Tomographic Inversion on Multiple Receivers/Arrays from Multiple Sources for the Estimation of Shallow Water Bottom Properties

  • Alex Tolstoy


Geoacoustic inversion in even rather simplified range independent regions (but for multiple unknown parameters) is known to be quite difficult [TCB]. Additionally, inversion for even one parameter but in a range-dependent region is also quite difficult [DYOC]. As might be expected, a combination of range variability plus multiple parameters leads to an extremely difficult problem. Recent efforts have concentrated on an approach which estimates range-independent, i.e., range-averaged, parameters on individual source-receiver/array (SR) paths and then combines all the results in a matrix inversion to estimate the range-dependent region properties. This chapter is analogous to one successfully developed for the estimation of large volume ocean sound-speed profiles (as seen in [T3]). This chapter will discuss recent efforts for this new shallow water tomographic geoacoustic inversion via individual paths.


Inversion Method Tomographic Method Inversion Error Small Condition Number Bottom Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [DYOC]
    S. Dosso, M.L. Yeremy, J.M. Ozard, and N.R. Chapman. Estimation of ocean-bottom properties by matched field inversion of acoustic field data. IEEE J. Ocean. Eng., 18:232–239, 1993.CrossRefGoogle Scholar
  2. [FD]
    M.R. Fallat and S.E. Dosso. Geoacoustic inversion for Worskhop ’97 benchmark test cases using simulated annealing. J. Comput. Acoust., 6(1 & 2):29–44, 1998.CrossRefGoogle Scholar
  3. [J]
    L. Jaschke. Geophysical Inversion by the Freeze Bath Method with an Application to Geoacoustic Ocean Bottom parameter Estimation. PhD Thesis, University of Victoria, 1997.Google Scholar
  4. [JF]
    F.B. Jensen and C.M. Ferla. Numerical solutions of range-dependent benchmark problems in ocean acoustics. J. Acoust. Soc. Am., 87:1499–1510, 1990.ADSCrossRefGoogle Scholar
  5. [JKPS]
    F.B. Jensen, W.A. Kuperman, M.B. Porter, and H. Schmidt. Computational Ocean Acoustics, American Institute of Physics, New York, 1994.Google Scholar
  6. [T1]
    A. Tolstoy. Tomographic inversion for geoacoustic parameters in shallow water. ICTCA’99 Proceedings book, 2000.Google Scholar
  7. [T2]
    A. Tolstoy. MFP benchmark inversions via the RIGS method. J. Comput. Acoust., 6(1 & 2):185–203, 1998.CrossRefGoogle Scholar
  8. [T3]
    A. Tolstoy. Performance of acoustic tomography via matched field processing. J. Comput. Acoust., 2(1): 1–10, 1994.MathSciNetCrossRefGoogle Scholar
  9. [T4]
    A. Tolstoy. Matched Field Processing in Underwater Acoustics. World Scientific, Singapore, 1993.Google Scholar
  10. [T5]
    A. Tolstoy. Linearization of the matched field processing approach to acoustic tomography. J. Acoust. Soc. Am., 91(2):781–787, 1992.ADSCrossRefGoogle Scholar
  11. [TCB]
    A. Tolstoy, N.R. Chapman, and G. Brooke. Workshop: Benchmarking for geoacoustic inversion in shallow water. J. Comput. Acoust., 6(1 & 2):1–28, 1998.CrossRefGoogle Scholar
  12. [WK]
    E.K. Westwood and R.A. Koch. Elimination of branch cuts from the normal mode solution using gradient half-spaces. J. Acoust. Soc. Am., 106:2513–2523, 1999.ADSCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Alex Tolstoy

There are no affiliations available

Personalised recommendations