Remote estimation of surficial seafloor properties through the application Angular Range Analysis to multibeam sonar data

The variation of the backscatter strength with the angle of incidence is an intrinsic property of the seafloor, which can be used in methods for acoustic seafloor characterization. Although multibeam sonars acquire backscatter over a wide range of incidence angles, the angular information is normally neglected during standard backscatter processing and mosaicking. An approach called Angular Range Analysis has been developed to preserve the backscatter angular information, and use it for remote estimation of seafloor properties. Angular Range Analysis starts with the beam-by-beam time-series of acoustic backscatter provided by the multibeam sonar and then corrects the backscatter for seafloor slope, beam pattern, time varying and angle varying gains, and area of insonification. Subsequently a series of parameters are calculated from the stacking of consecutive time series over a spatial scale that approximates half of the swath width. Based on these calculated parameters and the inversion of an acoustic backscatter model, we estimate the acoustic impedance and the roughness of the insonified area on the seafloor. In the process of this inversion, the behavior of the model parameters is constrained by established inter-property relationships. The approach has been tested using a 300 kHz Simrad EM3000 multibeam sonar in Little Bay, NH. Impedance estimates are compared to in situ measurements of sound speed. The comparison shows a very good correlation, indicating the potential of this approach for robust seafloor characterization.     

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.     

Inhomogeneous substrate analysis using EM300 backscatter imagery

Backscatter reflectivity from multibeam echo-sounders provides a powerful tool to efficiently characterize seafloor substrates. A comprehensive EM300 bathymetric and backscatter survey has been completed of Cook Strait, in central New Zealand. This paper presents a detailed analysis of the realtime corrections applied to the raw EM300 multibeam data and additional corrections required to compute angular variations of the backscatter strength. The corrections, including the local absorption coefficient, the influence of seafloor topography and sound refraction in the water column, are determined for different Cook Strait seafloor substrates. Modifying MB-System software code, we extracted the backscatter signal parameters in order to quantify the raw backscatter strength and apply additional processing. Profiles of backscatter strength versus incidence angle were computed for a variety of sites characterized by flat seafloor and homogeneous substrates, and for which ground-truth data were available. For each homogeneous site, different but characteristic backscatter profiles are observed that can be interpreted in terms of sediment facies. To analyze heterogeneous substrates, we present a statistical technique, based on a 3-dimensional distribution of (incidence angle, backscatter strength) couples that preserves geological information of the substrate components. This analysis, using backscatter data acquired on a submarine volcano, north of New Zealand, clearly differentiates soft sediments and lava flows within a heterogeneous substrate.     

Multi-angle backscatter classification and sub-bottom profiling for improved seafloor characterization

This study applies three classification methods exploiting the angular dependence of acoustic seafloor backscatter along with high resolution sub-bottom profiling for seafloor sediment characterization in the Eckernförde Bay, Baltic Sea Germany. This area is well suited for acoustic backscatter studies due to its shallowness, its smooth bathymetry and the presence of a wide range of sediment types. Backscatter data were acquired using a Seabeam1180 (180 kHz) multibeam echosounder and sub-bottom profiler data were recorded using a SES-2000 parametric sonar transmitting 6 and 12 kHz. The high density of seafloor soundings allowed extracting backscatter layers for five beam angles over a large part of the surveyed area. A Bayesian probability method was employed for sediment classification based on the backscatter variability at a single incidence angle, whereas Maximum Likelihood Classification (MLC) and Principal Components Analysis (PCA) were applied to the multi-angle layers. The Bayesian approach was used for identifying the optimum number of acoustic classes because cluster validation is carried out prior to class assignment and class outputs are ordinal categorical values. The method is based on the principle that backscatter values from a single incidence angle express a normal distribution for a particular sediment type. The resulting Bayesian classes were well correlated to median grain sizes and the percentage of coarse material. The MLC method uses angular response information from five layers of training areas extracted from the Bayesian classification map. The subsequent PCA analysis is based on the transformation of these five layers into two principal components that comprise most of the data variability. These principal components were clustered in five classes after running an external cluster validation test. In general both methods MLC and PCA, separated the various sediment types effectively, showing good agreement (kappa >0.7) with the Bayesian approach which also correlates well with ground truth data (r²?>?0.7). In addition, sub-bottom data were used in conjunction with the Bayesian classification results to characterize acoustic classes with respect to their geological and stratigraphic interpretation. The joined interpretation of seafloor and sub-seafloor data sets proved to be an efficient approach for a better understanding of seafloor backscatter patchiness and to discriminate acoustically similar classes in different geological/bathymetric settings.     

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.     

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.     

