基于最优估计理论、联合星载主被动传感器资料的液态云微物理特性反演研究

针对液态云微物理特性精确反演的迫切需求, 综合主被动传感器的探测优势, 联合CloudSat雷达反射率和Aqua光学厚度资料, 提出基于最优估计理论的液态云微物理参数反演算法.通过假设粒子谱服从对数正态分布, 基于前向物理模式建立测量变量与反演变量的函数关系, 借助谱分布参数的先验信息、通过算法迭代得到谱参数的最优解, 进而利用前向物理模式反演液态云微物理参数, 并根据误差传递理论计算反演不确定度.通过设计反演方案, 基于实测个例数据并与CloudSat官方发布产品和经验算法反演结果对比验证.结果表明: 基于最优估计理论、联合主被动传感器资料的液态云微物理参数反演结果与官方发布产品一致性较好, 弥补了经验算法误差大、扩展性差的不足, 对于开展国内星载和机载W波段毫米波雷达液态云微物理参数反演研究具有重要的借鉴意义. 关键词： CloudSat Aqua 液态云 最优估计理论     

横向各向同性地层快速各向异性反演方法

斯通利波的频散特性常用于反演横向各向同性地层的各向异性。该文重点对斯通利波频散曲线随井孔和地层弹性模量相关参数的变化规律进行了探讨,提出了频散曲线的快速插值计算方法,经过误差分析验证了插值频散计算的可行性。据此提出了通过对参数大间隔取值建立理论频散数值表,插值计算不同各向异性参数的频散曲线,对比波形频散快速反演横向各向同性地层各向异性的方法。基于实轴积分法计算的横向各向同性地层井孔声场分别进行了插值频散快速反演和传统方法反演,对比结果证实了该文提出的快速反演方法的准确高效性,并且对数据加噪后验证了快速反演方法的抗噪性。     

基于逆散射理论的地震波速度正则化反演

本文基于逆散射理论利用正则化有限差分对比源反演算法对地震波传播速度进行反演, 该方法是基于波动方程的频率域波形反演算法, 利用非线性共轭梯度法, 通过最小化目标优化函数不断迭代更新速度模型. 由于地球物理反演问题的病态性和不稳定性, 通过基于反演参数总变差的正则化处理, 使反演问题变为良性问题且算法具有较强的抗噪声干扰能力. 反演过程中使用了频率-空间域9点差分正演算子以及PML吸收边界条件. 与其他反演算法相比, 由于背景模型在反演迭代过程中保持不变, 可以避免在每次迭代过程中重新构造正演算子及矩阵分解等相关计算过程, 使得该算法非常适合于大规模三维反演计算. 此外, 本文采用基于MPI的并行计算, 进一步提高了反演计算的效率. 二维CSEG模型反演结果表明该方法可以反演得到高分辨率的地震波速度重建结果, 为地震勘探数据处理及解释提供准确的速度信息.     

一种基于激光辐照热效应的薄膜参数反演方法

本文研究并建立了一种基于激光辐照热效应的薄膜参数反演方法.首先给出激光辐照薄膜产生温升问题的热传导理论模型,并利用拉普拉斯变换得到了膜层和基底温度场的解析解;然后以膜层和基底的导热系数为反演参数,基于非线性共轭梯度算法给出反演基本原理及流程,并推导得到了反演过程中灵敏度系数的解析表达式;以aluminum,silver,copper和gold四种金属薄膜为例,通过与有限元法的计算结果对比验证了温度场解析解的正确性;最后结合四种金属薄膜进行了参数反演,通过考察分析不同随机噪声等条件下的参数反演结果,验证了本文方法在薄膜参数反演精度与反演效率等方面的有效性.反演结果显示:本文方法具有较高的反演精度和效率,在迭代截止误差为10~(-7)时只需用少于20次迭代就能收敛;在测量数据中加入的随机噪声越小,反演的迭代收敛次数就越少,即使是在迭代初值与反演结果相差较大时,用包含5%随机噪声的测量数据反演也能快速收敛.本文提出的薄膜参数反演方法不仅适用于反演导热系数,也可扩展用于反演膜层反射系数或吸收率等参数,具有一定的适用性.本文方法对于激光加工或激光损伤过程中的参数反演及优化具有一定的指导意义.     

