Kalman滤波器在船舶动力定位系统中的应用

近年来,世界各国对海洋资源的探索不断深入,为了开发海洋丰富的化石燃料等自然资源,世界上的发达国家建设了大量的海洋工程,同时,对海上作业平台和舰船的定位精度和稳定性的要求越来越高。动力定位系统随时受到海上环境的干扰作用力,是一个非线性运动系统,借助自身推进力抵消环境中的干扰作用力,干扰作用力可以分为低频和高频干扰,因此,干扰作用力的滤波在船舶动力定位系统具有重要意义。本文重点介绍一种Kalman滤波算法,基于船舶动力系统的运动模型,研究了动力定位系统的干扰作用力滤波流程。     

改进区间Kalman滤波器及其在船舶组合导航中的应用

具有执行简便和高精度优点的测量值融合技术已经在船舶组合导航中得到了广泛应用。但由于船舶组合导航系统中各子系统模型参数的不确定性,传统的多传感器数据融合算法状态估计精度难以保证,因此提出了一种多传感器数据融合的改进算法。该改进算法不仅具有常规区间Kalman滤波器的鲁棒性,而且实用性较强。其具有如下特点：将所有系统不确定性和观测不确定性等效为系统噪声和观测噪声的不确定性,简化了系统模型;采用一种较为简单的区间矩阵综合求逆方案;利用时变马尔可夫模型在线调整滤波输出加权系数。仿真结果表明：该改进算法的状态估计精度较高。     

船舶机舱噪声控制

随着船舶朝大型、高速方向发展，其机舱内推进主机和柴油发电机组的噪声问题越来越严重。本文对机舱内噪声的综合治理方法，如对推进主机进行隔振、安装进排气消声器；对柴油发电机组安装进排气消声器、使用隔声罩；在机舱内粘贴吸声材料以降低混响噪声等作了介绍。通过综合治理，可使机舱内噪声降低40dB以上，甲板上噪声降低26dB以上，取得了很好的控制效果。     

船舶操作及机舱监控模拟系统

随着计算机仿真技术的不断发展,基于计算机仿真的船舶操纵与监控模拟系统的开发引起了广泛重视,通过搭建船舶操作与监控模拟系统,可以使船舶工作人员的培训成本和周期缩短,也可以避免实船培训带来的危险因素。本文分别从船舶操作及机舱监控模拟系统的整体组成、模拟系统的数据库技术、模拟操作的运动建模和系统的硬件组成等方面进行研究。     

新型船舶机舱监测报警和控制系统分析

基于CAN总线的Datachief C20监测报警和控制系统集中体现了当前船舶机舱监控技术的先进水平.文中介绍了CAN总线技术的原理和特点,讨论了Datachief C20系统的结构组成及丰富的监控功能,总结了此系统优异的特性,并指出该系统在船舶自动化领域将有广阔的应用前景.     

采用混合动力的船舶机舱牵引变流器监控网络研究与应用

近年来,混合动力逐渐成为船舶动力变革的趋势。牵引变流器是混合动力船舶的核心设备,在船舶运行过程中,需要建立监控网络对变流器设备进行实时监控。本文研究牵引变流器、监控网络以及CAN网络的组成原理和影响因素,然后,根据动、静态CAN网络调度算法的优缺点提出改进的CAN网络调度算法,提高了监控网络的性能。     

船舶机舱监测系统设计

为及时掌握船舶动力装置的运行状况,为维修提供决策抗据,设计基于CAN现场总线的船舶机舱监测系统的数据采集节点,介绍监测系统的软、硬件组成和功能,该系统具有通信速率高、可靠性高、连接方便和性价比高的特点,适合船舶机舱监测.     

船舶机舱防暑降温点滴

船舶机舱夏季工作条件恶劣，气温可接近50℃，噪音可高达120分贝，轮机人员面临高温、高湿、高噪音的严竣考验。     

Wave data assimilation with the Kalman filter

A new data assimilation method for ocean waves is presented, based on an efficient low-rank approximation to the Kalman filter. Both the extended Kalman filter and a truncated second-order filter are implemented. In order to explicitly estimate past wind corrections based on current wave measurements, the filter is extended to a fixed-lag Kalman smoother for the wind fields. The filter is tested in a number of synthetic experiments with simple geometries. Propagation experiments with errors in the boundary condition showed that the KF was able to accurately propagate forecast errors, resulting in spatially varying error correlations, which would be impossible to model with time-independent assimilation methods like OI. An explicit comparison with an OI assimilation scheme showed that the KF also is superior in estimating the sea state at some distance from the observations. In experiments with errors in the driving wind, the modeled error estimates were also in agreement with the actual forecast errors. The bias in the state estimate, which is introduced through the nonlinear dependence of the waves on the driving wind field, was largely removed by the second-order filter, even without actually assimilating data. Assimilation of wave observations resulted in an improved wave analysis and in correction of past wind fields. The accuracy of this wind correction depends strongly on the actual place and time of wave generation, which is correctly modeled by the error estimate supplied by the Kalman filter. In summary, the KF approach is shown to be a reliable assimilation scheme in these simple experiments, and has the advantage over other assimilation methods that it supplies explicit dynamical error estimates.     

