Abstract
It is very difficult to present in one lecture all the material corresponding to the title of this paper. There are entire books on adaptive filtering and we do not even intend to make a résumé of them [1]–[4]. Adaptive systems have been the topic of many papers in previous meetings of the NATO Advanced Study Institute on Underwater Acoustics and Signal Processing, and this tutorial lecture will not make a new contribution to the field. On the contrary, after a long period of production, it is now time to make an overview of this material. As the field is extremely broad, it would of course be impossible to cover all the problems in one lecture, and we will focus our attention on some points which especially interest us.
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References
M.L. HONIG and D.G. MESSERSCHMITT, Adaptive filters: Structures, Algorithms and Applications, Kluwer Academic, Boston, 1984.
C. COWAN and P. GRANT, Adaptive filters, Prentice Hall, Englewood Cliffs, N.J., 1985.
B. WIDROW and S.D. STEARNS, Adaptive Signal Processing, Prentice Hall, Englewood Cliffs, N.J., 1985.
M. BELLANGER, Adaptive Digital Filters and Signal Analysis, Marcel Dekker, New York, 1987.
C.W. HELSTROM, Statistical theory of signal detection, Pergamon Press, New-York, 1968.
H.L. VAN TREES, Detection, estimation and modulation theory, Wiley, New-York, 1971.
P. COMON and J.L. LACOUME, Noise reduction for an estimated Wiener filtering using noise reference, IEEE Trans. on Inf. Theory, IT 32, pp. 310–313, 1986.
P. COMON and D. PHAM, An error bound for a noise canceller, Internal report, CEPHAG, Grenoble, 1988.
B. PICINBONO et P. DUVAUT, Detection and contrast, in Stochastic processes in underwater acoustics, edited by C. Baker, Lectures Notes in Control and Information Science, 85, Springer-Verlag, 1986.
I.S. REED, J.D. MALLET and L.E. BRENNAN, Rapid convergence rate in adaptive arrays, IEEE Trans. Aerospace and Electronic Systems, AES 8, pp.853–863, 1974.
S. KAY, Asymptotically optimal detection in unknown colored noise via autoregressive modeling, IEEE Trans. ASSP, 31, pp.927–940, 1983.
S. KAY and D. SENGUPTA, Optimal detection in colored non-Gaussian noise with unknown parameters, ICASSP 1987, Dallas, pp. 1087–1090, 1987.
E.J. KELLY, An adaptive detection algorithm, IEEE Trans. Aerospace and Electronic Systems, AES 22, pp. 115–127, 1986.
B. PORAT and B. FRIEDLANDER, Parametric techniques for adaptive detection of Gaussian signals”, IEEE Trans. ASSP, 32, pp.780–790.
D. TUFTS, I. Kirsteins and R. Kumaresan, Data-adaptive detection of a weak signal, IEEE Trans. Aerospace and Electronic Systems, pp.313–316, 1983.
I. KIRSTEINS and D. TUFTS, On the probability density of signal to noise ratio in an improved adaptive detector, ICASSP 85, pp.572–575, 1985.
G. VEZZOSI, B. PICINBONO, Détection d’un signal certain dans un bruit sphériquement invariant, structure et caractéristiques des récepteurs, Annales des Télécommunications, Vol.27, n° 3–4, pp.95–110, 1972.
P.G. CABLE, Maximum likelihood detection of signals in noise with unknown level, dans Aspects of Signal Processing, G. Tacconi (éditeur), Reidel, pp. 229–250, 1977.
M.H. EL AYADI, B. Picinbono, NAR AGC adaptive detection of nonoverlapping signals in noise with fluctuating power, IEEE Transactions on Acoustic, Speech and Signal Processing, Vol. 29, n° 5, pp.952–963, 1981.
M.A. BLANCO, R.M. BARNES, On the detection of signals of unknown energy in clutter of unknown power, 1980, IEEE Canadian Communications and Power Conference, 15–17/10/1980, Montréal.
J.P. GIBSON, J.L. MELSA, Introduction to non-parametric detection with applications, Academic Press, 1975.
G. VEZZOSI, What is optimality for an adaptive detection system?, Signal Proc, NATO Advanced Study Institute, Academic Press, p.657, 1973.
F. LEFAUDEUX, Algorithmes pragmatiques de normalisation, VIII Colloque GRETSI, Nice, Juin 1981, pp.651–655, 1981.
V. HANSEN and J. SAWYERS, Detectability loss due to the greatest of selection in a cell-averagving CFAR, IEEE Trans. Aerospace and Electronics Systems, AES 16, pp. 115–118, 1980.
M. WEISS, Analysis of some modified cell-averaging CFAR processors in multiple-target situations, IEEE Transaction on Aerospace and Electronic Systems, Vol.18, n° 1, pp. 102–114, 1982.
E.K. EL HUSSAINI, B.M. IBRAHIM, Comparison of adaptive cell-avaraging detectors for multiple-target situations, Proceedings of the IEEE, Vol.133, n° 3, pp.217–223, 1986.
R. NITZBERG, Clutter map CFAR analysis, IEEE Transactions on Aerospace and Electronic Systems, Vol.22, n° 4, pp.419–421, 1986.
W.A. STRUZINSKI et E.D. LOWE, Performance comparison of four noise background normalization schemes proposed for signal detection systems, Journal of the Acoustical Society of America, Vol.76, n° 6, pp. 1738.1732., 1984.
W.A. STRUZINSKI et E.D. LOWE, The effect of improper normalization on the performance of an automated energy detector, Journal of the Acoustical Society of America, Vol.78, n° 3, pp.936–941, 1985.
C. PLUMEJEAUD, B. RAFINE et B. LUCAS, Un algorithme de normalisation, IX colloque GRETSI, Nice 1983, pp. 111–114, 1983.
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Picinbono, B. (1989). Adaptive Methods in Temporal Processing. In: Chan, Y.T. (eds) Underwater Acoustic Data Processing. NATO ASI Series, vol 161. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-2289-1_35
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DOI: https://doi.org/10.1007/978-94-009-2289-1_35
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