Simultaneous operation of the Sea Beam multibeam echo-sounder andthe SeaMARC II bathymetric sidescan sonar system

An experiment aboard the Scripps Institution of Oceanography's RV Thomas Washington has demonstrated the seafloor mapping advantages to be derived from combining the high-resolution bathymetry of a multibeam echo-sounder with the sidescan acoustic imaging plus wide-swath bathymetry of a shallow-towed bathymetric sidescan sonar. To a void acoustic interference between the ship's 12-kHz Sea Beam multibeam echo-sounder and the 11-12-kHz SeaMARC II bathymetric sidescan sonar system during simultaneous operations, Sea Beam transmit cycles were scheduled around SeaMARC II timing events with a sound source synchronization unit originally developed for concurrent single-channel seismic, Sea Beam, and 3.5-kHz profile operations. The scheduling algorithm implemented for Sea Beam plus SeaMARC II operations is discussed, and the initial results showing their combined seafloor mapping capabilities are presented     

Quantitative backscatter measurements with a long-range side-scansonar

It is shown that useful relative backscatter strengths can be calculated from GLORIA long-range side-scan sonar data using a simple acoustic model. The calculation was performed on GLORIA side-scan sonar data collected during 1987 in the southern Indian Ocean. GEOSECS hydrographic information was used to access the effects of refraction (ray bending and aspherical spreading signal losses). Sea Beam bathymetry was used to correct the effective insonified area and compute the grazing angle. A major difficulty in performing this calculation over the terrain chosen (mid-ocean ridge topography) was one of adjusting navigation so that small features in Sea Beam and GLORIA data matched. Preliminary results show a 10-dB falloff in backscatter strength with decreasing grazing angle (10°-40°) at 6.5 kHz over what must presumably be a rough surface (extruded basalts and breccias)     

A SeaMARC II survey of recent submarine volcanism near Easter Island

SeaMARC II side-scan sonar data reveal that a large area of seafloor north and west of Easter Island has been disrupted by recent submarine volcanism. A large volcanic area begins approximately 60 km WNW of the island and extends for over 130 km to the west. The volcanic field is characterized by high backscatter intensity in the side-scan sonar records and is elevated 400–1000 m above the N-S seafloor fabric that surrounds it. This field, the Abu Volcanic Field, covers at least 2500 km² and appears to consist of recent lava flows and small volcanoes. Backscatter intensity of the Abu Volcanic Field is similar to that of the adjacent ridge flank which is less than 0.4 Ma, suggesting a similar age for its formation. Two additional areas of high backscatter immediately north of Easter Island cover a combined area of over 300 km². The sidescan sonar records show that these features are clearly of volcanic origin and are not debris flows from the nearby island. The flows are nearly 300 m thick and are morphologically similar to subaerial pahoehoe lava shields. Their high backscatter indicates that they are also the products of relatively recent submarine volcanic activity. The presence of these large areas of recent volcanism in the vicinity of Easter Island has important implications for the various models that have been proposed to explain the origin of the Easter Seamount Chain. In addition, the similar ages of Easter Island and the Easter Microplate suggest that the presence of a hotspot near or beneath this fast-spreading portion of the East Pacific Rise about 4.5 m.y. ago may have initiated the large-scale rift propagation that created the microplate.     