Application of neural and statistical classifiers to the problem ofseafloor characterization

In this paper neural and statistical classifiers are applied to the problem of seafloor classification. The feature vectors used consist of acoustic backscatter as a function of angle of incidence. Simulated seafloor backscatter is obtained by employing the Helmholtz-Kirchhoff approximation and the statistical properties of bottom reverberation. These synthetic data are used initially to train multilayer perceptrons and then to test them for their ability to discriminate among signal returns produced by seafloors with different roughness parameters. The same data are also processed with optimum Bayesian classifiers. A comparison of the results indicates a suboptimum performance for the perceptrons. The same procedures are applied to real data collected by the Sea Beam bathymetric system over two Central North Pacific seamounts. In this case, the perceptron performance is similar to that of the statistical classifier, which is no longer optimum, since no prior knowledge of the probability distribution parameters is available. In addition, Self Organizing Maps are applied to both synthetic and real data and are shown to result in a successful separation of the output space into distinct regions corresponding to different seafloor classes     

Preference of echo features for classification of seafloor sediments using neural networks

Selection of a set of dominant echo features to classify seafloor sediments using a multilayer perceptron neural network is investigated at two acoustic frequencies (33 and 210 kHz). Several sets of inputs with different combinations of two, three, four, five, and six echo features are exploited with three-layer neural networks. The performances of the networks are analyzed to assess the most discriminating set of echo features for classification of seafloor sediments. The results of the overall average performances reveal that backscatter strength and time spread are the two most important echo features at 33 kHz, whereas backscatter strength has higher discriminating characteristics at 210 kHz for seafloor sediment classification. In addition, a set of four echo features consisting of backscatter strength, time-spread, statistical skewness, and Hausdroff dimension gives the highest success at both the acoustic frequencies.     

Effects of using inclined parametric echosounding on sub-bottom acoustic imaging and advances in buried object detection

This study reports an adaptation of a parametric echosounder system using 15 kHz as secondary frequency to investigate the angular response of sub-bottom backscatter strength of layered mud, providing a new method for enhanced acoustic detection of buried targets. Adaptions to achieve both vertical (0°) and non-vertical inclination (1–15°, 30°, 45° and 60°) comprise mechanical tilting of the acoustic transducer and electronic beam steering. Data were acquired at 18 m water depth at a study site characterized by a flat, muddy seafloor where a 0.1 m diameter power cable lies 1–2 m below the seafloor. Surveying the cable with vertical incidence revealed that the buried cable can hardly be discriminated against the backscatter strength of the layered mud. However, the backscatter strength of layered mud decreases strongly at >3±0.5° incidence and the layered mud echo pattern vanishes beyond 5°. As a consequence, the backscatter pattern of the buried cable is very pronounced in acoustic images gathered at 15°, 30°, 45° and 60° incidence. The size of the cable echo pattern increases linearly with incidence. These effects are attributed to reflection loss from layered mud at larger incidence and to the scattering of the 0.1 m diameter buried cable. Data analyses support the visual impression of superior detection of the cable with an up to 2.6-fold increase of the signal-to-noise ratio at 40° incidence compared to the vertical incidence case.     

Sea-floor classification using multibeam echo-sounding angular backscatter data: a real-time approach employing hybrid neural network architecture

The presently studied numerical model, e.g., composite roughness, is successful for the purpose of seafloor classification employing processed multibeam angular backscatter data from manganese-nodule-bearing locations of the Central Indian Ocean Basin. Hybrid artificial neural network (ANN) architecture, comprised of the self-organizing feature map and learning vector quantization (LVQ), has been implemented as an alternative technique for sea-floor roughness classification, giving comparative results with the aforesaid numerical model for processed multibeam angular backscatter data. However, the composite-roughness model approach is protracted due to the inherent need for processed data including system-gain corrections. In order to establish that tedious processing of raw backscatter values is unessential for efficient classification, hybrid ANN architecture has been attempted here due to its nonparametric approach. In this technical communication, successful employment of LVQ algorithm for unprocessed (raw) multibeam backscatter data indicates true real-time classification application.     

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     

High-Frequency Scattered Envelope Statistics of Patchy Seafloors

The scattering properties of the individual components of seafloors consisting of discrete patches of different materials may have a complicated relationship in terms of their angular response and/or frequency dependence. Consequently, this relationship directly influences the angular and frequency response of scattered envelope probability density functions (pdfs). In this paper, the influence of the relative scattering strength of seafloor patches on scattered envelope statistics will be explored through both a modified form of a recently developed model [Abraham and Lyons, IEEE J. Ocean. Eng., vol. 27, pp. 800-813, 2002] and analysis of experimental data collected off Elba Island, Italy, in May 2003, by the NATO Undersea Research Centre, La Spezia, Italy. Qualitative comparisons of the $K$-distribution shape parameter $(alpha)$ between that predicted by the model and that measured from data display promising similarities such as the inverse relationship between $alpha$ and bandwidth, the relative difference in values of $alpha$ for the various seafloor types studied, and the dependence on grazing angle. The favorable model/data comparisons show that it is possible to link the scattered envelope distribution to measurable geoacoustic properties, providing the foundation necessary for solving several important problems related to the detection of targets in non-Rayleigh clutter including performance prediction for different systems based on seafloor properties, extrapolation of performance to other system/bandwidths, and optimization of system parameters such as bandwidth to local environment.      

