由垂直入射脉冲和海底回波反演海底声参数

浅海海底声参数是影响声场传播的重要参量。文中根据信号的相位特性对反演稳定性的影响进行了数值模拟;并于2002年8月在黄海海区进行了海底声参数反演实验。利用垂直入射脉冲和海底回波数据进行海底声参数反演,由于海底回波信号随穿透深度增加而导致回波信号的信噪比降低,为了有效地增加海底声阻抗反演深度,提出平滑分段抽取冲激响应,重建声阻抗剖面的方法。结合Hamilton经验公式,分离海底声速、密度,反演结果与海底采样样本分析值、经验值吻合较好。     

基于时域自适应搜索法的典型海温垂直结构声特征提取研究

针对层剥算法从海水声回波记录中反演海温垂直结构特征的不稳定问题,利用自适应搜索算法ASM(Adaptive searching method),从声回波记录中提取海温垂直结构的稳定冲激响应,然后利用层剥算法对所得冲激响应进行反演,得到海温垂直结构的声特征,结果表明,该方法可以较好地解决层剥算法反演的不稳定性问题。     

黄海水温垂直剖面的遥感反演与数值预报模型

基于黄海水温垂直剖面分层结构统计分析,建立了一个卫星遥感SST反演水温垂直剖面的参数化模式,以该模式反演数据作为一维数值预报模式的初值,同时用大气预报场资料作为预报模式的过程资料,发展了一个以卫星遥感资料作为主要输入量的黄海水温垂直剖面的数值预报模型.模型实现了利用卫星遥感资料反演预报黄海水温垂直剖面的目的,5 d时效的预报效果明显优于已往强温跃层数值预报模式.     

黄海冷水团声层析监测数值模拟

海洋冷水团是海洋学家关注多年的问题 ,其监测方法亟待解决。本文将简正波波数层析法用于冷水团监测 ,并对简正波波数层析用于反演黄海冷水团声速剖面进行了数值模拟。数值模拟结果表明 ,简正波波数层析可以用于反演平均声速剖面 ,特别在监测与距离有关海洋环境的声速结构方面大有潜力。     

基于EMD算法的海洋内波参数反演

利用合成孔径雷达(SAR)图像研究海洋内波具有其他遥感探测及实地海洋测量不可替代的优势,然而从SAR数据中提取内波参数的方法却往往由于人工选取的位置不同使得反演的内波参数产生不同的偏差,为了尽量避免人工操作带来的误差并有效反演内波参数,文中提出了一种SAR图像海洋内波波向与波长参数估计的新方法。通过人工选取内波前导线上的3个位置点,计算机自动地获取内波的位置和内波的波向,提取内波断面,在此基础上利用EMD算法反演内波波长,结合内波区域海水密度剖面数据,进一步反演内波振幅参数。通过对实测SAR图像数据进行处理的结果可知,采用该方法对内波SAR图像进行处理,能很好地定位内波位置并获得传播方向及内波波长参数,结合海水密度剖面,实现了内波振幅参数反演。人工干预选取3个位置点,自动计算内波前导线弯曲弧度并自动计算5个内波剖面,减少了由于人工干预操作不同形成的偏差。     

日本九州大学佐佐木裕博士来海洋学院讲学

1987年12月,日本九州大学工学部资源工学科佐佐木裕博士来我院讲学,内容为: 1.偶极剖面和四极剖面的电阻率二维反演。 2.大地电磁的二维反演。 3.电阻率和大地电磁的联合反演。 4.电阻率反演在地热调查中的应用。来自全国21个单位的学者及研究生听取了有关报告。从他的报告中,学员们学到了由佐佐木博士首创的广义最小二乘法进行联合反演的方法,对国内正在开展的研究工作有重要意义。     

针对C波段组网SAR卫星的风场优化反演方法研究

地球物理模型函数是一种常被用于同极化合成孔径雷达(synthetic aperture radar,SAR)的风场反演方法.在使用该方法提取SAR数据的风速时,需要将风向作为输入信息,这导致反演风速的精度受风向精度的影响,且使SAR风场反演无法独立完成.为了解决这些问题,通过数值模拟获取仿真的组网SAR卫星数据,3颗S...     

