一类带乘性噪声多通道非线性系统的平滑算法

在各通道乘性噪声不同的情况下,针对多通道带乘性噪声非线性系统的状态估计问题,提出1种状态平滑算法。该算法运用扩展卡尔曼滤波方法先根据全部观测数据对状态进行滤波估计,并存储一步预测估计值和一步预测估计误差的方差,利用存储的数据进行递推运算,得到状态的固定域平滑估计。仿真结果表明平滑算法较滤波算法精确性更高,稳定性更强。     

复杂多通道带乘性噪声系统的最优固定域平滑算法

研究 1种在更弱的乘性噪声限制条件下系统的状态最优估计算法。在最优滤波算法的基础上 ,进一步给出了在线性最小方差意义下最优的固定域平滑算法。针对该算法所进行的仿真研究已表明该算法的有效性     

带乘性噪声广义系统状态最优估计算法

针对带乘性噪声广义系统,提出1种在线性最小方差意义下的状态最优估计算法.首先,采用标准分解将系统变换为2个子系统;其次,通过估计子系统的状态,获得原系统的状态最优滤波.同时,算法还给出了动态噪声与量测噪声的估计.仿真结果表明了该算法的有效性.     

带乘性噪声广义系统多传感器最优滤波融合算法

研究带乘性噪声广义系统的多传感器信息融合状态估计问题。在系统正则的假设条件下,通过受限等价变换将广义系统变换为2个降阶子系统,进而将针对原系统的信息融合状态估计转化为2个耦合的非广义子系统的多传感器信息融合状态估计,然后分别推导出集中式与分布式滤波融合算法,这2种算法在数学上完全等价,均在线性最小方差意义下最优。考虑到分布式滤波融合算法的优点,重点讨论了该算法,仿真实验验证了该融合算法的有效性。     

带乘性噪声的一类非线性系统的滤波算法

针对带乘性噪声的一类非线性系统,给出了1种带单重渐消因子的强跟踪状态滤波算法。该算法将非线性系统线性化后,采用了线性最小方差估计方法来进行状态估计,通过运用正交原理和引入渐消因子,使得滤波效果具有强跟踪的优良性能。该算法扩展了卡尔曼滤波在带乘性噪声非线性系统状态估计中的应用范围。仿真结果表明了该算法的有效性。     

带乘性噪声广义系统的观测噪声最优估计算法

研究带乘性噪声广义系统的观测噪声最优估计问题。在假设系统正则的情况下,针对乘性噪声为一般随机矩阵即各观测通道乘性噪声同时刻相关的情况,通过受限等价变换和状态扩维的方法,给出了线性最小方差意义下的观测噪声最优滤波算法和最优平滑估计算法。数字仿真结果表明了算法的有效性。     

通道特性相关时带乘性噪声系统观测噪声的最优估计

研究在较弱的乘性噪声条件下系统观测噪声的最优估计问题,就乘性噪声为一般随机矩阵且各观测通道乘性噪声在同时刻相关的情形,给出了在线性最小方差意义下的观测噪声最优滤波算法和最优平滑算法。针对这些算法进行了仿真研究,仿真结果表明算法有较好的估计效果。     

多通道带乘性噪声系统观测噪声的最优估计

研究在多通道观测时观测噪声的最优估计问题。就多通道的乘性噪声为对角阵且动态噪声一步相关并与观测噪声在同时刻和过去相邻时刻也相关的复杂情况下给出了在线性最小方差意义下的观测噪声最优滤波估计算法和固定区间平滑估计算法。针对这些算法进行了仿真研究 ,仿真结果表明了算法的有效性。     

转移矩阵未知时带乘性噪声系统的自适应滤波算法

针对带乘性噪声系统状态转移矩阵未知的情况,提出1种在线性最小方差意义下的系统参数和状态联合滤波算法。以迭代方式获得模型参数和系统状态的递推估计:首先,利用之前时刻的状态估计值,根据投影定理,对系统未知参数即系统状态转移矩阵作出估计;其次,利用已得到的系统参数估计值,获取当前时刻的状态滤波。计算机仿真结果表明了算法的有效性。     

