共查询到20条相似文献，搜索用时 972 毫秒
1.
Processing of high-frequency multibeam echo sounder data for seafloor characterization 总被引：9，自引：0，他引：9
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. 相似文献
2.
Inhomogeneous substrate analysis using EM300 backscatter imagery 总被引：2，自引：0，他引：2
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. 相似文献
3.
Multibeam echosounders (MBES) have become a widely used acoustic remote sensing tool to map and study the seafloor, providing co-located bathymetry and seafloor backscatter. Although the uncertainty associated with MBES-derived bathymetric data has been studied extensively, the question of backscatter uncertainty has been addressed only minimally and hinders the quantitative use of MBES seafloor backscatter. This paper explores approaches to identifying uncertainty sources associated with MBES-derived backscatter measurements. The major sources of uncertainty are catalogued and the magnitudes of their relative contributions to the backscatter uncertainty budget are evaluated. These major uncertainty sources include seafloor insonified area (1–3 dB), absorption coefficient (up to >?6 dB), random fluctuations in echo level (5.5 dB for a Rayleigh distribution), and sonar calibration (device dependent). The magnitudes of these uncertainty sources vary based on how these effects are compensated for during data acquisition and processing. Various cases (no compensation, partial compensation and full compensation) for seafloor insonified area, transmission losses and random fluctuations were modeled to estimate their uncertainties in different scenarios. Uncertainty related to the seafloor insonified area can be reduced significantly by accounting for seafloor slope during backscatter processing while transmission losses can be constrained by collecting full water column absorption coefficient profiles (temperature and salinity profiles). To reduce random fluctuations to below 1 dB, at least 20 samples are recommended to be used while computing mean values. The estimation of uncertainty in backscatter measurements is constrained by the fact that not all instrumental components are characterized and documented sufficiently for commercially available MBES. Further involvement from manufacturers in providing this essential information is critically required. 相似文献
4.
Evangelos Alevizos Mirjam Snellen Dick Simons Kerstin Siemes Jens Greinert 《Marine Geophysical Researches》2018,39(1-2):289-306
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. 相似文献
5.
Jess I. T. Hillman Geoffroy Lamarche Arne Pallentin Ingo A. Pecher Andrew R. Gorman Jens Schneider von Deimling 《Marine Geophysical Researches》2018,39(1-2):205-227
Using automated supervised segmentation of multibeam backscatter data to delineate seafloor substrates is a relatively novel technique. Low-frequency multibeam echosounders (MBES), such as the 12-kHz EM120, present particular difficulties since the signal can penetrate several metres into the seafloor, depending on substrate type. We present a case study illustrating how a non-targeted dataset may be used to derive information from multibeam backscatter data regarding distribution of substrate types. The results allow us to assess limitations associated with low frequency MBES where sub-bottom layering is present, and test the accuracy of automated supervised segmentation performed using SonarScope® software. This is done through comparison of predicted and observed substrate from backscatter facies-derived classes and substrate data, reinforced using quantitative statistical analysis based on a confusion matrix. We use sediment samples, video transects and sub-bottom profiles acquired on the Chatham Rise, east of New Zealand. Inferences on the substrate types are made using the Generic Seafloor Acoustic Backscatter (GSAB) model, and the extents of the backscatter classes are delineated by automated supervised segmentation. Correlating substrate data to backscatter classes revealed that backscatter amplitude may correspond to lithologies up to 4 m below the seafloor. Our results emphasise several issues related to substrate characterisation using backscatter classification, primarily because the GSAB model does not only relate to grain size and roughness properties of substrate, but also accounts for other parameters that influence backscatter. Better understanding these limitations allows us to derive first-order interpretations of sediment properties from automated supervised segmentation. 相似文献
6.
A procedure is suggested in which a relative calibration for the intensity output of a multibeam echo sounder (MBES) can be performed. This procedure identifies a common survey line (i.e., a standard line), over which acoustic backscatter from the seafloor is collected with multiple MBES systems or by the same system multiple times. A location on the standard line which exhibits temporal stability in its seafloor backscatter response is used to bring the intensity output of the multiple MBES systems to a common reference. This relative calibration procedure has utility for MBES users wishing to generate an aggregate seafloor backscatter mosaic using multiple systems, revisiting an area to detect changes in substrate type, and comparing substrate types in the same general area but with different systems or different system settings. The calibration procedure is demonstrated using three different MBES systems over 3 different years in New Castle, NH, USA. 相似文献
7.
