Fluctuations of Seafloor Backscatter Data From Multibeam Sonar Systems

Several theoretical models of seafloor backscatter statistics developed over recent years show a reasonable agreement with experimental measurements made with sonar systems. However, methods of data collection and processing used in modern multibeam systems are often not taken into consideration when analyzing statistical characteristics of observed backscatter data. Fluctuations of various backscatter parameters, which can be derived from raw multibeam data, and their statistical properties, are analyzed in this paper using data collected with a Reson SeaBat 8125 system from two different seafloor types on the southern continental shelf of Western Australia. It is shown that fluctuations of the backscatter envelope not affected by the sonar beam pattern can be reasonably well approximated by a Rayleigh distribution, when the seafloor insonification area is large compared to the horizontal scale of the seafloor roughness. Based on data analysis and theory of extreme value statistics, it is demonstrated that the peak backscatter intensity, collected by some sonar systems as a single backscatter characteristic for each sonar beam, leads to considerable overestimation of the seafloor backscatter strength at oblique angles of incidence when the beam footprint is much larger than the insonification area. Sidescan data synthesized in some modern multibeam systems are also affected by effects of signal processing on statistical properties of backscatter fluctuations. In contrast to the peak backscatter intensity, the backscatter energy provides an almost unbiased estimate of the seafloor backscatter strength. The gamma distribution is demonstrated to be an adequate approximation for fluctuations of the backscatter energy at oblique angles of incidence. It was also found that sonar parameters and settings, signal processing in sonar hardware, and the incidence angle of seafloor observation have a much greater effect on statistical characteristics of backscatter fluctuations than the difference in acoustical properties of the seafloor, except for the first moment of backscatter variations which is governed by the seafloor backscatter coefficient.

[1]  Kevin Barraclough,et al.  I and i , 2001, BMJ : British Medical Journal.

[2]  J. Teugels,et al.  Statistics of Extremes , 2004 .

[3]  A. Lyons,et al.  Statistical characterization of high-frequency shallow-water seafloor backscatter , 1999 .

[4]  J. Boucher,et al.  Processing of high-frequency multibeam echo sounder data for seafloor characterization , 2003 .

[5]  Iain Parnum,et al.  CHARACTERIZATION OF THE SEAFLOOR IN AUSTRALIA'S COASTAL ZONE USING ACOUSTIC TECHNIQUES , 2005 .

[6]  Iain Parnum,et al.  Statistics of seafloor backscatter measured with multibeam sonar systems , 2008 .

[7]  Jean-Marc Boucher,et al.  Angular Dependence of K-Distributed Sonar Data , 2007 .

[8]  E. Jakeman,et al.  Significance of K Distributions in Scattering Experiments , 1978 .

[9]  C. Klüppelberg,et al.  Modelling Extremal Events , 1997 .

[10]  C. D. de Moustier,et al.  High-frequency volume and boundary acoustic backscatter fluctuations in shallow water. , 2003, The Journal of the Acoustical Society of America.

[11]  D. Middleton New physical-statistical methods and models for clutter and reverberation: the KA-distribution and related probability structures , 1999 .

[12]  M.V. Trevorrow Statistics of fluctuations in high-frequency low-grazing-angle backscatter from a rocky sea bed , 2004, IEEE Journal of Oceanic Engineering.

[13]  Jean-Marc Boucher,et al.  Angular Dependence of ${\cal K}$ -Distributed Sonar Data , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[14]  Douglas A. Abraham,et al.  Novel physical interpretations of K-distributed reverberation , 2002 .

[15]  Iain Parnum,et al.  Benthic habitat mapping using multibeam sonar systems , 2007 .

[16]  E. Jakeman,et al.  Non-Gaussian models for the statistics of scattered waves , 1988 .