Beyond bathymetry: Mapping acoustic backscattering from the deep seafloor with Sea Beam

In its standard mode of operation, the multibeam echosounder Sea Beam produces high resolution bathymetric contour charts of the seafloor surveyed. However, additional information about the nature of the seafloor can be extracted from the structure of the echo signals received by the system. Such signals have been recorded digitally over a variety of seafloor environments for which independent observations from bottom photographs or sidescan sonars were available. An attempt is made to relate the statistical properties of the bottom‐backscattered sound field to the independently observed geologicalcharacteristics of the seafloor surveyed. Acoustic boundary mapping over flat areas is achieved by following trend changes in the acoustic data both along and across track. Such changes in the acoustics are found to correlate with changes in bottom type or roughness structure. The overall energy level of a partial angular‐dependence function of backscattering appears to depend strongly on bottom type, whereas the shape of the function does not. Clues to the roughness structure of the bottom are obtained by relating the shape of the probability density function of normal‐incidence echo envelopes to the degree of coherence in the backscattered acoustic field

Field Evaluation of Sounding Accuracy in Deep Water Multibeam Swath Bathymetry

A new Kongsberg-Simrad EM120 multibeam echo-sounder has been installed aboard Scripps Institution of Oceanography\u27s Research Vessel Roger Revelle in January 2001. This system can map reliably a 20 km swath of seafloor in 4000 m water depth with 191 soundings per ping. Such a wide swath width demands highly accurate (\u3c0.05\u27 RMS) roll information from a motion sensor, and makes estimating sounding accuracy across the swath an interesting challenge. It is shown that good accuracy estimates can be obtained by collecting data on station under control of the GPS-aided dynamic positioning system usually available on most modern long-range oceanographic vessels. A number of motion sensors, with RMS roll accuracy specifications ranging from 0.05\u27 to 0.01\u27 ,were tested with the EM120 sonar on station in 3800 m to 4000 m water depths. Unexpectedly, they yielded roughly the same depth uncertainty as a function of receive beam angle. This result might be explained by synchronization errors between the attitude data and the sonar data leading to beam pointing errors, other types of beam pointing errors, a range of roll accuracy narrower than specified for the motion sensors, or a combination of these factor

State of the Art in Swath Bathymetry Survey Systems

In the last decade, advances in real-time computing and data storage capabilities have led to significant improvements in bathymetric survey systems and the single point echo-sounder has now been replaced by a variety of highresolution swath mapping sounding systems. This paper reviews the state of the art in the non-military swath bathymetry mapping systems. Such systems are typically multi narrow beam echo-sounders or interferometric side-looking sonars with swath width capabilities ranging from 0.75 to 7 times the water depth. The paper compares the design characteristics and the echo processing methods used in a number of these systems manufactured in Japan, Finland, Norway, the U.K., the U.S.A. and West Germany

Sidescan Sonar Image Enchancement Using a Decomposition Based on Orthogonal Functions. Applications with Chebyshev Polynomials

A method is presented to remove from sidescan sonar images of the seafloor, artifacts that are clearly unrelated to the backscattering properties of the seafloor. A spectral analysis performed on a ping by ping basis proved to be well suited to the problem. The technique relies on a decomposition using Chebyshev polynomials. This stochastic method does not require a priori knowledge of deterministic parameters. It deals with the low spatial frequency components of the image whose wavelengths are not very small compared to the swath width. Applications to sidescan sonar images obtained with the SeaMARC LI system are presented

Angular dependence of 12-kHz seafloor acoustic backscatter

The angular dependence of seafloor acoustic backscatter,measured with a 12‐kHz multi narrow‐beam echo‐sounder at two sites in the central North Pacific with water depths of 1500 and 3100 m, respectively, has been determined for incidence angles between 0° and 20°. The acoustic data consist of quadrature samples of the beamformed echoes received on each of the 16 2.66° beams of a Sea Beam echo‐sounder. These data are subjected to adaptive noise cancelling for sidelobe interference rejection, and the centroid of each echo is determined. After corrections for the ship’s roll and raybending effects through the water column, the angles of arrival are converted to angles of incidence by taking athwartships apparent bottom slopes into account. For each beam, the mean echo power received is normalized by the corresponding insonified area that depends on the transmit and receive beam patterns, the ship’s roll angle and the local bottom slope. For lack of system calibration, the data are presented as relative mean energy levels in 1° bins. Comparison of these results with theoretical angular dependence functions, based on the Helmholtz–Kirchhoff model for backscatter from a rough surface, indicates that a good fit is obtained in the angular sector from 5° to 20° incidence. In the near‐nadir sector (0° to 5°), the data suffer from high variance making the estimate unreliable. The data processing methods presented constitute one of the elements necessary to compile a map of seafloor acoustic backscatter from acoustic measurements made with a multinarrow beam echo‐sounder. The angular dependence function obtained will ultimately be used to normalize the backscattermeasurements in the athwartships direction

Application of a maximum likelihood processor to acoustic backscatter for the estimation of seafloor roughness parameters