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. 相似文献
8.
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. 相似文献
9.
10.
Processing Multibeam Backscatter Data 总被引：1，自引：0，他引：1
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. 相似文献
11.
User expectations for multibeam echo sounders backscatter strength data-looking back into the future
Vanessa Lucieer Marc Roche Koen Degrendele Mashkoor Malik Margaret Dolan Geoffroy Lamarche 《Marine Geophysical Researches》2018,39(1-2):23-40
With the ability of multibeam echo sounders (MBES) to measure backscatter strength (BS) as a function of true angle of insonification across the seafloor, came a new recognition of the potential of backscatter measurements to remotely characterize the properties of the seafloor. Advances in transducer design, digital electronics, signal processing capabilities, navigation, and graphic display devices, have improved the resolution and particularly the dynamic range available to sonar and processing software manufacturers. Alongside these improvements the expectations of what the data can deliver has also grown. In this paper, we identify these user-expectations and explore how MBES backscatter is utilized by different communities involved in marine seabed research at present, and the aspirations that these communities have for the data in the future. The results presented here are based on a user survey conducted by the GeoHab (Marine Geological and Biological Habitat Mapping) association. This paper summarises the different processing procedures employed to extract useful information from MBES backscatter data and the various intentions for which the user community collect the data. We show how a range of backscatter output products are generated from the different processing procedures, and how these results are taken up by different scientific disciplines, and also identify common constraints in handling MBES BS data. Finally, we outline our expectations for the future of this unique and important data source for seafloor mapping and characterisation. 相似文献
12.
In this study, the self-organizing map (SOM), which is an unsupervised clustering algorithm, and a supervised proportional learning vector quantization (PLVQ), are employed to develop a combined method of seafloor classification using multibeam sonar backscatter data. The PLVQ is a generalized learning vector quantization based on the proportional learning law (PLL). The proposed method was evaluated in an area where there are four types of sediments. The results show that the performance of the proposed method is better than the SOM and a statistical classification method. 相似文献
13.
In this study, the self-organizing map (SOM), which is an unsupervised clustering algorithm, and a supervised proportional learning vector quantization (PLVQ), are employed to develop a combined method of seafloor classification using multibeam sonar backscatter data. The PLVQ is a generalized learning vector quantization based on the proportional learning law (PLL). The proposed method was evaluated in an area where there are four types of sediments. The results show that the performance of the proposed method is better than the SOM and a statistical classification method. 相似文献
14.
A methodology for acoustic seafloor classification 总被引：3，自引：0，他引：3
A seafloor classification methodology, based on a parameterization of the reverberation probability density function in conjunction with neural network classifiers, is evaluated through computer simulations. Different seafloor provides are represented by a number of scatterer distributions exhibiting various degrees of departure from the nominal Poisson distribution. Using a computer simulation program, these distributions were insonified at different spatial scales by varying the transmitted pulse length. The statistical signature obtained consists of reverberation kurtosis estimates as a function of pulse length. Two neural network classifiers are presented with the task of discriminating among the various scatterer distributions based on obtained acoustic signatures. The results indicate that this approach offers considerable promise for practical, realizable solutions to the problem of remote seafloor classification 相似文献
15.
