两种基于贝叶斯点估计理论的多声源定位方法研究

海洋环境参数失配是制约匹配场定位性能的主要因素之一。为了克服环境失配，本文基于贝叶斯理论，将环境参数与声源的距离和深度一起作为未知量进行反演。然而在进行多声源定位时，反演参数的维数几何增长，极大地增加了反演问题的复杂性和计算量。为此本文将声源强度和噪声方差表示成其极大似然估计值，从而将这些参数进行隐式采样，大大降低了反演的维数和难度。文章比较了两种贝叶斯点估计方法，最大后验概率密度方法和最大边缘后验概率密度方法。最大后验概率密度方法的解是令后验概率密度取得最大值的参数组合，可以利用优化算法快速获得。最大边缘后验概率密度法将其他参数积分，得到目标参数的一维边缘概率分布，分布的最大值为反演结果。该方法得到最优估计值的同时可以获取参数估计的不确定信息。在环境参数和声源参数都未知的情况下，利用蒙特卡洛法在不同信噪比情况下对两种声源定位方法进行分析，实验结果表明：(1)对于敏感参数，如声源距离、水深和海水声速，最大边缘后验概率密度法比最大边缘后验概率密度方法的性能好。(2)对于较不敏感的参数，如海底声速、海底密度和海底声衰减，当信噪比较低时，最大边缘后验概率密度方法能较好地平滑噪声，从而比最大边缘后验概率密度法具有更好的性能。由于声源距离和深度是敏感参数，研究表明最大边缘后验概率密度法提供了一种在不确知环境下更可靠的多声源定位方法。     

基于最大似然估计的雷达高度计海面参数联合反演

对合成孔径雷达高度计的参数反演问题进行了研究。根据合成孔径雷达高度计的海面回波模型,推导了利用最大似然估计反演海面参数的算法流程,并确定了联合反演时海面参数的估计顺序,然后在给定的仿真参数下对海面参数的反演流程进行了仿真。仿真得到的参数估计值满足指标要求,显示了算法的良好性能。分析结果对雷达高度计的系统设计和挂飞试验都有一定的参考意义。     

浅海聚焦定位中简化地声模型的应用研究

为了提高定位算法的环境宽容性,聚焦法将环境参数纳入了寻优空间。聚焦法虽然降低了对环境测量的要求,但是反演参数的增加也增加了反演的复杂性。基于海底反射特性,用两个参数对海底进行建模。通过标准的反演测试问题对简化地声模型在浅海聚焦定位中的有效性进行了分析。结果表明:基于简化地声模型的聚焦定位是可行的。在获得正确定位结果的同时,随着地声参数个数的减少,匹配场处理的便捷性得到了提高。文中引入的简化地声模型是聚焦问题中参数最少的地声模型,它可以有效减少聚焦定位参数维数以提升反演的便捷性。同时,简化地声模型在参数敏感性和耦合性上有较好的表现,这些优点可以保证定位结果的稳健性。     

中法海洋卫星微波散射计风场反演残差特性研究

2018年10月发射的中法海洋卫星散射计(CSCAT)是国际上首个扇形波束旋转扫描微波散射计。本文以最大似然估计风场反演算法为基线,详细分析了中法海洋卫星微波散射计海面风场反演代价函数的残差特性,重点研究了新的观测几何对风场反演残差以及风场质量的影响,并建立了风场模糊解的似然概率模型函数。结果表明,CSCAT风场反演的残差特性随风矢量单元在刈幅交轨方向位置的变化而变化,模糊解似然概率模型函数的指数分布在?0.4～?1.8之间。分析结果为CSCAT风场质量控制和二维变分分析去模糊算法的精细化调整提供了重要的参考。     