通道特性相关时带乘性噪声系统的最优滤波

针对石油地震勘探、通讯工程、水声探测等许多实际应用领域 ,该文研究 1种在更弱的乘性噪声限制条件下系统的最优状态滤波 ,就乘性噪声矩阵为一般随机矩阵且各观测通道乘性噪声在同时刻相关的情形 ,给出了在线性最小方差意义下的状态最优滤波算法。针对该算法还进行了仿真研究 ,仿真结果表明了该算法的有效性。     

Data assimilation of partitioned HF radar wave data into Wavewatch III

In this study the assimilation of HF radar data into a high resolution, coastal Wavewatch III model is investigated. An optimal interpolation scheme is used to assimilate the data and the design of a background error covariance matrix which reflects the local conditions and difficulties associated with a coastal domain is discussed. Two assimilation schemes are trialled; a scheme which assimilates mean parameters from the HF radar data and a scheme which assimilates partitioned spectral HF radar data. This study demonstrates the feasibility of assimilating partitioned wave data into a coastal domain. The results show that the assimilation schemes provide satisfactory improvements to significant wave heights but more mixed results for mean periods. The best improvements are seen during a stormy period with turning winds. During this period the model is deficient at capturing the change in wave directions and the peak in the waveheights, while the high sea state ensures good quality HF radar data for assimilation. The study also suggests that there are both physical and practical advantages to assimilating partitioned wave data compared to assimilating mean parameters for the whole spectrum.     

Ant colony fuzzy neural network controller for cruising vessel on river

This paper proposes an ant colony fuzzy neural network (ACFNN) controller for a cruising vessel on a river. The proposed controller comprises an ant colony (AC) algorithm, a fuzzy neural network (FNN) controller, and a switching law. The approximately optimal sailing line and short sailing time are obtained using the AC algorithm. First, the searching pattern of the AC algorithm is constructed using the data of the tidal current, river current, vessel velocity, and position of the coordinate. From a tracking error viewpoint, the switching law determines that the approximately optimal sailing line and the shorter sailing time are obtained using the AC algorithm, and that uncertain nonlinear factors are compensated by the FNN controller. The controller consists of an FNN identifier and a robust controller. The identifier is used to estimate the vessel velocity, and its parameters are tuned online by the adaptive law derived from the Lyapunov function. The robust controller is used to compensate for uncertainties of the tidal current and river current through the estimated law. The output of the ACFNN controller is the sum of the FNN identifier, the robust controller, and an auxiliary function. Finally, a simulation and a practical cruising vessel on a river are performed to verify the effectiveness of the presented controller.     

Bayesian geoacoustic inversion for the Inversion Techniques 2001 Workshop

This paper applies a Bayesian formulation to range-dependent geoacoustic inverse problems. Two inversion methods, a hybrid optimization algorithm and a Bayesian sampling algorithm, are applied to some of the 2001 Inversion Techniques Workshop benchmark data. The hybrid inversion combines the local (gradient-based) method of downhill simplex with the global search method of simulated annealing in an adaptive algorithm. The Bayesian inversion algorithm uses a Gibbs sampler to estimate properties of the posterior probability density, such as mean and maximum a posteriori parameter estimates, marginal probability distributions, highest-probability density intervals, and the model covariance matrix. The methods are applied to noise-free and noisy benchmark data from shallow ocean environments with range-dependent geophysical and geometric properties. An under-parameterized approach is applied to determine the optimal model parameterization consistent with the resolving power of the acoustic data. The Bayesian inversion method provides a complete solution including quantitative uncertainty estimates and correlations, while the hybrid inversion method provides parameter estimates in a fraction of the computation time.     

