Monthly variation in the fat content of anchovy (Engraulis japonicus) in the Yellow Sea: implications for acoustic abundance estimation

Anchovy is a key species in the Yellow Sea ecosystem. An accurate estimate of anchovy abundance is vital for the management of the anchovy stock and measurement of the ecosystem response to changes in anchovy abundance. However, the acoustic fish abundance estimate may be biased by 30%-40% if the fat-content induced target strength variation is not taken into account. We measured the monthly variation in the fat content of anchovy (Engraulis japonicus) in the Yellow Sea, and evaluated the potential effect of variation in fat content on the acoustic assessment of anchovy abundance. The fat content of anchovy varied seasonally, with two maxima and two minima in a year. The highest fat content (14.75%) was measured in the pre-spawning period in May, and the lowest fat content (2.48%) was measured during the post-spawning period in October. Fat content appeared to correlate with water content, but not body size. Assuming that the target strength is decreased by 0.2dB for every 1% increase in fat content, the seasonal difference in the target strength of anchovy may be as high as 2.45 dB. Given this, the acoustic abundance estimate may be biased by between 43% and 76%. Our results highlight the need for more information on the changes in fat content of fishes whose abundance is estimated by acoustic surveys.

Acoustic estimation of suspended sediment concentration

In this paper, the acoustic estimation of suspended sediment concentration is discussed and two estimation methods of suspended sediment concentration are presented. The first method is curve fitting method, in which, according to the acoustic backscattering theory we assume that the fit-ting factor K1 (r) between the concentration M(r) obtained by acoustic observation and the concentra-tion M0(r) obtained by sampling water is a high order power function of distance r. Using least-square algorithm, we can determine the coefficients of the high order power function by minimizing the differ-ence between M(r) and M0(r) in the whole water profile. To the absorption coefficient of sound due to the suspension in water we do not give constraint in the first method. The second method is recur-sive fitting method, in which we take M0(r) as the conditions of initialization and decision and give ra-tional constraints to some parameters. The recursive process is stable. We analyzed the two methods with a lot of experimental data. The analytical results show that the estimate error of the first method is less than that of the second method and the latter can not only estimate the concentration of suspended sediment but also give the absorption coefficient of sound. Good results have been obtained with the two methods.

Research on underwater acoustic channel estimation and temperature factors based on FBMC

The complexity of underwater environment poses a challenge to underwater acoustic communication.In marine environment,different temperatures,depths and salinities would affect the performance of acoustic communication.The analysis of the underwater acoustic channel under the influence of temperature factors provides a reference for further study of the underwater acoustic channel estimation problem based on filter bank multi-carrier(FBMC).The FBMC based offset quadrature amplitude modulation(OQAM)technology(FBMC/OQAM)was introduced into the underwater acoustic communication.Based on FBMC,the underwater acoustic channel estimation technology was studied.By changing the pilot structure to adapt to the complex and variable underwater acoustic channel,the iterative method was used to obtain the channel information with higher accuracy and further improve the performance of channel estimation.Theoretical analysis and simulation results show that iterative channel estimation algorithm based on the new interference approximation method(IAM)pilot proposed in this paper has better performance in underwater acoustic channel.

Power Estimation of Acoustic Sources by Sensor Array Processing

A constant problem is to localize a number of acoustic sources, to separate their individual signals and to estimate their strengths in a propagation medium. An acoustic receiving array with signal processing algorithms is then used. The most widely used algorithm is the conventional beamforming algorithm but it has a very low resolution and high sidelobes that may cause a signal leakage problem. Several new signal processors for arrays of sensors are derived to evaluate the strengths of acoustic signals arriving at an array of sensors. In particular, we present the covariance vector estimator and the pseudoinverse of the array manifold matrix estimator. The covariance vector estimator uses only the correlations between sensors and the pseudoinverse of the array manifold matrix estimator operates with the minimum eigenvalues of the covariance matrix. Numerical and experimental results are presented.

Study on the simulation of acoustic logging measurements in horizontal and deviated wells

The conventional acoustic logging interpretation method, which is based on vertical wells that penetrate isotropic formations, is not suitable for horizontal and deviated wells penetrating anisotropic formations. This unsuitability is because during horizontal and deviated well drilling, cuttings will splash on the well wall or fall into the borehole bottom and form a thin bed of cuttings. In addition, the high velocity layers at different depths and intrinsic anisotropy may affect acoustic logging measurements. In this study, we examine how these factors affect the acoustic wave slowness measured in horizontal and deviated wells that are surrounded by an anisotropic medium using numerical simulation. We use the staggered-grid finite difference method in time domain （FDTD） combined with hybrid-PML. First, we acquire the acoustic slowness using a simulated array logging system, and then, we analyze how various factors affect acoustic slowness measurements and the differences between the effects of these factors. The factors considered are high-velocity layers, thin beds of cuttings, dipping angle, formation thickness, and anisotropy. The simulation results show that these factors affect acoustic wave slowness measurements differently. We observe that when the wavelength is much smaller than the distance between the borehole wall and high velocity layer, the true slowness of the formation could be acquired. When the wavelengths are of the same order （i.e., in the near-field scenarios）, the geometrical acoustics theory is no longer applicable. Furthermore, when a thin bed of cuttings exists at the bottom of the borehole, Fermat＇s principle is still applicable, and true slowness can be acquired. In anisotropic formations, the measured slowness changes with increments in the dipping angle. Finally, for a measurement system with specific spacing, the slowness of a thin target layer can be acquired when the distance covered by the logging tool is sufficiently long. Based on systematical simulations with different dipping angles and anisotropy in homogenous TI media, slowness estimation charts are established to quantitatively determine the slowness at any dipping angle and for any value of the anisotropic ratio. Synthetic examples with different acoustic logging tools and different elastic parameters demonstrate that the acoustic slowness estimation method can be conveniently applied to horizontal and deviated wells in TI formations with high accuracy.