长期极值统计理论及其在海洋环境参数统计分析中的应用

海洋环境极值参数(如风速、流速、波高、周期等)在海洋工程设计中具有重要意义。利用次序统计和极值理论方面的较新研究成果，从理论上证明了多种统计分布中Weibull分布是最优的，使长期极值统计建立在一个更坚实的基础上；同时引入基于序列统计的最大似然估计方法。利用大量数据．对最小二乘估计方法和最大似然估计法进行对比分析，指出最大似然估计法是精确估计．而最小二乘估计方法是保守估计。     

HY-2A卫星高度计不同重跟踪方案对反演海浪有效波高的影响

本文基于Amarouche的二阶理论回波模型,导出了带有偏度系数的二阶理论回波模型;针对HY-2A卫星高度计波形特点,引入了奇异值分解滤波,并根据最大似然估计算法反演参数的不同得到6种重跟踪方案;利用其中的五参数方案处理该波形数据,获得海面散射点高度概率密度函数中偏度的合理取值为0.15;将结果分别与浮标、Jason-1和HY-2AIDR有效波高对比,分析6种方案反演有效波高的准确度,确定了MLE4_SVD(波形重跟踪之前进行滤波)对HY-2A高度计重跟踪更适合反演有效波高。     

基于Sobol法的海底反向散射模型参数敏感度分析

为了对海底声学参数反演中的估计精度做出预估,合理解释反演结果,本文基于Jackson海底声散射模型,利用Sobol算法,对该模型中的耗散系数、速度比等7个参数进行定量的敏感度分析。Sobol算法可以给出参数的一阶敏感度和参数间相互作用的敏感度,适用于分析散射强度的影响因子。仿真结果表明,所选择的声波频率对于参数的敏感度影响不大,模型各参数交互作用较为强烈,速度比的全局敏感度最大,而耗散系数敏感度很小。将参数划分为地声属性参数、粗糙度参数和非均匀性参数,地声属性参数敏感度最大。模型参数敏感度分析结果对于反演有一定的指导作用。     

基于COS-2S模型的ADCP海浪方向谱估计

美国RD公司声学多普勒流速剖面仪(ADCP)使用的波向估计算法是迭代的最大似然算法(IMLM),IMLM可以准确估计出主浪向,但波向估计结果在主浪向以外其他方向上存在由噪声带来的能量分布,使得估计结果变得不准确。设计了基于COS-2S模型的波向估计方法,模型中只含有主波向,算法在准确估计主波向同时有效去除其他方向上噪声带来的能量分布。将一种混合遗传算法(HGA)代替遗传算法(GA)应用到波浪模型的参数求解中,HGA相对GA收敛更快,可有效找出全局最优解。仿真分析和实测数据表明,HGA和IMLM都能准确估计出波浪的主浪向,但HGA可有效去除主浪向以外其他方向上噪声带来的能量分布,HGA比IMLM更加适用于海洋各种噪声存在条件下的测量环境。     

概率权重矩法及其在Weibull分布参数估计中的应用

本文应用Ｗｅｉｂｕｌｌ分布各参数的概率权重矩表达式，估计Ｗｅｉｂｕｌｌ分布参数，并用该分布推算一百年一遇最大风速值，与目前国内较为流行的极值Ⅰ型和对数正态分布推算值比较接近。通过统计检验对概率权重矩法与最小二乘法和最大似然法进行比较，结果表明，虽然其拟合优度与最小二乘法和最大似然法相当，但计算过程要简单得多。     

磁性目标跟踪的多模型自适应滤波方法

针对非协作磁性目标定位中初始条件难以确定的问题，提出一种基于静态多模型滤波思想的自适应跟踪方法。 首先对磁场观测模型进行分析，设计了一种磁性目标初始参数估算方法，通过该方法得到不同假设条件下的磁性目标状态初值及其误差矩阵，在此基础上起始多个扩展卡尔曼滤波器(Extended Kalman Filter， EKF) 进行求解，根据各个滤波器的求解结果利用最大似然准则选取最佳解作为当前时刻估计结果。 通过仿真实验验证了方法的有效性，结果表明，方法可在目标源及位置等先验信息完全未知条件下准确估计出真实目标状态，对磁性目标实际应用具有参考价值。     