利用井孔偶极弯曲波反演横向各向同性孔隙地层渗透率的研究

对利用井孔偶极弯曲波衰减特性反演横向各向同性孔隙地层的纵、横向渗透率进行了理论方法和数值研究.对软地层,在方差函数极值行为分析的基础上,用最小二乘反演对多组理论模拟数据进行处理,得到的纵、横向渗透率精度都比较高,这与软地层弯曲波衰减对纵向渗透率的敏感程度明显比硬地层高有关;用添加不同强度的随机噪声综合反映现场资料可能带来的误差,对多道间提取的衰减叠加求平均可明显的抵消噪声的影响;对快速孔隙地层偶极声测井理论模拟数据也尝试性地进行了纵、横向渗透率反演,发现,虽然硬地层弯曲波的衰减对纵向渗透率很不敏感,但纵向渗透率的取值偏离真值却对横向渗透率的反演结果有明显影响.     

采用邻域近似算法估计环境参数不确定性

根据贝叶斯理论,逆问题的解可以用后验概率密度来表征,它包含了模型参数先验知识和观测数据信息,反映了反演参数的不确定性.一种快速吉布斯采样算法已经被用于后验概率密度的多维积分运算,但其需要调用大量的声场前向模型,在多个频率或水平变化的匹配场参数反演中,计算量仍然很大.基于邻域近似算法,提出一种比快速吉布斯采样算法更快的参数不确定性估计方法.对低维参数反演问题,邻域算法可以很好地逼近真实的后验概率密度;而对高维问题及其敏感参数,在模型参数样本量有限的条件下,邻域算法很难精确地估计后验概率密度.为了克服以上缺点,并完整地得到反演参数的不确定性信息,设计了一种多步估计方案.数值仿真和实测数据分析表明,多步邻域算法采用较少的计算代价,可获得与快速吉布斯方法相似的估计精度.     

细菌觅食优化算法在光散射法颗粒粒度反演中的应用

针对函数约束算法中传统的智能算法反演时存在鲁棒性差和易陷入局部最优的缺点,提出了将正则化理论与细菌觅食优化算法相结合应用在颗粒粒度的测量中。引入Tikhonov平滑泛函来构建算法的目标函数,采用L曲线法确定正则化参数;再利用细菌觅食优化算法通过趋向、聚群、复制和迁徙等四种智能行为,迭代计算来搜寻函数的最优解。实验仿真结果表明:利用细菌觅食优化算法实现了在不同程度的随机噪声下的服从J-SB分布的单峰分布的均匀球形颗粒粒度分布反演,其反演结果更稳定,反演精度高,对于实现稳定、快速、准确的颗粒粒度在线测量具有重要的意义。     

用改进的传输线算法计算水平层状横向同性地层中海洋可控源电磁响应

利用二维Fourier变换与电磁场分解技术将层状横向同性地层中Maxwell方程转化成两个独立的关于横磁(TM)波和横电(TE)波的传输线方程; 借助传输线理论与叠加原理, 仅利用电流源传输线Green函数得到TM波和TE波的解, 改进传输线算法, 建立横向同性地层中频率-波数域电流源电场和磁场并矢Green函数的新算法与新的解析表达式, 提高海洋可控源电磁响应数值模拟效率. 在此基础上, 利用传输线Green函数的基本解以及边界条件, 推导出广义反射系数与振幅递推公式, 得到各个地层中传输线Green函数的解析解; 然后利用Fourier逆变换与Bessel公式将海洋可控源电磁响应表示为Sommerfeld形式的积分, 借助三次样条插值与Lommel积分公式快速计算其数值解. 通过数值模拟结果考察工作频率以及地层各向异性电阻率变化等对海洋电磁响应的影响. 关键词： 传输线法 横向同性地层 海洋可控源电磁 Sommerfeld积分     

智能算法在晶体色散方程参量反演中的比较研究

为了研究智能优化算法在不同晶体材料色散方程参数反演中的迭代搜索性能问题,根据已测石英和方解石晶体的实验数据,分别采用遗传算法、模拟退火算法和遗传模拟退火算法应用于晶体色散方程的参数反演中,获得了晶体修正的塞耳迈耶尔方程的参量,同时比较了三种算法在迭代搜索性能、算法稳定性、计算时间和差方和等之间的差异,结果表明,三种算法在晶体色散方程参数反演时都可以得到满意的结果,但是,由于遗传模拟退火算法同时具备遗传算法的快速全局搜索性能和模拟退火算法的极强局部搜索性能,使得在晶体色散方程参数反演中的优化效果更优.因此在建立其它材料色散方程时建议采用遗传模拟退火算法,而且这一结果对研究混合智能算法的迭代搜索性能也是有帮助的.     