Gas seepage, pockmarks and mud volcanoes in the near shore of SW Taiwan

In order to understand gas hydrate related seafloor features in the near shore area off SW Taiwan, a deep-towed sidescan sonar and sub-bottom profiler survey was conducted in 2007. Three profiles of high-resolution sub-bottom profiler reveal the existence of five gas seeps (G96, GS1, GS2, GS3 and GS4) and one pockmark (PM) in the study area. Gas seeps and pockmark PM are shown in lines A and C, while no gas venting feature is observed along line B. This is the first time that a gas-hydrate related pockmark structure has been imaged off SW Taiwan. The relatively high backscatter intensity in our sidescan sonar images indicates the existence of authigenic carbonates or chemosynthetic communities on the seafloor. More than 2,000 seafloor photos obtained by a deep-towed camera (TowCam) system confirm the relatively high backscatter intensity of sidescan sonar images related to bacteria mats and authigenic carbonates formation at gas seep G96 and pockmark PM areas. Water column gas flares are observed in sidescan sonar images along lines A and C. Likewise, EK500 echo sounder images display the gas plumes above gas seep G96, pockmark PM and gas seep GS1; the gas plumes heights reach about 150, 100 and 20 m from seafloor, respectively. Based on multichannel seismic reflection (MCS) profiles, an anticline structure trending NNE-SSW is found beneath gas seep G96, pockmark PM and gas seep GS2. It implies that the gas venting features are related to the anticline structure. A thermal fluid may migrate from the anticline structure to the ridge crest, then rises up to the seafloor along faults or fissures. The seafloor characteristics indicate that the gas seep G96 area may be in a transitional stage from the first to second stage of a gas seep self-sealing process, while the pockmark PM area is from the second to final stage. In the pockmark PM area, gas venting is observed at eastern flank but not at the bottom while authigenic carbonates are present underneath the pockmark. It implies that the fluid migration pathways could have been clogged by carbonates at the bottom and the current pathway has shifted to the eastern flank of the pockmark during the gas seep self-sealing process.     

Processing of high-frequency multibeam echo sounder data for seafloor characterization

Processing simultaneous bathymetry and backscatter data, multibeam echosounders (MBESs) show promising abilities for remote seafloor characterization. High-frequency MBESs provide a good horizontal resolution, making it possible to distinguish fine details at the water-seafloor interface. However, in order to accurately measure the seafloor influence on the backscattered energy, the recorded sonar data must first be processed and cleared of various artifacts generated by the sonar system itself. Such a preprocessing correction procedure along with the assessment of its validity limits is presented and applied to a 95-kHz MBES (Simrad EM 1000) data set. Beam pattern effects, uneven array sensitivities, and inaccurate normalization of the ensonified area are removed to make possible further quantitative analysis of the corrected backscatter images. Unlike low-frequency data where the average backscattered energy proves to be the only relevant feature for discriminating the nature of the seafloor, high-frequency MBES backscatter images exhibit visible texture patterns. This additional information involves different statistical distributions of the backscattered amplitudes obtained from various seafloor types. Non-Rayleigh statistics such as K-distributions are shown to fit correctly the skewed distributions of experimental high-frequency data. Apart from the effect of the seafloor micro-roughness, a statistical model makes clear a correlation between the amplitude statistical distributions and the signal incidence angle made available by MBES bathymetric abilities. Moreover, the model enhances the effect of the first derivative of the seafloor backscattering strength upon statistical distributions near the nadir and at high incidence angles. The whole correction and analysis process is finally applied to a Simrad EM 1000 data set.     

Postprocessing and corrections of bathymetry derived from sidescansonar systems: application with SeaMARC II

A procedure for postprocessing bathymetry data provided by a phase-measuring sidescan sonar system is presented. The data were collected with the SeaMARC II system, and are generally characterized by a high level of noise and uneven spatial sampling. Before any spatial filtering is applied, data are selected to remove most of the obvious artifacts and to retain instantaneous depth profiles whose slant ranges increase monotonically from a central location to the edges of the swath. An extrapolation scheme, patterned after a potential field, is proposed to fill gaps in the coverage or to extend the bathymetric swath to that of the corresponding sidescan image when regridding the data to a rectangular frame. To fill the near nadir gap typically found in these data, a specific interpolation methodology is developed that takes into account the slant range of the first bottom return as received by the sidescan sonar itself or by a shipboard echo-sounder. Spatial low-pass filtering is applied through convolutions with parabolic windows whose width is proportional to the footprint of the acoustic beam along track and roughly 1/8 of the swath width across track. Mismatches of contour lines between adjacent tracks are reduced through a statistical method design to correct systematic profile errors     

High-resolution seafloor mapping using the DSL-120 sonar system: Quantitative assessment of sidescan and phase-bathymetry data from the Lucky Strike segment of the Mid-Atlantic Ridge