Geoacoustical parameters estimation with impulsive and boat-noise sources

Localization is a crucial issue in underwater acoustics: when an underwater source is detected, the next step consists of localizing it. To do this, environmental parameters must be known or estimated. How can we estimate these parameters? As underwater sources produce low frequency (<100 Hz), most of the seismic processing tools developed by petroleum research can be adapted to estimate geophysical parameters of the sea and the seafloor. To know which methods or representations are useful to estimate geoacoustical parameters, a study of the propagation between an underwater source and receivers laid on the floor is proposed in the case of a real waveguide. Then, geoacoustical parameters are estimated on real data using transformations such as velocity correction or frequency-wavenumber transform. To validate these methods, two wave-propagation simulations using a finite-difference algorithm are made: the first in an environment similar to the model used to estimate geoacoustical parameters and the second in a more realistic environment (with several layers of sediments and variable water layer depth). Geoacoustical parameters are estimated and compared to the values used in the simulation. Finally, impulsive source is replaced by a boat-noise source to show that it is still possible to estimate geoacoustical parameters using noise sources.     

Estimation of Transmission Loss in the Presence of Geoacoustic Inversion Uncertainty

A common problem in sonar system prediction is that the ocean environment is not well known. Utilizing probabilistic based results from geoacoustic inversions we characterize parameters relevant to sonar performance. This paper describes the estimation of transmission loss and its statistical properties based on posterior parameter probabilities obtained from inversion of ocean acoustic array data. This problem is solved by first finding an ensemble of relevant environmental model parameters and the associated posterior probability using a likelihood based inversion of the acoustic array data. In a second step, each realization of these model parameters is weighted with their posterior probability to map into the transmission loss domain. This approach is illustrated using vertical-array data from a recent benchmark data set and from data acquired during the Asian Seas International Acoustics Experiment (ASIAEX) 2001 in the East China Sea. The environmental parameters are first estimated using a probabilistic-based geoacoustic inversion technique. Based on the posterior probability that each of these environmental models fits the ocean acoustic array data, each model is mapped into transmission loss. This enables us to compute a full probability distribution for the transmission loss at selected frequencies, ranges, and depths, which potentially could be used for sonar performance prediction.     

VLF source localization with a freely drifting acoustic sensorarray

The source localization and tracking capability of the freely drifting Swallow float volumetric array is demonstrated with the matched-field processing (MFP) technique using the 14-Hz CW data collected during a 1989 float experiment conducted in the northeast Pacific. Initial MFP of the experimental data revealed difficulties in estimating the source depth and range while the source azimuth estimate was quite successful. The main cause of the MFP performance degradation was incomplete knowledge of the environment. An environment adaptation technique using a global optimization algorithm was developed to alleviate the environmental mismatch problem, allowing the ocean-acoustic environment to be adapted to the acoustic data in a matched-field sense. Using the adapted environment, the 14-Hz source was successfully localized and tracked in azimuth and range within a region of interest using the MFP technique at a later time interval. Two types of environmental parameters were considered, i.e., sound speed and modal wave number. While both approaches yield similar results, the modal wave number adaptation implementation is more computationally efficient     

Track Parameter Estimation from Multipath Delay Information

It is desired to track the location of an underwater acoustic source with range difference measurements from a stationary passive array. Many times, the array has only one or two sensors, and the multipath and intersensor range difference measurements are insufficient to localize and track a source moving along an arbitrary path [1]. Here, we propose to track sources with one- or two-sensur stationary passive arrays by making the simplifying assumption that the source's path can be described by a small set of so-called track parameters. Range difference information can then be used to estimate the track parameter set rather than the source location as a function of time. In this paper, we choose the track parameters to specify a straight-line constant-velocity constant-depth path. Cramer-Rao bounds are presented for estimating these track parameters from the time history of multipath and intersensor range difference measurements. It is shown that this track parameter set cannot be accurately estimated from the time history of a single multipath range difference without side information (an independent velocity estimate, for instance), although multipath and intersensor range difference measurements from a two-sensor array are generally sufficient to estimate the track parameter set. Computationally efficient techniques are presented which estimate track parameters from range difference measurements taken from one- and two-sensor arrays. Monte-Carlo simulations are presented which show that these techniques have sample mean-square error approximately equal to the Cramer-Rao bound when a single multipath range difference and an independent velocity estimate are available. The sample mean-square error is shown to be in the range of two to ten times the corresponding Cramer-Rao bounds when these techniques are applied to two-sensor range difference data.     