An Improved Underwater Acoustic Network Localization Algorithm

Underwater sensor network can achieve the unmanned environmental monitoring and military monitoring missions.Underwater acoustic sensor node cannot rely on the GPS to position itself,and the traditional indirect positioning methods used in Ad Hoc networks are not fully applicable to the localization of underwater acoustic sensor networks.In this paper,we introduce an improved underwater acoustic network localization algorithm.The algorithm processes the raw data before localization calculation to enhance the tolerance of random noise.We reduce the redundancy of the calculation results by using a more accurate basic algorithm and an adjusted calculation strategy.The improved algorithm is more suitable for the underwater acoustic sensor network positioning.

Carrier frequency offset and impulse noise estimation for underwater acoustic orthogonal frequency division multiplexing

The carrier frequency offset（CFO）and impulse noise always affect the performance of underwater acoustic communication_systems.The CFO and impulse noise could be estimated by using the null subcarriers to cancel the effects of the two types of interference.The null subcarriers estimation methods include optimal separate estimation and joint estimation.The separate estimation firstly estimates the CFO value and then estimates the impulse noise value.However,the CFO and impulse noise always affect each other when either of them is estimated separately.The performance could be improved by using the joint estimation.The results of simulations and experiments have showed that these two optimization methods have good performance and the joint estimation has better performance than the separate estimation method.There is 3 dB performance gain at the BER value of 10^（-2）when using the joint estimation method.Thus these methods could improve the system robustness by using the CFO compensation and impulse noise suppression.

Frame synchronization for underwater acoustic communication based on maximum likelihood estimation

Traditional frame synchronization methods for underwater acoustic communication(UWAC) merely depend on correlation coefficient when synchronization signal detection is concerned and,hence,false triggering and missed synchronization can hardly be avoided in complex UWAC channels.In order to solve this problem,firstly,we analyze the effects of interference from noise,multipath and Doppler on frame synchronization;then we propose a new frame synchronization scheme based on parameter estimation.By exploiting the parameter estimation technique,we detect the synchronization signal according to the estimated parameters,thus the false triggering rate and missed synchronization rate can be reduced.We also simplify the maximum likelihood estimation to reduce computational cost.Simulation results indicate that this new scheme outperforms the traditional method in terms of delay resolution and correlation coefficient.Both static and mobile communication experimental results show that the correlation coefficient of the new scheme is higher than that of the traditional one.Moreover,the detection ability of the receiver is improved,which helps to avoid false triggering and missed synchronization.

On fast estimation of direction of arrival for underwater acoustic target based on sparse Bayesian learning

The Direction of Arrival （DOA） estimation methods for underwater acoustic target using Temporally Multiple Sparse Bayesian Learning （TMSBL） as the reconstructing algorithm have the disadvantage of slow computing speed. To solve this problem, a fast underwater acoustic target direction of arrival estimation was proposed. Analyzing the model characteristics of block-sparse Bayesian learning framework for DOA estimation, an algorithm was proposed to obtain the value of core hyper-parameter through MacKay＇s fixed-point method to estimate the DOA. By this process, it will spend less time for computation and provide more superior recovery performance than TMSBL algorithm. Simulation results verified the feasibility and effectiveness of the proposed algorithm.

Passive tracking and size estimation of volume target based on acoustic vector intensity

The special sections of volume target are observed with acoustic vector intensity according to the difference among their radiated-noise characteristics, then three sections are tracked with Kalman filtering, and target size is estimated. Simulation results indicate that in ideal condition three sections of a ship can be tracked and ship's size can be estimated even though one of three sections can not be observed.

Measurement and estimation of free field to eardrumtransfer function for virtual acoustic space research

Free field to Eardrum Thansfer Function (FETF) is one of the major factors influencing the identification of the sound source direction. FETF can be employed to generate a Virtual Acoustic Space (VAS) by computer and other equlpment. In this paper the methods to improve the measurement and estimation of FETF are approached. Least-mean-squares (LMS)method is much better than empirical FFT method. This paper also gives a sample description of excitation signals for measuring the impulse response of FETF.