High-resolution, side-looking sonar data collected near the seafloor (100 m altitude) provide important structural and topographic information for defining the geological history and current tectonic framework of seafloor terrains. DSL-120 kHz sonar data collected in the rift valley of the Lucky Strike segment of the Mid-Atlantic Ridge near 37° N provide the ability to quantitatively assess the effective resolution limits of both the sidescan imagery and the computed phase-bathymetry of this sonar system. While the theoretical, vertical and horizontal pixel resolutions of the DSL-120 system are <1 m, statistical analysis of DSL-120 sonar data collected from the Lucky Strike segment indicates that the effective spatial resolution of features is 1–2 m for sidescan imagery and 4 m for phase-bathymetry in the seafloor terrain of the Mid-Atlantic Ridge rift valley. Comparison of multibeam bathymetry data collected at the sea-surface with deep-tow DSL-120 bathymetry indicates that depth differences are on the order of the resolution of the multibeam system (10–30 m). Much of this residual can be accounted for by navigational mismatches and the higher resolving ability of the DSL-120 data, which has a bathymetric footprint on the seafloor that is 20 times smaller than that of hull-mounted multibeam at these seafloor depths (2000 m). Comparison of DSL-120 bathymetry with itself on crossing lines indicates that residual depth values are ±20 m, with much of that variation being accounted for by navigational errors. A DSL-120 survey conducted in 1998 on the Juan de Fuca Ridge with better navigation and less complex seafloor terrain had residual depth values half those of the Lucky Strike survey. The quality of the bathymetry data varies as a function of position within the swath, with poorer data directly beneath the tow vehicle and also towards the swath edges.Variations in sidescan amplitude observed across the rift valley and on Lucky Strike Seamount correlate well with changes in seafloor roughness caused by transitions from sedimented seafloor to bare rock outcrops. Distinct changes in sonar backscatter amplitude were also observed between areas covered with hydrothermal pavement that grade into lava flows and the collapsed surface of the lava lake in the summit depression of Lucky Strike Seamount. Small features on the seafloor, including volcanic constructional features (e.g., small cones, haystacks, fissures and collapse features) and hydrothermal vent chimneys or mounds taller than 2 m and greater than 9 m² in surface area, can easily be resolved and mapped using this system. These features at Lucky Strike have been confirmed visually using the submersible Alvin, the remotely operated vehicle Jason, and the towed optical/acoustic mapping system Argo II.     

Swath bathymetry with GLORIA

For many years, GLORIA has been producing sonar images of the deep ocean floor. In the mid-1980's, the SeaMARC II system came to prominence producing depth values as well as sonar images. The basic method compares the phases of the signals returning from the seafloor to two rows of transducers. The phase differences are converted into angles of arrival and together with the arrival times converted into range and depth values. This capability has now been added to the GLORIA system. The fact that GLORIA uses a 2s FM pulse means the backscattered reverberation can come from a strip of seafloor up to 1.5 km wide. To accommodate this, overlapping complex FFT's are used to produce a time-frequency matrix for the returning signals. In this matrix, a constant range feature appears as a diagonal. Phases are then calculated using a least-mean-squares estimate along diagonals. The main source of error and bias is due to surface reflection, and this is taken into account. The GLORIA swath bathymetry system was tested on two cruises and it was possible to produce depth contours with a good level of confidence. The total swath width was over eight water depths and would have been greater with a more favorable velocity profile. Comparison with other bathymetry data (such as multibeam systems) showed excellent correlation, having a standard deviation of only 4% of total water depth     

Constrained iterative deconvolution applied to SeaMARC I sidescansonar imagery

Images collected by any sidescan sonar system represent the convolution of the acoustic beam pattern of the instrument with the true echo amplitude distribution over the seafloor. At typical low speeds, the 1.7° beam width of SeaMARC I (seafloor mapping and remote characterization) results in multiple insonification of individual targets, particularly at the outside of the swath. A nonlinearly constrained iterative deconvolution technique developed for radar applications can be applied to SeaMARC I imagery to reduce the effect of the beam pattern and equalize the spectral content of the image across the swath. Since the deconvolution is implemented in the along-track direction, the registration of individual scan lines must be precisely corrected before the operator is applied. The deconvolution operator must be modeled to account for beam shape, vehicle speed, swath width, slant range, and ping rate. The method is numerically stable and increases the effective resolution of the image, but results in some loss of dynamic range. The technique is applied to target recognition and imagery from volcanic terrains of the central Juan de Fuca Ridge     