Source localization in shallow water in the presence of sensorlocation uncertainty

The problem of source localization in shallow water in the presence of sensor location uncertainty is considered. The Cramer-Rao Bound is used to carry out a feasibility study for the joint source and sensor location problem when the multipath propagation channel is modeled as a known, deterministic waveguide. Unlike the free-space propagation channel, the boundedness of the shallow-water waveguide along its vertical axis provides the key to joint determination of the source and sensor location parameters. It is seen that, when a set of intuitive identifiability conditions are satisfied, numerical examples indicate that, for the scenarios considered, the resulting loss in accuracy with which the source location can be estimated due to sensor location uncertainty may be tolerable     

Robust source localization in shallow water based on vector optimization

Owing to the multipath effect, the source localization in shallow water has been an area of active interest. However, most methods for source localization in shallow water are sensitive to the assumed model of the underwater environment and have poor robustness against the underwater channel uncertainty, which limit their further application in practical engineering. In this paper, a new method of source localization in shallow water, based on vector optimization concept, is described, which is highly robust against environmental factors affecting the localization, such as the channel depth, the bottom reflection coefficients, and so on. Through constructing the uncertainty set of the source vector errors and extracting the multi-path sound rays from the sea surface and bottom, the proposed method can accurately localize one or more sources in shallow water dominated by multipath propagation. It turns out that the natural formulation of our approach involves minimization of two quadratic functions subject to infinitely many nonconvex quadratic constraints. It shows that this problem (originally intractable) can be reformulated in a convex form as the so-called second-order cone program (SOCP) and solved efficiently by using the well-established interior point method, such as the software tool, SeDuMi. Computer simulations show better performance of the proposed method as compared with existing algorithms and establish a theoretical foundation for the practical engineering application.     

Ensemble covariances adaptively localized with ECO-RAP. Part 1: tests on simple error models

In atmospheric data assimilation (DA), observations over a 6–12-h time window are used to estimate the state. Non-adaptive moderation or localization functions are widely used in ensemble DA to reduce the amplitude of spurious ensemble correlations. These functions are inappropriate (1) if true error correlation functions move a comparable distance to the localization length scale over the time window and/or (2) if the widths of true error correlation functions are highly flow dependent. A method for generating localization functions that move with the true error correlation functions and that also adapt to the width of the true error correlation function is given. The method uses ensemble correlations raised to a power (ECO-RAP). A gallery of periodic one-dimensional error models is used to show how the method uses error propagation information and error correlation width information retained by powers of raw ensemble correlations to propagate and adaptively adjust the width of the localization function. It is found that ECO-RAP localization outperforms non-adaptive localization when the true errors are propagating or the error correlation length scale is varying and is as good as non-adaptive localization when such variations in error covariance structure are absent.     

基于小型三维阵列的瞬态声源快速被动定位方法

重物在落水和着底过程中都会产生瞬态声信号,这类信号可被运用于浅水区域水下目标定位。 针对浅水区域目标定位的问题,提出了一种基于小型立体五元基阵的瞬态声源快速被动定位算法。 在分析重物落水信号特征的基础上,选取合适的广义互相关加权函数求得传声器之间的声程差,运用快速最小二乘搜索算法进行声源定位。 结果表明:运用 5 传声器阵列可以同时兼顾定位精度和鲁棒性,且满足实时性要求,该方法可运用于浅水区域瞬态声源定位等领域。