一种基于四叉树的地形模型简化快速生成算法

本文对于地形的四叉树简化技术进行研究。根据给定限差，提出了一种判断各节点是否为叶节点的算法。该算法只要通过递归调用对原始数据扫描一次，就可十分快速和准确地判断该地形各节点是否分裂。另外，通过将较高分辨率节点的顶点移到相邻较低分辨率节点的边界上的方法消除裂缝。同时，进行了实验研究。结果表明，本文提出的算法结构简单，便于实现，实验效果良好。     

Limitations on the overlap-correlator method imposed by noise andsignal characteristics

Limitations on the performance of the overlap-correlator method of forming a passive synthetic aperture are derived. The technique uses the overlap of the array in sequential positions to estimate a series of phase correction factors that compensate for the motion of the array over time. It is of primary interest to optimize this overlap with respect to the effects of random noise. By minimizing the variance of the estimates of the set of phase correction factors, it is found that the optimal overlap is one-half the length of the physical array. Using this optimal overlap, the bounds on the usable spatial response are then determined as a function of signal-to-noise ratio and the number of hydrophones in the physical array. The ability of the overlap-correlator algorithm to synthesize a coherent aperture is investigated for the case of multiple sources in the absence of noise     

基于MPI的LAGFD-WAM海浪数值模式并行算法研究

在LAGFD-WAM海浪串行数值模式基础上,利用MPI信息传递机制实现其并行化。通过对模拟区域合理划分,对数据采取分块加载,实现了各个节点的负载平衡;通过对算法的改进实现了粗粒度计算,大幅度减少了通信量,从而提高了程序的执行效率。对串行计算和并行计算的效率比较表明,本文建立的方法能够得到较高的加速比。对全球海浪模式,加速比和CPU数目大致呈线性关系。对高分辨率的区域海浪模式,在128 CPU条件下加速比可以达到91.9。     

水体后向散射系数校正方法研究

后向散射系数是水色反演半分析模型的重要参数,后向散射系数的测量与分析是固有光学测量与分析的重要组成部分。为了更准确的获得后向散射系数数据,根据不同的实际测量情况提出了两种后向散射系数数据的校正方法,即利用散射与后向散射系数模型计算的散射系数替代法和实测数据替代法。结果表明这两种方法在比传统的数据校正方法有明显的优势,是一种符合水体剖面固有光学特性规律的数据校正方法。     

基于小波分析的海洋锋形态特征提取

遥感影像中海洋锋具有弱边缘(Weak Edge)信息特性,其空间尺度在不同的空间位置存在较大的差异。针对传统边缘算子只能提取某一尺度的海洋锋信息,而损失其他尺度信息不足,本文利用小波多尺度分析特性,探讨了海洋锋信息在各尺度间的分布的继承性,提出最佳尺度确定的算法框架,设计出最佳尺度确定算法的流程,进一步进行海洋锋各尺度信息的提取。最后以海面温度锋-墨西哥湾流为实例进行形态特征提取,并与典型的边缘提取算子效果在信息量、抗干扰性、定位精度、连续性和对比度上进行对比分析。试验结果表明了该算法在提取多尺度的海洋锋信息上的可行性和实用性。     

受扰线性系统的前馈-反馈最优控制

针对具有外部持续扰动的线性系统，研究前馈-反馈最优控制律的设计问题。给出了最优控制律的存在唯一性条件。并提出了最优控制律的设计算法。利用滤波器解决了前馈控制的物理不可实现问题。仿真结果表明，此算法易于实现，与传统的反馈最优控制相比对抑制外部扰动具有较强的鲁棒性。     

带乘性噪声系统的多尺度最优滤波融合算法

利用小波变换和多尺度分析的思想，将基于模型的动态系统分析和基于统计特性的多尺度信号变换方法相结合。提出了在线性最小方差意义下的带乘性噪声系统的多尺度最优滤波融合算法。并用计算机仿真说明了融合算法的有效性。