基于回波时间的多波束测深与声纳数据匹配方法

以多波束精确的水深数据为参照源,采用原始回波时间对多波束测深数据与其同源声纳数据进行匹配,从而获得高精度和高分辨率的海底影像数据,并避免了传统声纳图像处理过程中斜距改正所带来的几何形变。匹配结果采用光照图输出,并与三维水深图、原始声纳图像和CARIS处理后的声纳图像进行比较分析。该方法有效地提高了多波束数据的利用率,增强了对海底地形的探测分辨率。     

Sidescan sonar image processing techniques

A four-step processing sequence is described to produce image mosaics from the various segments of a sidescanned acoustic imaging survey of a given seafloor area. Starting with data consisting for each ping of acoustic backscatter levels versus horizontal range across-track, median prefiltering is used first to reduce the influence of outliers on subsequent linear processes. Artifacts that are clearly unrelated to the backscattering properties of the seafloor are then isolated on a ping by ping basis through a spectral analysis that relies on a decomposition using Chebyshev polynomials to filter the low spatial frequency components of the image. Contrast enhancement is then achieved through an original implementation of the classical gray level histogram equalization technique by balancing local versus global histogram contributions. Pixels are mapped on a geographic grid taking due account of the geometry of the measurement and of the spacing between pings to minimize along-track smearing of features. Examples of results obtained with these processing techniques are given for SeaMARC II data recorded during a complete survey of Fieberling Guyot (32°.5 N, 128° W)     

Seafloor acoustic remote sensing with multibeam echo-sounders and bathymetric sidescan sonar systems

This paper examines the potential for remote classification of seafloor terrains using a combination of quantitative acoustic backscatter measurements and high resolution bathymetry derived from two classes of sonar systems currently used by the marine research community: multibeam echo-sounders and bathymetric sidescans sonar systems. The high-resolution bathymetry is important, not only to determine the topography of the area surveyed, but to provide accurate bottom slope corrections needed to convert the arrival angles of the seafloor echoes received by the sonars into true angles of incidence. An angular dependence of seafloor acoustic backscatter can then be derived for each region surveyed, making it possible to construct maps of acoustic backscattering strength in geographic coordinates over the areas of interest. Such maps, when combined with the high-resolution bathymetric maps normally compiled from the data output by the above sonar systems, could be very effective tools to quantify bottom types on a regional basis, and to develop automatic seafloor classification routines.     

Differential phase estimation with the SeaMARCII bathymetricsidescan sonar system

A maximum-likelihood estimator is used to extract differential phase measurements from noisy seafloor echoes received at pairs of transducers mounted on either side of the SeaMARC II bathymetric sidescan sonar system. Carrier frequencies for each side are about 1 kHz apart, and echoes from a transmitted pulse 2 ms long are analyzed. For each side, phase difference sequences are derived from the full complex data consisting of base-banded and digitized quadrature components of the received echoes. With less bias and a lower variance, this method is shown to be more efficient than a uniform mean estimator. It also does not exhibit the angular or time ambiguities commonly found in the histogram method used in the SeaMARC II system. A figure for the estimation uncertainty of the phase difference is presented, and results are obtained for both real and simulated data. Based on this error estimate and an empirical verification derived through coherent ping stacking, a single filter length of 100 ms is chosen for data processing applications     

多波束反向散射强度数据处理研究

在探讨多波束测深系统反向散射强度与海底底质类型的关系基础上,研究影响反向散射强度的各种因素,主要分析了海底地形起伏、中央波束区反射信号对反向散射强度的影响,并给出了消除这些影响的方法;将处理后的“纯”反向散射强度数据镶嵌生成海底声像图,为海底底质类型划分以及地貌解译提供了基础数据和辅助判读依据.     