经验模态与小波分解在光学遥感内波参数提取中的应用

内波遥感参数提取是利用遥感影像研究海洋内波的重要手段,通过提取内波的基本参数可以对海洋内波的生成与传播机制进行进一步的研究。提出了利用经验模态分解、小波分解与高阶多项式拟合从光学影像中提取内波半波宽度的方法。经验模态分解与小波分解对内波剖面数据进行尺度分解,根据归一化方差最大来提取内波分量;多项式拟合基于内波剖面的亮暗条纹变化完全由内波调制的假设,对数据进行拟合,并根据一阶导数来提取半波宽度。用南海北部东沙岛附近2004年7月10日的中-巴资源卫星(China-Brazil Earth Resources Satellite,CBERS)影像对方法进行了验证。结果表明,3种方法能较好地提取所需参数,获取的内波半波宽度具有较好的一致性;上述方法在处理非平稳及非线性遥感数据上,具有非常明显的优势。基于一维非线性内波理论,通过提取的内波半波宽度,辅以水深和混合层深度数据,反演了内波的振幅。     

基于浅地层剖面数据和改进地声模型的底质反演方法

浅地层剖面仪发射的声脉冲能够穿透海底面进入沉积层内部,其回波中携带了丰富的底质信息。地声模型是底质声学与物理性质关系的数学描述,广泛用于海底声学与地声反演研究。本文通过对浅地层剖面数据的处理、解译得到海底反射系数,与考虑底质松密影响的改进Biot-Stoll模型相结合,提出底质反演新方法并开展实例验证。研究结果表明：通过对浅地层剖面原始记录的读取、解译,提取反射波振幅,并结合设备声源级,可有效求取海底反射系数。通过引入相对密度改进孔隙度计算公式,进而在基于Biot-Stoll模型构建海底反射系数和底质平均粒径关系过程中进一步考虑了底质松密的影响。基于山东威海某海域及文献的算例均显示,本文提出的改进地声模型可缩小底质反演与实测结果之间的相对误差、提升基于浅地层剖面数据的海底底质地声反演精度。     

基于VMD对SAR海洋内波参数的自动反演

经验模态分解(empirical mode decomposition,简称EMD)是反演海洋内波参数的有效方法之一,但由于EMD存在模态混叠等问题,对海洋内波进行参数反演时会产生一定误差。相比较于EMD,变分模态分解(variational mode decomposition,简称VMD)能够有效地抑制模态混叠现象。为了更好地对海洋内波进行参数反演,提出了一种基于VMD对合成孔径雷达(synthetic aperture radar,简称SAR)遥感图像中的内波参数进行自动反演的方法。该方法先对SAR图像进行Canny处理,获取图像中的内波条纹信息,再根据内波传播方向自动选取灰度剖面;然后利用集合经验模态分解(ensemble empirical mode decomposition,简称EEMD)信号特征自适应分解模态函数的特点,再将分解得到的有效模态数作为VMD中参数K的参考值;最后利用VMD分解后的数据进行内波参数反演。试验结果表明:通过对Canny预处理后的条纹信息进行灰度剖面自动选取,解决了人为选取剖面所可能导致的误差;通过对剖面信号进行VMD处理不仅解决了EMD模态混叠的问题,成功地反演出内波的前导波振幅,而且所反演的结果与EEMD反演参数以及实测资料数据吻合得很好。     

Reflection response for normal incidence probing of vertically nonhomogeneous media

A time domain synthetic reflection seismogram is detailed and, as a limiting condition on this model, the analytic reflection impulse response for a one-dimensional lossless acoustic medium with piecewise continuous acoustic impedance is obtained. This analytic impulse response solution, in the structure of a sum of terms by order of reflection, provides insight to some of the poorly understood aspects of acoustic reflections from stratified and smoothly varying media as may be encountered in shallow marine sediments and elsewhere. It offers as well an approach for the inverse problem of extracting acoustic impedance profiles from reflection response data, though other effects (such as wavefront spreading, dispersive and absorptive attenuation, and wavelet broadening attendant with pulse propagation through a medium) need to be accommodated.     