GPS/INS松耦合组合导航的自适应卡尔曼滤波算法研究

  目的  为解决载体受到扰动时组合导航精度下降的问题,提出一种基于置信检验自适应联邦卡尔曼滤波（CC-AFKF）框架。  方法  首先,将电子罗盘（EC）、全球定位系统（GPS）与惯性导航系统（INS）相结合;其次,构建置信检验模型,有效滤除INS/GPS和INS/EC子系统中低置信度的量测值,保证量测值的准确性;最后,提出INS/GPS和INS/EC系统自适应调节因子策略,有效调整更新过程中系统噪声协方差。  结果  通过对具备INS/GPS/EC组合导航系统的水下机器人开展大量相关试验,结果表明,CC-AFKF算法相较于典型的卡尔曼滤波（KF）和联邦卡尔曼滤波（FKF）算法在位置和速度的融合精度上均能至少提高29%。  结论  研究成果可为松耦合组合导航系统的研究提供相应的方向和思路。     

卡尔曼滤波在潜艇垂直面运动控制器设计中的应用

潜艇低噪声操纵存在无效用舵现象。简要介绍了滤波信号的表示形式,在潜艇垂直面线性运动方程的基础上,得出了滤波信号的系统模型,并对其进行了离散化处理;将均方差最小线性递推滤波算法引入到输入信号的控制过程中,通过仿真证明对输入信号进行卡尔曼滤波能够提高输入信号的品质,用于工程应用。     

Application of an Ensemble Kalman filter to a 1-D coupled hydrodynamic-ecosystem model of the Ligurian Sea

The Ensemble Kalman filter (EnKF) has been applied to a 1-D complex ecosystem model coupled with a hydrodynamic model of the Ligurian Sea. In order to improve the performance of the EnKF, an ensemble subsampling strategy has been used to better represent the covariance matrices and a pre-analysis step for correcting the non-normality of the members distribution has been implemented. Twin experiments have been realized to assess the performance of the developed tool and a real data assimilation experiment has been conducted to hindcast the ecosystem at the Dyfamed site during the year 2000. Finally the performance of the EnKF has been compared with a Singular Evolutive Extended Kalman (SEEK) filter with a fixed basis. We conclude that, on one hand, there is a benefit in using the subsampling strategy and the lognormal transformation with the EnKF, and on the other hand, this filter presents better performance than the fixed basis version of the SEEK filter. However, it also incurs a large computational cost.     

基于Unscented卡尔曼滤波器的地磁辅助组合导航

将船位推算与地磁测量相结合构成组合导航方法.首先建立了推算模型,然后利用Unscented卡尔曼滤波方法,直接将地磁测量的结果用于校正推算结果,进行导航定位.此方法不采用匹配方法进行定位,可进行实时定位,能适用于非线性和离散的地磁模型.仿真表明,此方法能减小定位误差,适用于基于船位推算和地磁定位的实时组合导航.     

低成本AHRS中Kalman滤波器的降维状态观测器设计

最优控制系统如捷联惯导系统（AHRS）都离不开状态反馈。然而系统的状态变量并不都是易于直接检测到的，这就需要状态观测器。基于减轻导航计算机计算负担和降低成本的考虑，提出Kalman滤波器的降维观测器的设计，并且讨论了误差模型的噪声补偿和降低估值误差的方法。     

一种改进的卡尔曼滤波定位算法研究

研究了一种改进的卡尔曼滤波导航信号定位算法:通过测量每次接收机得到的伪距观测量及伪距变化量,估算出接收机的位置、速度,实现无线电导航系统的定位解算.该方法不直接使用卡尔曼滤波器来估计载体的状态,而是用滤波器来确定状态的误差,减小了运算误差,有效提高了定位精度.在进行参数估计时不需要贮存大量的测量数据,能够方便地进行动态测量数据的实时处理.该方法已经应用在导航定位解算中,仿真结果和实际应用验证了该方法具有快的收敛速度和高的定位精度.     

Data assimilation with the Ensemble Kalman Filter and the SEIK filter applied to a finite element model of the North Atlantic

Currently there are different approaches to filter algorithms based on the Kalman filter. One of the most used filter algorithms is the Ensemble Kalman Filter (EnKF). It uses a Monte Carlo approach to the filtering problem. Another approach is given by the Singular Evolutive Extended Kalman (SEEK) and Singular Evolutive Interpolated Kalman (SEIK) filters. These filters operate explicitly on a low-dimensional error space which is represented by an ensemble of model states. The EnKF and the SEIK filter have been implemented within a parallel data assimilation framework in the Finite Element Ocean Model FEOM. In order to compare the filter performances of the algorithms, several data assimilation experiments are performed. The filter algorithms have been applied with a model configuration of FEOM for the North Atlantic to assimilate the sea surface height in twin experiments. The dependence of the filter estimates on the represented error subspace is discussed. In the experiments the SEIK algorithm provides better estimates than the EnKF. Furthermore, the SEIK filter is much cheaper in terms of computing time.     

六相同步电机控制系统在船舶电力推进中的应用

船舶电力推进在船舶海上行进过程中具有高效性、灵活性等优点。本文通过研究六相同步电机控制系统来分析其推进性能。首先建立相坐标系和旋转坐标系下的六相同步电机控制数学模型,然后在船桨一体化负载下进行系统仿真,通过仿真曲线来说明本文控制的有效性。