Automatic segmentation of gas plumes from multibeam water column images using a U-shape network

Cold seeps are widely developed on the seabed of continental margins and can form gas plumes due to the upward migration of methane-rich fluids.The detection and automatic segmentation of gas plumes are of great significance in locating and studying the cold seep system that is usually accompanied by hydrate layers in the subsurface.A multibeam echo-sounder system(MBES)can record the complete backscatter intensity of the water column,and it is one of the most effective means for detecting cold seeps.However,the gas plumes recorded in multibeam water column images(WCI)are usually blurred due to the interference of the complicated water environment and the sidelobes of the MBES,making it difficult to obtain the effective segmentation.Therefore,based on the existing UNet semantic segmentation network,this paper proposes an AP-UNet network combining the convolutional block attention module and the pyramid pooling module for the automatic segmentation and extraction of gas plumes.Comparative experiments are conducted among three traditional segmentation methods and two deep learning methods.The results show that the AP-UNet segmentation model can effectively suppress complicated water column noise interference.The segmentation precision,the Dice coefficient,and the recall rate of this model are 92.09%,92.00%,and 92.49%,respectively,which are 1.17%,2.10%,and 2.07%higher than the results of the UNet.

Multibeam water column data research in the Taixinan Basin:Implications for the potential occurrence of natural gas hydrate

A multi beam sonar survey is carried out in the continental slope of the Taixinan Basin to obtain submarine topographic and water column data. The data are processed to obtain water column images. Anomalous water column images, displaying plume characteristics, are found in gas hydrate enriched areas in the Taixinan Basin.This indicates the presence of natural gas resources in the Taixinan Basin. The multibeam sonar system is shown to provide an accurate and effective approach for detecting sub-sea gas hydrate.

Correction for Depth Biases to Shallow Water Multibeam Bathymetric Data

Vertical errors often present in multibeam swath bathymetric data. They are mainly sourced by sound refraction, internal wave disturbance, imperfect tide correction, transducer mounting, long period heave, static draft change, dynamic squat and dynamic motion residuals, etc. Although they can be partly removed or reduced by specific algorithms, the synthesized depth biases are unavoidable and sometimes have an important influence on high precise utilization of the final bathymetric data. In order to. confidently identify the decimeter-level changes in seabed morphology by MBES, we must remove or weaken depth biases and improve the precision of multibeam bathymetry further. The fixed-interval profiles that are perpendicular to the vessel track are generated to adjust depth biases between swaths. We present a kind of postprocessing method to minimize the depth biases by the histogram of cumulative depth biases. The datum line in each profile can be obtained by the maximum value of histogram. The corrections of depth biases can be calculated according to the datum line. And then the quality of final bathymetry can be improved by the corrections. The method is verified by a field test.

Determination of Precise Instantaneous Height at Multibeam Transducer

To overcome the shortcomings of the traditional multibeam survey and data processing, a new method is presented for the precise determination of the instantaneous height at the multibeam transducer by the blend of GPS height and heave signals. Before signal blend, GPS height and heave signals need to be corrected first to the transducer center by attitude correction. Second, the GPS height needs to be checked and modified by heave check and modification itself. Butterworth and FFT （fast Fourier transformation） were used in the signal blend. Finally, FFT is thought to be appropriate in signal processing. The new method efficiently overcomes the shortcomings of the traditional method, and this is proven well by the MBS （multibeam bathymetric system） experiment.

Data Fusion Technique for Multibeam Echosoundings

On the basis of an analysis of the error sources in multibeam echosounding system,a data processing method for compensating systematic errors in multibeam survey is proposed.In order to improve the accuracy of overall swath,a data fusion technique using single beam survey data as control information for single beam and multibeam echosounding is then presented.Some questions involved in solving the adjustment problem,such as its feasibility and the numerical stability,are discussed in detail,and a two_step adjustment method is suggested.Finally,a practical survey data set is used as a case study to prove the efficiency and reliability of the proposed methods.

Design and Implementation of An Active Multibeam Antenna System with 64 RF Channels and 256 Antenna Elements for Massive MIMO Application in 5G Wireless Communications

This paper focuses on the design and implementation of an active multibeam antenna system for massive MIMO applications in 5G wireless communications.The highly integrated active multibeam antenna system is designed and implemented at 5.8 GHz with 64 RF Channels and 256 antenna elements.The 64-channel highly integrated active multibeam antenna system provides a verification platform for digital beamforming algorithm and massive MIMO channel estimation for next generation wireless communications.