An inverse method for reconstructing the density and sound speed profiles of a layered ocean bottom

A standard inverse problem in underwater acoustics is the reconstruction of the ocean subbottom structure (e.g., the density and sound speed profiles) from an aperture- and bandlimited knowledge of the reflection coefficient. In this paper we describe an inverse solution method due to Candel et al. [12] which is based on the scattering of acoustic plane waves by a one-dimensional inhomogeneous medium. As a consequence of applying the forward scattering approximation to a local wave representation of the acoustic field, they obtain an expression for the reflection coefficient in the form of a nonlinear Fourier transform of the logarithmic derivative of the local admittance. Inversion of this integral transform enables the recovery of the admittance profile via the numerical integration of two first-order differential equations which require as reflection data a single impulse response of the medium. Separate recovery of both the density and sound speed profiles requires two impulse responses for two different grazing angles. In this case, four differential equations need to be integrated instead of two. To illustrate the capability of the method, we present numerical reconstructions which are based on synthetic reflection data for a geoacoustic model that represents the acoustic properties of the surficial sediments for a site in the Hatteras Abyssal Plain.     

Experimental Verification of Acoustic Impedance Inversion

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Analysis of shallow-water experimental acoustic data including acomparison with a broad-band normal-mode-propagation model

Channel temporal variability, resulting from fluctuations in oceanographic parameters, is an important issue for reliable communications in shallow-water-long-range acoustic propagation. As part of an acoustic model validation exercise, audio-band acoustic data and oceanographic data were collected from shallow waters off the West Coast of Scotland. These data have been analyzed for temporal effects. The average impulse response for this channel has been compared with simulations using a fast broad-band normal-mode propagation model. In this paper, we also introduce a novel technique for estimating and removing the bistatic reverberation contribution from the data. As propagation models do not necessarily account for reverberation, it has to be extracted from the signals when comparing measured and modeled transmission loss     

Strategies for waveform processing in sparker data

A sparker is a marine seismic impulsive source used for high-resolution seismic surveys. Sparker sources were very popular during the late 1960s and 1970s before being supplanted by small volume airguns. However, in the last 10 years there has been renewed interest in sparker technology because (1) it can be easily deployed at relatively low costs and (2) in certain areas the use of small airguns is restricted for environmental purposes. In this study a sparker source was used to assess the seismic stratigraphy of Quaternary deposits and to image the sediment/bedrock interface. Three different inverse filtering methods were tested (i.e., spiking deconvolution, match-filtering and vertical seismic profile (VSP) deconvolution) to correct the poor shot-to-shot repeatability of the source and to compress its reverberations. Results show that the matched-filter and VSP deconvolution methods, which design and apply one operator for each shot, produced comparable results, whereas the spiking deconvolution that used the same operator on all traces failed to compress the source signature properly.     

Blind marine seismic deconvolution using statistical MCMC methods

In order to improve the resolution of seismic images, a blind deconvolution of seismic traces is necessary, since the source wavelet is not known and cannot be considered as a stationary signal. The reflectivity sequence is modeled as a Gaussian mixture, depending on three parameters (high and low reflector variances and reflector density), on the wavelet impulse response, and on the observation noise variance. These parameters are unknown and must be estimated from the recorded trace, which is the reflectivity convolved with the wavelet, plus noise. Two methods are compared in this paper for the parameter estimation. Since we are considering an incomplete data problem, we first consider maximum likelihood estimation by means of a stochastic expectation maximization (SEM) method. Alternatively, proper prior distributions can be specified for all unknown quantities. Then, a Bayesian strategy is applied, based on a Monte Carlo Markov Chain (MCMC) method. Having estimated the parameters, one can proceed to the deconvolution. A maximum posterior mode (MPM) criterion is optimized by means of an MCMC method. The deconvolution capability of these procedures is checked first on synthetic signals and then on the seismic data of the IFREMER ESSR4 campaign, where the wavelet duration blurs the reflectivity, and on the SMAVH high-resolution marine seismic data.     