Seafloor multibeam backscatter calibration experiment: comparing 45°-tilted 38-kHz split-beam echosounder and 30-kHz multibeam data

Obtaining absolute seafloor backscatter measurements from hydrographic multibeam echosounders is yet to be achieved. We propose a low-cost experiment to calibrate the various acquisition modes of a 30-kHz Kongsberg EM 302 multibeam echosounder in a range of water depths. We use a 38-kHz Simrad EK60 calibrated fisheries split-beam echosounder mounted at 45° angle on the vessel’s hull as a reference for the calibration. The processing to extract seafloor backscatter from the EK60 requires bottom detection, ray tracing and motion compensation to obtain acceptable geo-referenced backscatter measurements from this non-hydrographic system. Our experiment was run in Cook Strait, New Zealand, on well-known seafloor patches in shallow, mid, and deep-water depths. Despite acquisition issues due to weather, our results demonstrate the strong potential of such an approach to obtain system’s absolute calibration which is required for quantitative use of backscatter strength data.     

Shallow-water imaging multibeam sonars: A new tool for investigating seafloor processes in the coastal zone and on the continental shelf

Hydrographic quality bathymetry and quantitative acoustic backscatter data are now being acquired in shallow water on a routine basis using high frequency multibeam sonars. The data provided by these systems produce hitherto unobtainable information about geomorphology and seafloor geologic processes in the coastal zone and on the continental shelf.Before one can use the multibeam data for hydrography or quantitative acoustic backscatter studies, however, it is essential to be able to correct for systematic errors in the data. For bathymetric data, artifacts common to deep-water systems (roll, refraction, positioning) need to be corrected. In addition, the potentially far greater effects of tides, heave, vessel lift/squat, antenna motion and internal time delays become of increasing importance in shallower water. Such artifacts now cause greater errors in hydrographic data quality than bottom detection. Many of these artifacts are a result of imperfect motion sensing, however, new methods such as differential GPS hold great potential for resolving such limitations. For backscatter data, while the system response is well characterised, significant post processing is required to remove residual effects of imaging geometry, gain adjustments and water column effects. With the removal of these system artifacts and the establishment of a calibrated test site in intertidal regions (where the seabed may be intimately examined by eye) one can build up a sediment classification scheme for routine regional seafloor identification.When properly processed, high frequency multibeam sonar data can provide a view of seafloor geology and geomorphology at resolutions of as little as a few decimetres. Specific applications include quantitative estimation of sediment transport rates in large-scale sediment waves, volume effects of iceberg scouring, extent and style of seafloor mass-wasting and delineation of structural trends in bedrock. In addition, the imagery potentially provides a means of quantitative classification of seafloor lithology, allowing sedimentologists the ability to examine spatial distributions of seabed sediment type without resorting to subjective estimation or prohibitively expensive bottom-sampling programs. Using Simrad EM100 and EM1000 sonars as an example, this paper illustrates the nature and scale of possible artifacts, the necessary post-processing steps and shows specific applications of these sonars.     

Stochastic modeling of seafloor morphology; Resolution oftopographic parameters by sea beam data

The authors explore the resolving power of an inversion algorithm which estimates five parameters of the seafloor covariance function from a single swath of multibeam echosounding data. The resolving power is evaluated as a function of the swath length, the orientation of ship track with respect to topographic grain, and the response width of the sounding system. The analysis is conducted by inverting sets of synthetic data with known statistics. The mean and standard deviation of the inverted parameters can be directly compared with the input parameters and the standard errors output from the inversion. Experiments show that resolution of the covariance parameters is strongly dependent on the number of characteristic lengths which are sampled. Root-mean-square seafloor height can be estimated to within ~15%, and anisotropic orientation to within ~5% (for a strong lineation), using track lengths as short as three characteristic lengths     

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.     

Characterizing Indian Ocean manganese nodule-bearing seafloor using multi-beam angular backscatter

Application of quantitative angular backscatter modelling to manganese nodule-bearing areas of the Central Indian Ocean Basin (CIOB) has been initiated at NIO during the year 1998. Studies were aimed to establish the suitability of seafloor backscattering in delineating seafloor parameters characteristic of nodule-rich sediments. In this paper, processed Hydrosweep multi-beam backscatter data from 45 spot locations in the CIOB (where nodule samples are available) were analysed to estimate seafloor and sediment volume roughness parameters. The application of a composite roughness model to a nodule-bearing region (6,600 km²) of the CIOB, to determine seafloor interface roughness parameters from a multi-beam backscatter dataset, shows only four power law sets. The results attest 80% of the nodule-bearing seafloor to be smooth in terms of interface roughness parameters at micro-topographic level. The sediment volume roughness parameters are dominant only in 29% of the smooth interface roughness sites. This indicates that 51% of the seafloor area possesses negligible (interface and volume) roughness. A critical analysis using pseudo-side-scan records from 12 selected locations in the study area affirms the combined importance of the seafloor interface and sediment volume roughness parameters for precise determination of manganese nodule abundance.