各向异性海底地层海洋可控源电磁响应三维积分方程法数值模拟

采用积分方程法对各向异性海底地层海洋可控源电磁（MCSEM）响应进行三维数值模拟.首先利用算子理论给出各向异性海底地层中的压缩积分方程,由于满足压缩映射条件,该积分方程在任意参数下总是迭代收敛的.然后为了提高计算效率,引入分区域多重网格准线性近似技术.通过具体算例验证了所述算法在计算精度与效率方面的有效性.最后利用该算法考察并分析了海底地层的各向异性对MCSEM三维响应特征的影响. 关键词： 海洋可控源电磁法 各向异性 三维模拟 积分方程法     

The estimation of lower refractivity uncertainty from radar sea clutter using the Bayesian-MCMC method

The estimation of lower atmospheric refractivity from radar sea clutter(RFC) is a complicated nonlinear optimization problem.This paper deals with the RFC problem in a Bayesian framework.It uses the unbiased Markov Chain Monte Carlo(MCMC) sampling technique,which can provide accurate posterior probability distributions of the estimated refractivity parameters by using an electromagnetic split-step fast Fourier transform terrain parabolic equation propagation model within a Bayesian inversion framework.In contrast to the global optimization algorithm,the Bayesian-MCMC can obtain not only the approximate solutions,but also the probability distributions of the solutions,that is,uncertainty analyses of solutions.The Bayesian-MCMC algorithm is implemented on the simulation radar sea-clutter data and the real radar seaclutter data.Reference data are assumed to be simulation data and refractivity profiles are obtained using a helicopter.The inversion algorithm is assessed(i) by comparing the estimated refractivity profiles from the assumed simulation and the helicopter sounding data;(ii) the one-dimensional(1D) and two-dimensional(2D) posterior probability distribution of solutions.     

大尺度分层介质电特性参数的反演方法研究

针对大尺度分层介质电磁场散射回波数据, 提出了一种用于分层介质特性参数反演的新方法, 实现了分层介质的介电常数、电导率和介质厚度的同时反演. 方法首先将这些参数的反演转化为最优化问题进行求解, 然后应用模拟退火算法搜索最优解, 充分利用算法的全局寻优能力, 同时改善了算法的搜索控制策略, 使算法在最优解的搜索过程中可以自适应地调整搜索步长, 提高了算法的搜索效率. 结果表明, 本文方法可以实现大尺度分层介质特性参数的准确反演, 且具有较强的抗噪声能力. 该方法可以应用于火星/月球 雷达探测回波数据的反演以及地下分层结构特性的分析. 关键词： 电磁散射 分层介质 模拟退火算法 最优化     

Estimation of lower refractivity uncertainty from radar sea clutter using Bayesian-MCMC method

Estimation of lower atmospheric refractivity from radar sea clutter (RFC) is a complicated nonlinear optimization problem. This paper deals with the RFC problem in a Bayesian framework. It uses unbiased Markov Chain Monte Carlo (MCMC) sampling technique, which can provide accurate posterior probability distributions of the estimated refractivity parameters by using an electromagnetic split-step fast Fourier transform terrain parabolic equation propagation model within a Bayesian inversion framework. In contrast to the global optimization algorithm, the Bayesian-MCMC can obtain not only the approximate solutions, but also the probability distributions of the solutions, that is, uncertainty analyses of solutions. The Bayesian-MCMC algorithm is implemented on the simulation radar sea-clutter data and the real radar sea-clutter data. Reference data are assumed to be simulation data and refractivity profiles obtained with a helicopter. Inversion algorithm is assessed (i) by comparing the estimated refractivity profiles from the assumed simulation and the helicopter sounding data; (ii) the one-dimensional (1D) and two-dimensional (2D) posterior probability distribution of solutions.     

一种基于支持向量机的海底声学参数快速统计反演方法

匹配场统计反演海底声参数的根本目的是求解未知参数的后验概率分布(PPD)。针对现有各种求解参数PPD的数值方法如穷举搜索、Markov Chain Monte Carlo采样、最近邻域插值近似算法普遍存在计算速度慢、时间长、难以满足实际应用的问题,本文提出了一种基于支持向量机的快速求解参数PPD的新算法。该算法利用了支持向量机强大的小样本学习能力,通过训练学习拟合未知海底声参数和后验概率之间存在的函数关系,从而在求解参数PPD时简化了利用声场传播模型计算后验概率的复杂过程,减少了计算时间。数值仿真算例和海上实验数据的处理结果验证了该算法在低维匹配场统计反演海底声参数问题中的有效性。      