Assessment of acoustic iterative inverse method for bubble sizing to experimental data

Comparative study was carried out for an acoustic iterative inverse method to estimate bubble size distributions in water. Conventional bubble sizing methods consider only sound attenuation for sizing. Choi and Yoon [IEEE, 26(1), 125–130 (2001)] reported an acoustic iterative inverse method, which extracts the sound speed component from the measured sound attenuation. It can more accurately estimate the bubble size distributions in water than do the conventional methods. The estimation results of acoustic iterative inverse method were compared with other experimental data. The experimental data show good agreement with the estimation from the acoustic iterative inverse method. This iterative technique can be utilized for bubble sizing in the ocean.     

Correlation-based decision-feedback equalizer for underwater acoustic communications

The purpose of this paper is to develop a decision-feedback equalizer (DFE) using a fixed set of parameters applicable to most shallow oceans with minimal user supervision (i.e., a turn key system). This work is motivated by the superior performance [bit error rate (BER)] of the multichannel DFE compared with other methods, such as passive-phase conjugation (PPC), at the same time noting its sensitivity to different acoustic environments. The approach is to couple PPC, utilizing its adaptability to different environments, with a single-channel DFE. This coupling forms an optimal processor for acoustic communications in theory, but it has never been implemented in practice. By coupling with DFE, the method achieves the same spatial diversity as conventional multichannel DFE, without requiring a large number of receivers as does PPC. The correlation-based DFE in terms of the autocorrelation functions of the channel impulse responses summed over the receiver channels (the Q function) is derived. This paper shows in terms of waveguide physics, further supported by real data, the many desirable features of the Q function that suggest, given adequate sampling of the water column, a general applicability of the correlation-based equalizer to different environments, irrespective of the sound speed profiles, bottom properties, and source-receiver ranges/depths. This property can be expected to hold approximately for a small number of receivers with spatial diversity. This paper demonstrates the robustness of the new equalizer with moving source data despite the range change (which modifies the impulse response) and symbol phase change due to time-varying Doppler.     

Measurement of sound-speed gradients in deep-ocean sediments usingl_{1}deconvolution techniques

A method is described for measuring the sound speed and the sound-speed gradient of surficial sea floor sediment from bottom-reflected signals recorded in marine seismic experiments. The technique makes use of the ocean-bottom impulse responses that are deconvolved from the data by means of a novel curve-fitting algorithm based on thel_{1}norm (least absolute value) criterion. The algorithm constructs the impulse response by extracting spikes one at a time in a manner that causes thel_{1}error to decrease by the maximum amount possible as each spike is chosen. Thel_{1}curve-fitting approach is a completely general strategy for deconvolution, and our algorithm can be used with data obtained from any type of marine seismic source. Since our experiments have been carried out with small explosive charges, we have also developed a method for estimating the bubble-pulse wavelet directly from the recorded bottom-reflected signal. In this paper, thel_{1}algorithm is used to deconvolve impulse responses for data obtained in an experiment in the Alaskan Abyssal Plain. The sediment-sound-speed gradient determined from these results is typical of other values reported for turbidite abyssal plains where the surficial sediments are composed of unconsolidated silty deposits.     

Adaptive second-order Volterra filtering and its application tosecond-order drift phenomena

This paper presents an adaptive second-order Volterra filter and its application to model-test data of a prototype tension leg platform (TLP). The least-squares approach of a second-order Volterra model and its adaptive filtering algorithm based on recursive least-squares are introduced. The second-order Volterra filter is applied to identify the linear and quadratically nonlinear relationship between irregular sea wave excitation and the surge response of a tension leg platform. Next, a deconvolution technique, based on the impulse invariance standard Z-transform, is utilized to recover the linear and quadratic forces exerted on the TLP