Mapping marine habitats with high resolution sidescan sonar

The application of marine geophysics and GIS techniques to the characterization of benthic habitats has increased the ability of fisheries managers to assess distribution and habitat types beyond common practices. We report upon a 150 kHz sidescan sonar survey offshore of Kruzof Island, Alaska undertaken to characterize rockfish (Sebastes) habitat. Using GIS, MapGrafix and Map¹Factory we determined the percentage of seafloor cover that exists in our survey area. Bathymetry in the study area was determined with sidescan interferometry. All XYZ data were gridded using Surfer and plotted in shaded relief, bathymetric contour, and 3-dimensional formats. Contoured bathymetry was used as an over-lay in MapGrafix. Small sub-areas were extracted from the bathymetric data for closer study, and gridded in Surfer. Areas of the mosaic where backscatter patterns were not distinct were verified with hand samples and video collected with the submersible Delta. The use of submersibles for verification of interpreted lithologies and surface textures enables a high degree of accuracy for the interpretations. Lithotypes were lumped into larger groups based on morphology and fish associations with different morphologies verified using the submersible. The accuracy of digital maps from high-resolution sidescan sonar data allows a close quantification of the areal extents of these important features, directing the application of management strategies to critical areas.     

Processing and analysis of Simrad multibeam sonar data

The common approach to analysing data collected with multibeam and sidescan sonars is to visually interpret charts of contoured bathymetry and mosaics of seabed images. However, some of the information content is lost by processing the data into charts because this involves some averaging; the analysis might uncover more information if done on the data at an earlier stage in the processing. Motivated by this potential, I have created a software system which can be used to analyse data collected with Simrad EM1000 (shallow water) and EM12 (deep water) multibeam sonars, as well as to generate bathymetry contour charts and backscatter mosaics. The system includes data preprocessing, such as navigation filtering, depth filtering (removal of outlying values), and amplitude mapping using the multibeam bathymetry to correctly position image pixels across the swath. The data attributes that can be analysed include the orientation and slope of the seafloor, and the mean signal strength for each sounding. To determine bathymetry attributes such as slope, the soundings across a number of beams and across a series of pings are grouped and a least-squares plane fitted to them. Bathymetric curvature is obtained by detrending the grouped data using the least-squares plane and fitting a paraboloid to the residuals. The magnitudes and signs of the paraboloid's coefficients reveal depressions and hills and their orientations. Furthermore, the seafloor geology can be classified using a simple combination of these attributes. For example, flat-lying sediments can be classified where the backscatter, slope and curvature fall below specified values.     

Processing Multibeam Backscatter Data

A new highly precise source of data has recently become available using multibeam sonar systems in hydrography. Multibeam sonar systems can provide hydrographic quality depth data as well as high-resolution seafloor sonar images. We utilize the seafloor backscatter strength data of each beam from multibeam sonar and the automatic classification technology so that we can get the seafloor type identification maps. In this article, analyzing all kinds of error effects in backscatter strength, data are based on the relationship between backscatter strength and seafloor types. We emphasize particularly analyzing the influences of local bottom slope and near nadir reflection in backscatter strength data. We also give the correction algorithms and results of these two influent factors. After processing the raw backscatter strength data and correcting error effects, we can get processed backscatter strength data which reflect the features of seafloor types only. Applying the processed backscatter strength data and mosaicked seafloor sonar images, we engage in seafloor classification and geomorphy interpretation in future research.     

Processing Multibeam Backscatter Data

A new highly precise source of data has recently become available using multibeam sonar systems in hydrography. Multibeam sonar systems can provide hydrographic quality depth data as well as high-resolution seafloor sonar images. We utilize the seafloor backscatter strength data of each beam from multibeam sonar and the automatic classification technology so that we can get the seafloor type identification maps. In this article, analyzing all kinds of error effects in backscatter strength, data are based on the relationship between backscatter strength and seafloor types. We emphasize particularly analyzing the influences of local bottom slope and near nadir reflection in backscatter strength data. We also give the correction algorithms and results of these two influent factors. After processing the raw backscatter strength data and correcting error effects, we can get processed backscatter strength data which reflect the features of seafloor types only. Applying the processed backscatter strength data and mosaicked seafloor sonar images, we engage in seafloor classification and geomorphy interpretation in future research.