Development of Method in Precise Multibeam Acoustic Bathymetry

The sound ray tracing method can achieve higher accuracy in determining depths and plan positions with multibeam echo sounding system. In data processing, actual sound speed profile must be used in the method. However, the method is too complicated. In order to overcome the shortcoming, this paper presents a new method, the position correction method. Two situations are considered in the new method, namely, change of sound velocity keeps constant gradient in whole water column (including N layers) or in different water layer.

Underwater Terrain-Aided Navigation Based on Multibeam Bathymetric Sonar Images

Underwater terrain-aided navigation is used to complement the traditional inertial navigation employed by autonomous underwater vehicles during lengthy missions. It can provide fixed estimations by matching real-time depth data with a digital terrain map, This study presents the concept of using image processing techniques in the underwater terrain matching process. A traditional gray-scale histogram of an image is enriched by incorporation with spatial information in pixels. Edge comer pixels are then defined and used to construct an edge comer histogram, which employs as a template to scan the digital terrain map and estimate the fixes of the vehicle by searching the correlation peak. Simulations are performed to investigate the robustness of the proposed method, particularly in relation to its sensitivity to background noise, the scale of real-time images, and the travel direction of the vehicle. At an image resolution of 1 m2/pixel, the accuracy of localization is more than 10 meters.

Fuzzy ARTMAP neural network for seafloor classification from multibeam sonar data

This paper presents a seafloor classification method of multibeam sonar data, based on the use of Adaptive Resonance Theory （ART） neural networks. A general ART-based neural network, Fuzzy ARTMAP, has been proposed for seafloor classification of multibeam sonar data. An evolutionary strategy was used to generate new training samples near the cluster boundaries of the neural network, therefore the weights can be revised and refined by supervised learning. The proposed method resolves the training problem for Fuzzy ARTMAP neural networks, which are applied to seafloor classification of multibeam sonar data when there are less than adequate ground-troth samples. The results were synthetically analyzed in comparison with the standard Fuzzy ARTMAP network and a conventional Bayesian classifier. The conclusion can be drawn that Fuzzy ARTMAP neural networks combining with GA algorithms can be alternative powerful tools for seafloor classification of multibeam sonar data.

Seafloor Sediment Classification Based on Multibeam Sonar Data

The multibeam sonars can provide hydrographic quality depth data as well as hold the potential to provide calibrated measurements of the seafloor acoustic backscattering strength. There has been much interest in utilizing backscatters and images from multibeam sonar for seabed type identification and most results are obtained. This paper has presented a focused review of several main methods and recent developments of seafloor classification utilizing multibeam sonar data or/and images. These are including the power spectral analysis methods, the texture analysis, traditional Bayesian classification theory and the most active neural network approaches.

AMP Dual-Turbo Iterative Detection and Decoding for LDPC Coded Multibeam MSC Uplink

The uplink of mobile satellite communication(MSC) system with hundreds of spot beams is essentially a multiple-input multiple-output(MIMO) channel. Dual-turbo iterative detection and decoding as a kind of MIMO receiver, which exchanges soft extrinsic information between a soft-in soft-out(SISO) detector and an SISO decoder in an iterative fashion, is an efficient method to reduce the uplink inter-beam-interference(IBI),and so the receiving bit error rate(BER).We propose to replace the linear SISO detector of traditional dual-turbo iterative detection and decoding with the AMP detector for the low-density parity-check(LDPC) coded multibeam MSC uplink. This improvement can reduce the computational complexity and achieve much lower BER.

High-resolution bottom detection algorithm for a multibeam echo-sounder system with a U-shaped array

High-resolution approaches such as multiple signal classification and estimation of signal parameters via rotational invariance techniques（ESPRIT） are currently employed widely in multibeam echo-sounder（MBES）systems for sea floor bathymetry,where a uniform line array is also required.However,due to the requirements in terms of the system coverage/resolution and installation space constraints,an MBES system usually employs a receiving array with a special shape,which means that high-resolution algorithms cannot be applied directly.In addition,the short-term stationary echo signals make it difficult to estimate the covariance matrix required by the high-resolution approaches,which further increases the complexity when applying the high-resolution algorithms in the MBES systems.The ESPRIT with multiple-angle subarray beamforming is employed to reduce the requirements in terms of the signal-to-noise ratio,number of snapshots,and computational effort.The simulations show that the new processing method can provide better fine-structure resolution.Then a highresolution bottom detection（HRBD） algorithm is developed by combining the new processing method with virtual array transformation.The application of the HRBD algorithm to a U-shaped array is also discuss.The computer simulations and experimental data processing results verify the effectiveness of the proposed algorithm.

