vol. ASSP-36, No.10, Oct. 1988, pp. 1553–1560

    Google Scholar 

  78. M. D. Zoltowski, “Novel Techniques for Estimation of Array Signal Parameters Based on Matrix Pencils, Subspace Rotations, and Total Least Squares”, ICASSP 88 Conference Proceedings, Vol.V, pp. 2861–2864

    Google Scholar 

  79. M. D. Zoltowski, “Generalized Minimum Norm and Total Least Squares with Applications to Array Signal Processing”, Advanced Algorithms and Architectures for Signal Processing III, SPIE Vol. 975, (1988), paper 975-08, pp. 78–85

    Google Scholar 

  80. M. D. Zoltowski and D. Stavrinides, “Sensor Array Signal Processing Via a Procrustes Rotations Based Eigenanalysis of the ESPRIT Data Pencil”, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 37, No.6, June 1989, pp. 832–861

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Naval Ocean Systems Center, 92152-5000, San Diego, CA

    H. J. Whitehouse

  2. GRISSP, University of Queensland, 4067, Brisbane, Australia

    B. Boashash

  3. Naval Ocean Systems Center, 92152-5000, San Diego, CA

    J. M. Speiser

Authors
  1. H. J. Whitehouse
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. B. Boashash
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. J. M. Speiser
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Michel Bouvet Georges Bienvenu

Rights and permissions

Reprints and permissions

Copyright information

© 1991 Springer-Verlag

About this paper

Cite this paper

Whitehouse, H.J., Boashash, B., Speiser, J.M. (1991). High resolution processing techniques for temporal and spatial signals. In: Bouvet, M., Bienvenu, G. (eds) High-Resolution Methods in Underwater Acoustics. Lecture Notes in Control and Information Sciences, vol 155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0040090

Download citation

  • DOI: https://doi.org/10.1007/BFb0040090

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-53716-8

  • Online ISBN: 978-3-540-47013-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation