Chaotic dynamics of sea clutter

The notion that a deterministic nonlinear dynamical system (with relatively few degrees of freedom) can display aperiodic behavior has a strong bearing on sea clutter characterization: random-looking sea clutter may be the outcome of a chaotic process. This new approach envisages deterministic rules for the underlying sea clutter dynamics, in contrast to the stochastic approach where sea clutter is viewed as a random process with a large number of degrees of freedom. In this paper, we demonstrate, convincingly for the first time, the chaotic dynamics of sea clutter. We say so on the basis of results obtained using radar data collected from a series of extensive and thorough experiments, which have been carried out with ground-truthed sea clutter data sets at three different sites. The study includes correlation dimension analysis (based on the maximum likelihood principle) and Lyapunov spectrum analysis. The Lyapunov (Kaplan-Yorke) dimension, which is a byproduct of Lyapunov spectrum analysis, shows that it is indeed a good estimator of the correlation dimension. The Lyapunov spectrum also reveals that sea clutter is produced by a coupled system of nonlinear differential equations of order five or six. (c) 1997 American Institute of Physics.     

基于海杂波散射特性的微弱信号检测方法

从研究海杂波的电磁散射特性出发,利用随机微分理论对海杂波的物理特性进行了系统地分析.首先建立了海杂波电磁散射所满足的随机微分方程,然后利用Itô公式得到了海杂波散射信号幅度和相位的扩散过程模型,最后利用海杂波散射信号的规律给出了微弱信号检测的相关处理方法. 关键词： 随机微分方程 海杂波 散射 微弱信号     

基于小波leaders的海杂波时变奇异谱分布分析

海杂波的奇异谱分析不仅能从理论上揭示海洋表面的动力学机理,同时也是对海探测雷达的关键技术之一.本文提出基于小波leaders的海杂波时变奇异谱分析方法,将时间信息引入海杂波的奇异谱分析之中,从而实现动态的解析描述海杂波随时间变化的奇异谱特性.在理论上,通过信号自身加窗,将时间信息引入传统的奇异谱(或称多重分形谱),实现了对海杂波时变奇异谱分布分析;在算法上,充分利用了小波leaders技术对于多种奇异性的提取能力(包括chirp奇异性和cusp奇异性),通过对时变奇异性指数和时变尺度函数的Legendre变换,实现对海杂波时变奇异谱分布的计算;在应用部分,采用经典的多重分形模型——随机小波序列(RWC)以及三级海态条件下连续波多普勒体制雷达海杂波进行仿真分析,实验结果表明:1)基于小波leaders的奇异谱分布能跟踪海杂波的时变尺度特性,有效展示其时变奇异性谱分布;2)算法具有较好的负矩特性和统计收敛性.该方法能为复杂非线性系统及随机多重分形信号分析提供参考.     

Detection probability and detection time using clutter metrics

We modified the structure similarity index, which is extensively used for image quality assessment, to be clutter metrics and call them target structure similarity measures (TSSIM). Two methods for calculating the TSSIM metrics were suggested. In this paper, via different mathematical formulas, the metrics are used to predict detection probabilities and detection times. The degrees of correlation between various clutter metrics and both the target detection probabilities and the mean detection times, which are obtained from the Search_2 dataset, are presented. Based on these data, comparisons between TSSIMs and three other typical clutter metrics are demonstrated. Experiment results show the TSSIMrms measure generates much better predictive capabilities for both the experimental detection probabilities and the mean detection times than other clutter measures being compared.     

海杂波的分段分数布朗运动模型

主要研究了分段分数布朗运动(PFBM)模型在雷达海杂波分形建模中的应用.由于自然界和人造系统中研究对象不具有数学上完美的分形特性, 从而研究对象的分形特性无法在整个尺度区间上成立, 传统上, 海杂波的单一分形模型仅利用无标度区间内海杂波的自相似信息进行参数估计, 并没有考虑海杂波在无标度区间以外的尺度下所包含的信息.分段分数布朗运动从频域角度对海杂波频谱进行分段描述, 对应到时域即从粗略尺度和精细尺度两方面描述海杂波时间序列.结合海杂波产生的物理背景, 该模型可以为海杂波时间序列在粗略尺度和精细尺度下表现出的不同粗糙度提供机理性解释.在此基础上, 还研究了具有不同多普勒频率的运动目标对海杂波的影响, 结果表明运动目标对粗略尺度和精细尺度下海杂波的影响程度是不同的.     

A Novel Measure Inspired by Lyapunov Exponents for the Characterization of Dynamics in State-Transition Networks

The combination of network sciences, nonlinear dynamics and time series analysis provides novel insights and analogies between the different approaches to complex systems. By combining the considerations behind the Lyapunov exponent of dynamical systems and the average entropy of transition probabilities for Markov chains, we introduce a network measure for characterizing the dynamics on state-transition networks with special focus on differentiating between chaotic and cyclic modes. One important property of this Lyapunov measure consists of its non-monotonous dependence on the cylicity of the dynamics. Motivated by providing proper use cases for studying the new measure, we also lay out a method for mapping time series to state transition networks by phase space coarse graining. Using both discrete time and continuous time dynamical systems the Lyapunov measure extracted from the corresponding state-transition networks exhibits similar behavior to that of the Lyapunov exponent. In addition, it demonstrates a strong sensitivity to boundary crisis suggesting applicability in predicting the collapse of chaos.     

Langevin Dynamics,Large Deviations and Instantons for the Quasi-Geostrophic Model and Two-Dimensional Euler Equations

We investigate a class of simple models for Langevin dynamics of turbulent flows, including the one-layer quasi-geostrophic equation and the two-dimensional Euler equations. Starting from a path integral representation of the transition probability, we compute the most probable fluctuation paths from one attractor to any state within its basin of attraction. We prove that such fluctuation paths are the time reversed trajectories of the relaxation paths for a corresponding dual dynamics, which are also within the framework of quasi-geostrophic Langevin dynamics. Cases with or without detailed balance are studied. We discuss a specific example for which the stationary measure displays either a second order (continuous) or a first order (discontinuous) phase transition and a tricritical point. In situations where a first order phase transition is observed, the dynamics are bistable. Then, the transition paths between two coexisting attractors are instantons (fluctuation paths from an attractor to a saddle), which are related to the relaxation paths of the corresponding dual dynamics. For this example, we show how one can analytically determine the instantons and compute the transition probabilities for rare transitions between two attractors.     

Estimation of sea clutter inherent Doppler spectrum from shipborne S-band radar sea echo

Measurement of shipborne radar sea echo is instrumental in collecting the sea clutter data in open sea areas. However,the ship movement would introduce an extra Doppler component into the spectrum of the sea clutter, so the sea clutter inherent spectrum must be estimated prior to investigating the sea clutter Doppler characteristics from the shipborne radar sea echo. In this paper we show some results about a shipborne sea clutter measurement experiment that was conducted in the South China Sea in a period between 2017 and 2018; abundant clutter data have been collected by using a shipborne S-band clutter measurement radar. To obtain the sea clutter inherent Doppler spectrum from these data, an estimation method, based on the mapping relationship between the shipborne clutter spectrum and the inherent clutter spectrum, is proposed. This method is validated by shipborne clutter data sets under the same measuring conditions except for the ship speed. Using this method, the characteristics of the Doppler spectrum lineshapes in the South China Sea are calculated and analyzed according to different sea states, wave directions, and radar resolutions, which can be instrumental in designing the radar target detection algorithms.     

空间散斑的运动规律(续)——物表面位移微分量的影响

本文讨论了由物表面变形所引起的空间散斑的运动。从Fresnel-Kirchhoff积分出发,导出了受物表面变形影响的散斑运动必须遵从的基本方程组,并对它们的物理意义进行了讨论。把物表面刚体运动和变形影响下的基本方程组综合起来,导出了物表面发生一般运动和变形时,空间散斑运动的公式。实验结果与公式一致。 关键词：     

基于不同散射机制特征的海杂波时变多普勒谱模型

海杂波的多普勒谱建模对采用多普勒处理技术的雷达进行有效的海杂波抑制和目标检测具有重要的意义.本文分别考虑Bragg,白冠和破碎波三种散射机制对应的多普勒谱分量的特征,对三种谱分量的频移和展宽进行分离,并引入附加速度频移量,提出了基于不同散射机制特征的雷达海杂波时变多普勒谱模型.该模型假设谱强度为受观测时间区间影响的随机变量,能够同时适用于平均多普勒谱与短时多普勒谱建模.通过分别对黄海海域实测的岸基P,S波段海杂波平均多普勒谱与短时多普勒谱建模测试,结果表明该模型相对传统模型的建模精度更高,尤其体现在短时谱的观测时间较长和平均谱形式较为复杂的情况下,建模误差显著减小.     

利用散斑图像测量表面粗糙度的计算机模拟及实验

从菲涅耳-基尔霍夫衍射公式出发推导出了粗糙面近场衍射方程。通过对观察面散斑光强统计特性的分析,提出了采用镜射光强分量法测量表面粗糙度的思想。为验证该方法的有效性,首先用计算机模拟产生具有不同统计特性的随机表面,然后对由随机表面产生的散斑场及其光强分布进行计算。计算结果表明,与传统的散斑对比度法相比,散斑镜射光强分量法测量弱粗糙表面粗糙度具有更大的适用范围和更高的测量精度,克服了散斑对比度法易受表面横向相关长度影响的缺点。通过实验对计算机模拟结果进行了验证。     

Decay of correlations. IV. Necessary and sufficient conditions for a rapid decay of correlations

We considerN-particle systems whose probability distributions obey the master equation. For these systems, we derive the necessary and sufficient conditions under which the reducedn-particle (n) probabilities also obey master equations and under which the Ursell functions decay to their equilibrium values faster than the probability distributions. These conditions impose restrictions on the form of the transition rate matrix and thus on the form of its eigenfunctions. We first consider systems in which the eigenfunctions of theN-particle transition rate matrix are completely factorized and demonstrate that for such systems, the reduced probabilities obey master equations and the Ursell functions decay rapidly if certain additional conditions are imposed. As an example of such a system, we discuss a random walk ofN pairwise interacting walkers. We then demonstrate that for systems whoseN-particle transition matrix can be written as a sum of one-particle, two-particle, etc. contributions, and for which the reduced probabilities obey master equations, the reduced master equations become, in the thermodynamic limit, those for independent particles, which have been discussed by us previously. As an example of suchN-particle systems, we discuss the relaxation of a gas of interacting harmonic oscillators.Supported in part (grants to D.B. and K.E.S.) by the Advanced Research Projects Agency of the Department of Defense as monitored by the U.S. Office of Naval Research under Contract N00014-69-A-0200-6018, and in part (grant to I.O.) by the National Science Foundation.     

气液两相流电导波动信号复杂性测度分析及其流型表征

为了考察从时间序列提取的复杂性测度与气液两相流流型变化之间的关系，本文首先讨论了三种复杂性测度(Lempel-Ziv复杂性、功率谱熵和近似熵)对周期信号、随机信号、混合随机信号和混沌信号的识别能力，然后分析了时间序列长度对复杂性计算的影响.在此基础上，从实际测量的80种垂直上升管中气液两相流电导波动信号中提取了这三种复杂性测度，结果表明：三种复杂度对两相流流型变化是敏感的，通过对三种复杂度随两相流流动参数变化规律分析，可以得到气液两相流动力学结构反演特征，为揭示气液两相流流型转化机理提供了一种有效的辅助诊断工具. 关键词： 气液两相流 Lempel和Ziv复杂性 功率谱熵 近似熵     

Segmentation and classification of time series using ordinal pattern distributions

The distribution of ordinal patterns in time series has been found to reflect important qualitative features of the underlying system dynamics. Abrupt changes in the dynamics typically result in clearly visible differences between the distributions before and after the break. Recurring dynamical regimes can be discovered by classifying the distributions in different parts of the time series. This paper discusses two algorithms which exploit the relation between ordinal pattern distributions and system dynamics for the segmentation and classification of time series. The first algorithm employs a kernel-based statistic, the Maximum Mean Discrepancy of ordinal pattern distributions, to detect and locate change points in the time series. The second algorithm uses clustering of the ordinal pattern distributions to classify time series segments with similar dynamics. The methodology is applied to various real-life time series from physiology and economics.     

海杂波背景下小目标检测的分形方法

针对海杂波背景下小目标检测对海情依赖性强的问题, 本文采用分数布朗运动模型对实测海杂波建模, 结合多重分形去势波动分析法确定分形参数, 分析了海杂波的单尺度、多重分形特性. 在单尺度分形的基础上, 利用表征海杂波分形特征的分数维和Hurst指数构建了分形差量, 提出了基于分形差量的小目标检测方法;在多重分形基础上, 比较了两种海杂波的高尺度多重分形特性. 结果表明, 当尺度q > 10时, 纯海杂波的多重分形参数H(q) < 0, 而存在小目标的H(q) > 0, 此差异性为高尺度分形参数的海杂波背景小目标检测提供了判定依据. 所研究的两种方法均能实现不同海情下的小目标检测.     

Dynamics of a quantum phase transition

We present two approaches to the dynamics of a quench-induced phase transition in the quantum Ising model. One follows the standard treatment of thermodynamic second order phase transitions but applies it to the quantum phase transitions. The other approach is quantum, and uses Landau-Zener formula for transition probabilities in avoided level crossings. We show that predictions of the two approaches of how the density of defects scales with the quench rate are compatible, and discuss the ensuing insights into the dynamics of quantum phase transitions.     

椭球模型下通过雾场的多重光散射谱

由于雾滴的非球形、多重散射特性以及几何光学效应,光通过实际雾场的散射问题成为一个研究难点. 建立了近于实际的椭球雾滴模型,考虑光的衍射、透射及反射特性后,利用辐射传播方程得到了在不同的雾滴大小分布 及不同的雾滴形状分布下通过雾场的多重散射光强公式.在两种特例下与已有的结果较为相符,说明了方法的可靠性. 计算表明:与随机取向的非球形颗粒场的散射谱呈圆形特征不同,通过椭球形雾滴场的散射谱呈椭圆特征, 不同方位角的散射光强角分布有所差异,雾滴的形状因子越接近于1,差异越小;与单散射不同, 散射谱中的条纹随光学厚度增大逐步消失;对于不同大小分布及不同形状分布的雾滴场, 在不同方位角及不同观察角的散射光强随光学厚度τ的增加总是先增大再减小,光强的极大值位置在τ = 1.0---3.0 范围内.计算同时还表明,由于多数情况下实际雾场的雾滴大小偏差较大, 因而通过雾场的散射谱将呈现以中央亮斑为中心向四周弥散的图样.     

海杂波FRFT域的分形特征分析及小目标检测方法

针对海杂波背景下海情对小目标检测的严重影响, 本文研究了实测海杂波在分数阶Fourier变换(FRFT)域的分形特征, 分别提出了单、高尺度下的分形检测方法. 由数学定义推得, FRFT 在不同阶数和尺度情况下, 不具有一致的自相似特性, 采用多重分形趋势波动分析法确定分形参数H(q), 分析了海杂波在不同海情、距离和极化条件下的分形特征. 在单尺度基础上结合FRFT的变阶优势, 提出了阶数自适应的小目标检测方法; 高尺度条件下, 比较了不同因素对海杂波FRFT域多重分形参数的影响. 结果表明:海杂波FRFT域可用变换阶数的方法检测到湮没在复杂海情中的小信号, 检测门限多数提高200%以上, 比采用时域信号提高26.3%. H(q) 在负高尺度上具有明显的多重分形特征差异, H(q)-q曲线满足反正切分布, 纯海杂波与含目标数据的拟合幅值比分别大于1.8(HH)和1.4(VV), 为海杂波背景小目标检测提供了判定依据.     

海杂波背景下的目标检测新方法

提出了一种基于分形布朗运动模型的S波段雷达海杂波分形维数提取方法.分析了基于记忆库混沌时间序列预测方法，引入一种改进核函数的支持向量机分类器.在此基础上，提出了一种新的海杂波背景下目标检测方法.应用S波段雷达实测海杂波数据，计算得到了该信号的分形维数与Lyapunov指数，验证了S波段雷达海杂波的混沌分形特性.仿真实验结果验证了该方法具有较强的检测能力和抗杂波性能. 关键词： 分形布朗运动 分形维数 记忆库预测方法 支持向量机分类器