Automatic calibration for wobble errors in shallow water multibeam bathymetries

The wobble errors caused by the imperfect integration of motion sensors and transducers in multibeam echo-sounder systems(MBES)manifest as high-frequency wobbles in swaths and hinder the accurate expression of high-resolution seabed micro-topography under a dynamic marine environment.There are many types of wobble errors with certain coupling among them.However,those current calibration methods ignore the coupling and are mainly manual adjustments.Therefore,we proposed an automatic calibration method with the coupling.First,given the independence of the transmitter and the receiver,the traditional georeferenced model is modified to improve the accuracy of footprint reduction.Secondly,based on the improved georeferenced model,the calibration model associated with motion scale,time delay,yaw misalignment,lever arm errors,and soundings is constructed.Finally,the genetic algorithm(GA)is used to search dynamically for the optimal estimation of the corresponding error parameters to realize the automatic calibration of wobble errors.The simulated data show that the accuracy of the calibrated data can be controlled within 0.2%of the water depth.The measured data show that after calibration,the maximum standard deviation of the depth is reduced by about 5.9%,and the mean standard deviation of the depth is reduced by about 11.2%.The proposed method has significance in the precise calibration of dynamic errors in shallow water multibeam bathymetrie s.

Real-time programmable coding metasurface antenna for multibeam switching and scanning

Novel electromagnetic wave modulation by programmable dynamic metasurface promotes the device design freedom,while multibeam antennas have sparked tremendous interest in wireless communications.A programmable coding antenna based on active metasurface elements(AMSEs)is proposed in this study,allowing scanning and state switching of multiple beams in real time.To obtain the planar array phase distribution in quick response,the aperture field superposition and discretization procedures are investigated.Without the need for a massive algorithm or elaborate design,this electronically controlled antenna with integrated radiation and phase-shift functions can flexibly manipulate the scattering state of multiple beams under field-programmable gate array(FPGA)control.Simulation and experimental results show that the multiple directional beams dynamically generated in the metasurface upper half space have good radiation performance,with the main lobe directions closely matching the predesigned angles.This metasurface antenna has great potential for future applications in multitarget radar,satellite navigation,and reconfigurable intelligent metasurfaces.

Multibeam Raman amplification of a finite-duration seed in a short distance

A new scheme of multibeam Raman amplification(MRA)is proposed in virtue of the collective mode by sharing a common scattered light.Multiple laser beams can provide a higher growth rate,but the overlapping region limits the amplification length.We suggest to use a finite-duration seed to facilitate MRA in a short distance.Through two-dimensional particle-in-cell simulations,we find that two-beam Raman amplification has a much higher growth rate than that of singlebeam one.This growth rate depends on the initial seed amplitude,electron temperature,and seed duration.An empirical criterion,γ0τc=1,whereγ0 is the theoretical growth rate of MRA,is used to choose a proper duration for a higher growth rate.After a total amplification length of 320µm,the two-beam Raman amplification shows nonlinear features of pulse compression and a bow-shape wave front,indicating that the amplification has finally entered the self-similar regime.

Application of modified multiple subarrays detection method to multibeam bathymetry system

Either amplitude based methods or phase based methods are usually used in multibeam bathymetry system and chosen in practical measurement by ad hoc criteria. The errors of the detection are often caused by choosing wrong detection method. In this paper a modified multiple subarrays amplitude-phase united detection method is proposed , which uses both the amplitude and phase of echo from bottom.This new method not only realizes the super-wide swath coverage, but also improves the detection performance by using the phase differences among subarrays in place of phases of subarrays to estimate the phase slope image. Experimental results are also analyzed and discussed to demonstrate the effectivity of the proposed approach.

A Method for the Removal of Ray Refraction Effects in Multibeam Echo Sounder Systems

To a multibeam echo sounder system (MBES), under water sound refraction plays an important role in depth measure- ment accuracy, and errors in sound velocity profile lead to inaccuracies in the measured depth (especially for outer beams). A method is developed to estimate the sound velocity profile based on the depth measured by vertical beam. Using this depth and other pa- rameters, such as t (sound pulse propagation time), θ (beam inclination angle), etc. We can estimate a simple sound velocity profile with which the depth error has been reduced. This method has been tested with a real dataset acquired in the East China Sea.

Channel Correlation Based User Grouping Algorithm for Nonlinear Precoding Satellite Communication System

Low Earth Orbit(LEO)multibeam satellites will be widely used in the next generation of satellite communication systems,whose inter-beam interference will inevitably limit the performance of the whole system.Nonlinear precoding such as Tomlinson-Harashima precoding(THP)algorithm has been proved to be a promising technology to solve this problem,which has smaller noise amplification effect compared with linear precoding.However,the similarity of different user channels(defined as channel correlation)will degrade the performance of THP algorithm.In this paper,we qualitatively analyze the inter-beam interference in the whole process of LEO satellite over a specific coverage area,and the impact of channel correlation on Signal-to-Noise Ratio(SNR)of receivers when THP is applied.One user grouping algorithm is proposed based on the analysis of channel correlation,which could decrease the number of users with high channel correlation in each precoding group,thus improve the performance of THP.Furthermore,our algorithm is designed under the premise of co-frequency deployment and orthogonal frequency division multiplexing(OFDM),which leads to more users under severe inter-beam interference compared to the existing research on geostationary orbit satellites broadcasting systems.Simulation results show that the proposed user grouping algorithm possesses higher channel capacity and better bit error rate(BER)performance in high SNR conditions relative to existing works.

A VGGNet-based correction for satellite altimetry-derived gravity anomalies to improve the accuracy of bathymetry to depths of 6500 m

Understanding the topographic patterns of the seafloor is a very important part of understanding our planet.Although the science involved in bathymetric surveying has advanced much over the decades,less than 20%of the seafloor has been precisely modeled to date,and there is an urgent need to improve the accuracy and reduce the uncertainty of underwater survey data.In this study,we introduce a pretrained visual geometry group network(VGGNet)method based on deep learning.To apply this method,we input gravity anomaly data derived from ship measurements and satellite altimetry into the model and correct the latter,which has a larger spatial coverage,based on the former,which is considered the true value and is more accurate.After obtaining the corrected high-precision gravity model,it is inverted to the corresponding bathymetric model by applying the gravity-depth correlation.We choose four data pairs collected from different environments,i.e.,the Southern Ocean,Pacific Ocean,Atlantic Ocean and Caribbean Sea,to evaluate the topographic correction results of the model.The experiments show that the coefficient of determination(R~2)reaches 0.834 among the results of the four experimental groups,signifying a high correlation.The standard deviation and normalized root mean square error are also evaluated,and the accuracy of their performance improved by up to 24.2%compared with similar research done in recent years.The evaluation of the R^(2) values at different water depths shows that our model can achieve performance results above 0.90 at certain water depths and can also significantly improve results from mid-water depths when compared to previous research.Finally,the bathymetry corrected by our model is able to show an accuracy improvement level of more than 21%within 1%of the total water depths,which is sufficient to prove that the VGGNet-based method has the ability to perform a gravity-bathymetry correction and achieve outstanding results.

An improved algorithm based on equivalent sound velocity profile method at large incident angle

With the development of ultra-wide coverage technology,multibeam echo-sounder(MBES)system has put forward higher requirements for localization accuracy and computational efficiency of ray tracing method.The classical equivalent sound speed profile(ESSP)method replaces the measured sound velocity profile(SVP)with a simple constant gradient SVP,reducing the computational workload of beam positioning.However,in deep-sea environment,the depth measurement error of this method rapidly increases from the central beam to the edge beam.By analyzing the positioning error of the ESSP method at edge beam,it is discovered that the positioning error increases monotonically with the incident angle,and the relationship between them could be expressed by polynomial function.Therefore,an error correction algorithm based on polynomial fitting is obtained.The simulation experiment conducted on an inclined seafloor shows that the proposed algorithm exhibits comparable efficiency to the original ESSP method,while significantly improving bathymetry accuracy by nearly eight times in the edge beam.