Maximum likelihood (ML) estimation is used to extract seafloor roughness parameters from records of acoustic backscatter. The method relies on the Helmholtz–Kirchhoff approximation under the assumption of a power‐law roughness spectrum and on the statistical modeling of bottom reverberation. The result is a globally optimum, highly automated technique that is a useful tool in the context of seafloor classification via remote acoustic sensing. The general geometry of the Sea Beam bathymetric system is incorporated into the design of the ML processor in order to make it applicable to real acoustic data collected by this system. The processor is initially tested on simulated backscatter data and is shown to be very effective in estimating the seafloor parameters of interest. The simulated data are also used to study the effect of data averaging and normalization in the absence of system calibration information. The same estimation procedure is applied to real data collected over two central North Pacific seamounts, Horizon Guyot and Magellan Rise. The Horizon Guyot results are very close to estimates obtained through a curve‐fitting procedure presented by de Moustier and Alexandrou [J. Acoust. Soc. Am. 90, 522–531 (1991)]. In the case of Magellan Rise, discrepancies are observed between the results of ML estimation and curve fitting

Time dependent seafloor acoustic backscatter (10-100kHz)

A time-dependent model of the acoustic intensity backscattered by the seafloor is described and compared with data from a calibrated, vertically oriented, echo-sounder operating at 33 and 93 kHz. The model incorporates the characteristics of the echo-sounder and transmitted pulse, and the water column spreading and absorption losses. Scattering from the water–sediment interface is predicted using Helmholtz–Kirchhoff theory, parametrized by the mean grain size, the coherent reflection coefficient, and the strength and exponent of a power-law roughness spectrum. The composite roughness approach of Jackson et al. [J. Acoust. Soc. Am. 79, 1410–1422 (1986)], modified for the finite duration of the transmitted signal, is used to predict backscatter from subbottom inhomogeneities. It depends on the sediment’s volume scattering and attenuation coefficients, as well as the interface characteristics governing sound transmission into the sediment. Estimation of model parameters (mean grain size, roughness spectrum strength and exponent, volume scattering coefficient) reveals ambiguous ranges for the two spectral components. Analyses of model outputs and of physical measurements reported in the literature yield practical constraints on roughness spectrum parameter settings appropriate for echo-envelope-based sediment classification procedures

Remote sensing of sediment characteristics by optimized echo-envelope matching

A sediment geoacoustic parameter estimation technique is described which compares bottom returns, measured by a calibrated monostatic sonar oriented within 15° of vertical and having a 10°–21° beamwidth, with an echo envelope model based on high-frequency (10–100 kHz) incoherent backscattertheory and sediment properties such as: mean grain size, strength, and exponent of the power law characterizing the interface roughness energy density spectrum, and volume scattering coefficient. An average echo envelope matching procedure iterates on the reflection coefficient to match the peak echo amplitude and separate coarse from fine-grain sediments, followed by a global optimization using a combination of simulated annealing and downhill simplex searches over mean grain size, interface roughness spectral strength, and sediment volume scattering coefficient. Error analyses using Monte Carlo simulations validate this optimization procedure. Moderate frequencies (33 kHz) and orientations normal with the interface are best suited for this application. Distinction between sands and fine-grain sediments is demonstrated based on acoustic estimation of mean grain size alone. The creation of feature vectors from estimates of mean grain size and interface roughness spectral strength shows promise for intraclass separation of silt and clay. The correlation between estimated parameters is consistent with what is observed in situ

Near bottom sediment characterization offshore SW San Clemente Island

Normal incidence, 23.5 kHz seafloor acoustic backscatter data and bottom video were measured with the Deep Tow instrument package of the Scripps Institution of Oceanography in 100 meter water depth south of San Clemente Island, CA. The collected data were processed using an echo envelopesediment characterization method, to derive geoacoustic parameters such as particle mean grain size and the strength of the power law characterizing the roughness energy density spectrum of thesediment-water interface. Two regions, sand and silt, were selected based on available ground truth, perceived along-track sediment homogeneity, data quality and tow fish stability. Distinction between sand and fine grain sediments can be accomplished by creation of feature vectors comprised of mean grain size (MΦ) and interface roughness spectral strength (w2). Estimates for mean grain size and roughness spectral strength (MΦ, w2) were (1.5, 0.0095) for sand, and (6.7, 0.0033) for silt, where MΦ is expressed in PHI units, and w2 has units cm4. These results are consistent with local ground truth measurements and illustrate the potential of this sediment characterization method in survey mode

Variable Bandwidth Filter for Multibeam Echo-sounding Bottom Detection

The accuracy of a seafloor map derived from multibeam swath bathymetry depends first and foremost on the quality of the bottom detection process that yields estimates of the arrival time and angle of bottom echoes received in each beam. Filtering of each beam with a fixed bandwidth filter, with the bandwidth based on the length of the transmitted pulse, reduces the error associated with the time-angle estimates. However, filters of this type can not be optimal over the wide range of operational environments encountered. Better results are obtained with a processing scheme that varies the filter bandwidth across the swath width using detected time and angle information from the previous ping. This method is evaluated using sonar data obtained with a Reson SeaBat 8111ER and the results compared with those obtained using a fixed bandwidth filter