Maximum likelihood estimation of A-scan amplitudes for coherent targets in media of unresolvable scatterers

The author derives a maximum-likelihood estimator (MLE) for A-scan amplitudes corresponding to coherent reflectors embedded in media of unresolvable scatterers. The MLE processes sampled RF A-scans from broadband ultrasonic pulse-echo systems. A major source of interference for these signals is the backscattered energy from the unresolvable scatterers that exist throughout the beam field. A statistical model is formulated that characterizes the backscattered energy from a resolution cell when a coherent target scatterer is present. It is shown that the MLE is equivalent to a matched filter when the distribution of the interfering back-scatter energy is stationary over the resolution cell. In addition, the form of the MLE is described when the interfering echoes are not stationary within the resolution cell. Experimental results are presented for an adaptive implementation of the MLE applied to flaw detection in stainless steel. The results demonstrate the ability of the MLE to reveal targets masked by grain echoes, without prior knowledge of the gain-echo spectral characteristics.<<ETX>>

[1]  E. S. Furgason,et al.  Flaw-to-grain echo enhancement by split-spectrum processing , 1982 .

[2]  James A. Ritcey,et al.  Performance of max-mean level detector with and without censoring , 1989 .

[3]  W. E. Lawrie,et al.  Ultrasonic testing of materials: 2nd English Edition, translated from the 3rd German Edition, J. & H. Krautkrämer Springer-Verlag, Berlin, Heidelberg, New York (1977) 667 pp, $65.20, DM 148 , 1978 .

[4]  Steven P. Neal,et al.  A prior knowledge based optimal Wiener filtering approach to ultrasonic scattering amplitude estimation , 1989 .

[5]  G. Wade,et al.  Fundamentals of Digital Ultrasonic Processing , 1984, IEEE Transactions on Sonics and Ultrasonics.

[6]  F. Harris On the use of windows for harmonic analysis with the discrete Fourier transform , 1978, Proceedings of the IEEE.

[7]  Steven P. Neal,et al.  The Measurement and Analysis of Acoustic Noise as a Random Variable , 1990 .

[8]  P. Welch The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms , 1967 .

[9]  J. Goodman Some fundamental properties of speckle , 1976 .

[10]  Dennis L. Parker,et al.  Analysis of B-Scan Speckle Reduction by Resolution Limited Filtering , 1982 .

[11]  Kevin D. Donohue,et al.  A Robust Detection Algorithm Using Frequency Diverse Multiple Observations , 1990 .

[12]  F. L. Thurstone,et al.  Acoustic Speckle: Theory and Experimental Analysis , 1979 .

[13]  P. A. Magnin,et al.  A-Mode Speckle Reduction with Compound Frequencies and Compound Bandwidths , 1984 .

[14]  N. Bilgutay,et al.  SPLIT-SPECTRUM PROCESSING FOR FLAW-TO-GRAIN ECHO ENHANCEMENT IN ULTRASONIC DETECTION , 1981 .

[15]  P.M. Shankar,et al.  Split-spectrum processing: analysis of polarity threshold algorithm for improvement of signal-to-noise ratio and detectability in ultrasonic signals , 1989, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[16]  N. Bilgutay,et al.  Analysis and Comparison of Some Frequency Compounding Algorithms for the Reduction of Ultrasonic Clutter , 1986, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[17]  Keinosuke Fukunaga,et al.  Introduction to Statistical Pattern Recognition , 1972 .

[18]  L. Verrazzani,et al.  Power spectrum equalization for ultrasonic image restoration , 1989, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[19]  Michael F. Insana,et al.  Analysis of ultrasound image texture via generalized rician statistics , 1986 .

[20]  W. Gardner Exploitation of spectral redundancy in cyclostationary signals , 1991, IEEE Signal Processing Magazine.

[21]  Fernand S. Cohen Modeling of ultrasound speckle with application in flaw detection in metals , 1992, IEEE Trans. Signal Process..

[22]  Joseph L. Rose,et al.  Split spectrum processing: optimizing the processing parameters using minimization , 1987 .

[23]  J. Saniie,et al.  Grain noise suppression through bandpass filtering , 1988 .

[24]  Nihat M. Bilgutay,et al.  Adaptive and robust filtering techniques for ultrasonic flaw detection , 1989, Proceedings., IEEE Ultrasonics Symposium,.

[25]  M Fatemi,et al.  Ultrasonic B-scan imaging: theory of image formation and a technique for restoration. , 1980, Ultrasonic imaging.

[26]  J. Goodman Statistical Optics , 1985 .

[27]  Shuang Chen,et al.  Detection of narrow-band sonar signals using order statistical filters , 1987, IEEE Trans. Acoust. Speech Signal Process..

[28]  R. F. Wagner,et al.  Ultrasound speckle size and lesion signal to noise ratio: verification of theory. , 1984, Ultrasonic imaging.