Chan Min Yoo Jongmin Joo Sang Hoon Lee Youngtak Ko Sang-Bum Chi Hyung Jeek Kim Inah Seo Kiseong Hyeong 《Ocean Science Journal》2018,53(2):381-394
A high level of confidence in resource data is a key prerequisite for conducting a reliable economic feasibility study in deep water seafloor mining. However, the acquisition of accurate resource data is difficult when employing traditional point-sampling methods to assess the resource potential of polymetallic nodules, given the vast size of the survey area and high spatial variability in nodule distribution. In this study, we analyzed high-resolution acoustic backscatter intensity images to estimate nodule abundance and increase confidence levels in nodule abundance data. We operated a 120 kHz deep-towed sidescan sonar (DSL-120) system (1×1 m resolution) across a 75 km2 representative area in the Korean Exploration Area for polymetallic nodules in the Northeastern Equatorial Pacific. A deep-towed camera system was also run along two tracks in the same area to estimate the abundance of polymetallic nodules on the seafloor. Backscatter data were classified into four facies based on intensity. The facies with the weakest and strongest backscatter intensities occurred in areas of high slope gradient and basement outcrops, respectively. The backscatter intensities of the two other facies correlated well with the nodule abundances estimated from still-camera images. A linear fit between backscatter intensity and mean nodule abundance for 10 zones in the study area yielded an excellent correlation (r2 = 0.97). This allowed us to compile a map of polymetallic nodule abundance that shows greater resolution than a map derived from the extrapolation of point-sampling data. Our preliminary analyses indicate that it is possible to greatly increase the confidence level of nodule resource data if the relationship between backscatter intensity and nodule abundance is reliably established. This approach has another key advantage over point sampling and image analyses in that detailed maps of mining obstacles along the seafloor are produced when acquiring data on the abundance of polymetallic nodules. The key limitation of this work is a poor correlation between nodule coverage, as observed from photographs, and nodule abundance. Significant additional ground truth sampling using well located box cores should be completed to determine whether or not there is a real correlation between the backscatter and abundance. 相似文献
16.
Remote estimation of surficial seafloor properties through the application Angular Range Analysis to multibeam sonar data 总被引：2，自引：2，他引：2
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. 相似文献
17.
18.
While the average seafloor backscatter strength within a narrow range of grazing angles can be used as a first-order classification tool, this technique often fails to distinguish seafloors of known differing geological character. In order to resolve such ambiguities, it is necessary to examine the variation in backscatter strength as a function of grazing angle. For this purpose, a series of multiply overlapping GLORIA sidescan sonar images (6.5 kHz) have been obtained in water depths ranging from 1000 to 2500 m. To constrain the placement of acoustic backscatter measurements and to measure the true impinging angle of the incident wave, the corresponding seafloor was simultaneously surveyed using the Seabeam multibeam system. As a result of the multiple overlap, the angular response of seafloor backscatter strength may be derived for regions much smaller than the swath width. By using the derived angular response of seafloor backscatter strength in regions for which sediment samples exist, an empirical seafloor classification scheme is proposed based on the shape, variance, and magnitude of the angular response. Because of the observed variability in the shape of the angular response with differing seafloor types, routine normalization of single-pass swath data to an equivalent single grazing angle image cannot be achieved. As a result, for the case of single-pass surveys, confident seafloor classification may only be possible for regions approaching the scale of the swath width 相似文献
19.
Luciano Fonseca Edson Mintsu Hung Arthur Ayres Neto Fábio José Guedes Magrani 《Marine Geophysical Researches》2018,39(1-2):139-149
A series of multibeam sonar surveys were conducted from 2009 to 2013 around Admiralty Bay, Shetland Islands, Antarctica. These surveys provided a detailed bathymetric model that helped understand and characterize the bottom geology of this remote area. Unfortunately, the acoustic backscatter records registered during these bathymetric surveys were heavily contaminated with noise and motion artifacts. These artifacts persisted in the backscatter records despite the fact that the proper acquisition geometry and the necessary offsets and delays were applied during the survey and in post-processing. These noisy backscatter records were very difficult to interpret and to correlate with gravity-core samples acquired in the same area. In order to address this issue, a directional notch-filter was applied to the backscatter waterfall in the along-track direction. The proposed filter provided better estimates for the backscatter strength of each sample by considerably reducing residual motion artifacts. The restoration of individual samples was possible since the waterfall frame of reference preserves the acquisition geometry. Then, a remote seafloor characterization procedure based on an acoustic model inversion was applied to the restored backscatter samples, generating remote estimates of acoustic impedance. These remote estimates were compared to Multi Sensor Core Logger measurements of acoustic impedance obtained from gravity core samples. The remote estimates and the Core Logger measurements of acoustic impedance were comparable when the shallow seafloor was homogeneous. The proposed waterfall notch-filtering approach can be applied to any sonar record, provided that we know the system ping-rate and sampling frequency. 相似文献