Three-dimensional electromagnetic nonlinear inversion in layered media by a hybrid diagonal tensor approximation: Stabilized biconjugate gradient fast Fourier transform method

This paper presents an efficient three-dimensional nonlinear electromagnetic inversion method in a multilayered medium for radar applications where the object size is comparable to the wavelength. In the first step of this two-step inversion algorithm, the diagonal tensor approximation is used in the Born iterative method. The solution of this approximate inversion is used as an initial guess for the second step in which further inversion is carried out using a distorted Born iterative method. Since the aim of the second step is to improve the accuracy of the inversion, a full-wave solver, the stabilized biconjugate-gradient fast Fourier transform algorithm, is used for forward modelling. The conjugate-gradient method is applied at each inversion iteration to minimize the functional cost. The usage of an iterative solver based on the FFT algorithm and the developed recursive matrix method combined with an interpolation technique to evaluate the layered medium Green's functions rapidly, makes this method highly efficient. An inversion problem with 32 768 complex unknowns can be solved with 1% relative error by using a simple personal computer. Several numerical experiments for arbitrarily located source and receiver arrays are presented to show the high efficiency and accuracy of the proposed method.     

Three-dimensional electromagnetic nonlinear inversion in layered media by a hybrid diagonal tensor approximation: Stabilized biconjugate gradient fast Fourier transform method

This paper presents an efficient three-dimensional nonlinear electromagnetic inversion method in a multilayered medium for radar applications where the object size is comparable to the wavelength. In the first step of this two-step inversion algorithm, the diagonal tensor approximation is used in the Born iterative method. The solution of this approximate inversion is used as an initial guess for the second step in which further inversion is carried out using a distorted Born iterative method. Since the aim of the second step is to improve the accuracy of the inversion, a full-wave solver, the stabilized biconjugate-gradient fast Fourier transform algorithm, is used for forward modelling. The conjugate-gradient method is applied at each inversion iteration to minimize the functional cost. The usage of an iterative solver based on the FFT algorithm and the developed recursive matrix method combined with an interpolation technique to evaluate the layered medium Green's functions rapidly, makes this method highly efficient. An inversion problem with 32 768 complex unknowns can be solved with 1% relative error by using a simple personal computer. Several numerical experiments for arbitrarily located source and receiver arrays are presented to show the high efficiency and accuracy of the proposed method.     

Application of linear frequency modulated signals in three-dimensional radio tomography

A method is proposed for reconstructing three-dimensional images of scattering inhomogeneities from the results of wideband multiposition radio sounding in the millimeter-wave range with the help of linear frequency modulated signals. An algorithm is devised that implements the method based on the fast Fourier transform algorithm and ensures the real-time data processing. Results of numerical simulations, processed experimental data, and reconstructed images of test objects are considered.     

利用积分方程法的各向异性地层频率测深三维模拟

应用一种新的积分方程算法对各向异性地层频率域电磁测深三维问题进行正演模拟.利用范数小于或等于1的修正Green算子得到各向异性地层中的新积分方程,由于满足压缩映射条件,该积分方程在任意参数条件下总是迭代收敛的.提出一种应用迭代法求解新积分方程的迭代初值优化选择方法,并通过具体算例对比说明该方法可使频率域电磁测深三维模拟的计算效率得到有效提高.最后应用所述算法对层状各向异性大地轴向频率测深视电阻率响应进行三维数值模拟,考察分析地层的各向异性对视电阻率响应特征的影响,得到一些重要结论.     

Refractivity estimation from radar sea clutter

This paper addresses the problem of estimating lower atmospheric refractivity under the nonstandard propagation conditions frequently encountered in low altitude maritime radar applications. The vertical structure of the refractive environment is modeled by using a five-parameter model, and the horizontal structure is modeled as range-independent. The electromagnetic propagation in the troposphere is simulated by using a split-step fast Fourier transform based on parabolic approximation to the wave equation. A global search marked as a modified genetic algorithm (MGA) for the 5 environmental parameters is performed by using a genetic algorithm (GA) integrated with a simulated annealing technique. The retrieved results from simulated runs demonstrate the ability of this method to make atmospheric refractivity estimations. A comparison with the classical GA and the Bayesian Markov Chain Monte Carlo (Bayesian-MCMC) technique shows that the MGA can not only shorten the inverse time but also improve the inverse precision. For real data cases, the inversion values do not match the reference data very well. The inverted profile, however, can be used to synoptically describe the real refractive structure.