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.     

几种非线性滤波算法的性能比较与分析

在非线性状态估计中,传统的扩展卡尔曼滤波通过线性化来实现高斯近似,由于截断误差的存在很难保证估计精度;而基本粒子滤波容易出现粒子退化,导致滤波发散。针对粒子滤波的两个基本假设：蒙特卡罗假设和重要采样假设,采用蒙特卡罗随机链的方法来提高粒子的多样性,并利用无味卡尔曼滤波来产生更高精度的替代分布,发展了无味粒子滤波。通过仿真实验证明,相比较扩展卡尔曼滤波和基本粒子滤波,改进后的无味粒子滤波算法性能更优越,对含有非线性非高斯的状态估计问题有更好的滤波效果。     

Application of Linear Mean-Square Estimation in Ocean Engineering

The attempt to obtain long-term observed data around some sea areas we concern is usually very hard or even impossible in practical offshore and ocean engineering situations. In this paper, by means of linear mean-square estimation method, a new way to extend short-term data to long-term ones is developed. The long-term data about concerning sea areas can be constructed via a series of long-term data obtained from neighbor oceanographic stations, through relevance analysis of different data series. It is effective to cover the insufficiency of time series prediction method’s overdependence upon the length of data series, as well as the limitation of variable numbers adopted in multiple linear regression model. The storm surge data collected from three oceanographic stations located in Shandong Peninsula are taken as examples to analyze the number-selection effect of reference oceanographic stations (adjacent to the concerning sea area) and the correlation coefficients between sea sites which are selected for reference and for engineering projects construction respectively. By comparing the N-year return-period values which are calculated from observed raw data and processed data which are extended from finite data series by means of the linear mean-square estimation method, one can draw a conclusion that this method can give considerably good estimation in practical ocean engineering, in spite of different extreme value distributions about raw and processed data.     

多波束条带测深仪的动态测量误差评估

对于近年发展起来的多波束条带测深仪,其动态测量误差的评估是一项尚未完善解决的课题。本文提出了一种多波束条带测深仪动态测量误差的评估方法,并用海试结果证明了该方法的实用有效性。该方法可以推广应用到其它多波束测量声呐系统的动态测量误差分析与估计中。     

基于杨赤中插值法的坡度、坡向计算的实现与分析

应用杨赤中滤波推估法,将地形碎部点高程观测值看作一种包含规律性和随机性变化的复合变量,求其二项系数加权游动平均,建立估值数学模型,求得各格网点高程估值。将离散的数据经插值计算转换为DEM数据,并根据其网格顶点来分析、推算和显示网格单元的坡度和坡向。     

Robust LS-SVM regression for ore grade estimation in a seafloor hydrothermal sulphide deposit

Due to the geological complexities of ore body formation and limited borehole sampling, this paper proposes a robust weighted least square support vectormachine (LS-SVM) regression model to solve the ore grade estimation for a seafloor hydrothermal sulphide deposit in Solwara 1, which consists of a large proportion of incomplete samples without ore types and grade values. The standard LS-SVM classification model is applied to identify the ore type for each in complete sample. Then, a weighted K-nearest neighbor (WKNN) algorithm is proposed to interpolate the missing values. Prior to modeling, the particle swarm optimization (PSO) algorithm is used to obtain an appropriate splitting for the training and test data sets so as to eliminate the large discrepancies caused by randomdivision. Coupled simulated annealing (CSA) and grid search using 10-fold cross validation techniques are adopted to determine the optimal tuning parameters in the LS-SVM models. The effectiveness of the proposed model by comparing with other well-known techniques such as inverse distance weight (IDW), ordinary kriging (OK), and back propagation (BP) neural network is demonstrated. The experimental results show that the robust weighted LS-SVM outperforms the othermethods, and has strong predictive and generalization ability.     

Acoustic estimations of porosity and thickness for thin soft surface layer of sea floor

Abstract

In some areas, the sea floor contains a surface layer with high porosity and a thickness of 10–30 cm. The characters of an explosive pulse reflected at such a sea floor are discussed. The thickness and porosity estimations for the surface layer by acoustic method are studied, and the estimated and measured results are listed.     

消除EMD 边界效应的四中点估计方法

为了快速高效地实现信号的本征模态分解,消除分解过程中边界效应,在 Directly-Mean EMD方法的基础上,通过引入左、右待估中点和左、右延拓中点,并根据信号首尾两端各种可能的情况给出了四中点估计公式,建立了可完全消除边界效应的Directly-Mean EMD四中点估计方法。该方法不仅减少了样条插值次数,提高分解速度,而且还可以有效避免因插值节点过于稀疏所产生的大幅波动,使分解结果更加准确。将新方法应用于日长数据序列的本征模态函数分解,得到了满意的分解结果。     

Discrete time-delay control of an autonomous underwater vehicle: Theory and experimental results

A discrete time-delay control (DTDC) law for a general six degrees of freedom unsymmetric autonomous underwater vehicle (AUV) is presented. Hydrodynamic parameters like added mass coefficients and drag coefficients, which are generally uncertain, are not required by the controller. This control law cancels the uncertainties in the AUV dynamics by direct estimation of the uncertainties using time-delay estimation technique. The discrete-time version of the time-delay control does not require the derivative of the system state to be measured or estimated, which is required by the continuous-time version of the controller. This particularly provides an advantage over continuous-time controller in terms of computational effort or availability of sensors for measuring state derivatives, i.e., linear and angular accelerations. Implementation issues for practical realization of the controller are discussed. Experiments on a test-bed AUV were conducted in depth, pitch, and yaw degrees of freedom. Results show that the proposed control law performs well in the presence of uncertainties.