System structure and calibration models of intelligent photogrammetron

This paper describes the structure, geometric model and geometric calibration of Photogrammetron I—the first type of photogrammetron which is designed to be a coherent stereo photogrammetric system in which two cameras are mounted on a physical base but driven by an intelligent agent architecture. The system calibration is divided into two parts: the in-lab calibration determines the fixed parameters in advance of system operation, and the in-situ calibration keeps tracking the free parameters in real-time during the system operation. In a video surveillance set-up, prepared control points are tracked in stereo image sequences, so that the free parameters of the system can be continuously updated through iterative bundle adjustment and Kalman filtering.     

OpenCV开源库在核数据信息处理中的应用

介绍了OpenCV开源库在核数据谱线数据处理中的应用,使用OpenCV实现了谱线光滑、寻峰,以及卡尔曼滤波常用的谱处理方法。对492条256道谱线的NASVD算法的测试的结果表明,使用OpenCV方法的运算时间仅约为传统C＋＋方法的1／3,大大提升了数据处理的效率,在核数据处理中具有很好的应用前景和价值。     

卡尔曼滤波算法的灰色理论模型在变形监测中的应用

本文针对灰色理论模型在建模过程中受到随机扰动影响这一问题,提出了利用卡尔曼滤波处理建模数据的方法.经过实例检验,证明基于滤波算法的灰色理论模型在一定程度上可以提高预测值的精度,更好地反映了观测目标的变形趋势,在变形监测中具有一定的优势.     

抗差自适应卡尔曼滤波在GPS精密单点定位中的应用

卡尔曼滤波是GPS精密单点定位中最常用的参数估计方法.理论上讲,随着观测数据的增多,通过卡尔曼滤波可以得到更精确的状态估值,但有时由于状态异常或发生大的周跳等原因,使得状态估值与实际状态之间的误差较大,滤波会发生发散现象,为此,本文提出了将抗差自适应滤波模型运用到精密单点定位中,通过算例分析显示,该方法将显著提高定位结...     

基于Kalman滤波的动力学模型误差估计算法

本文分析介绍了模型误差对滤波解和预报残差影响的表达式.随后,针对GPS/INS松组合导航系统观测信息无冗余的情况,给出了基于Kalman滤波的动力学模型误差估计算法.最后利用一个车载实测数据证明了算法的有效性.     

基于"当前"统计模型的载体速度计算

本文通过分析描述载体运动的"当前"统计模型,设计了基于"当前"统计模型计算载体速度的自适应卡尔曼滤波算法.利用航空飞行实验中获得的相位观测值,进行时序差分得出相位率,并对其组双差,获得计算速度的双差多普勒频移值,使用设计的算法进行计算分析,同时与常加速度模型的滤波结果做了比较.结果表明在静态和动态情况下,"当前"统计模...     

动态非线性滤波模型非线性强度的曲率度量及其应用

基于微分几何的两种曲率——参数影响曲率和固有曲率,给出了定量描述非线性滤波问题的非线性强度的方法,分别采用扩展Kalman滤波方法和Unscented Kalman滤波方法进行了模拟实验。结果验证了这些曲率确实能够度量非线性滤波问题的非线性强度,且能够评估非线性滤波算法的状态估计性能。     

GPS非差相位动态定位中Sage自适应滤波算法的研究及软件实现

介绍了GPS非差定位中的卡尔曼滤波模型,详细分析了滤波发散的原因.研究并给出了一种改进的自适应滤波,在此基础上编制了相应的软件,结合实例分析了该方法的有效性.     

Robust coordinated motion control of an underwater vehicle-manipulator system with minimizing restoring moments

For autonomous manipulation in water, an underwater vehicle-manipulator system (UVMS) should be able to generate trajectori9es for the vehicle and manipulators and track the planned trajectories accurately. In this paper, for trajectory generation, we suggest a performance index for redundancy resolution. This index is designed to minimize the restoring moments of the UVMS during manipulation, and it is optimized without impeding the performance of a given task. As a result, the restoring moments of the UVMS are decreased, and control efforts are also reduced. For tracking control of the UVMS, a nonlinear H_∞ optimal control with disturbance observer is proposed. This control is robust against parameter uncertainties, external disturbances, and actuator nonlinearities. Numerical simulations are presented to demonstrate the performance of the proposed coordinated motion control of the UVMS. The results show that control inputs for tracking are reduced, and the UVMS can successfully track generated trajectories.     

Algorithms for automatic,real-time tsunami detection in wind–wave measurements Part I: Implementation strategies and basic tests

Several, although not all, wind–wave gages are equipped with sensors capable of detecting sea-level oscillations within the tsunami frequency band. The present paper looks at the algorithms to be implemented in the software of these gages in order to automatically perform the real-time detection of a possible tsunami within recorded signals. In particular, a new algorithm is proposed and tested. The first part of the paper concentrates on the algorithms' characteristics, implementation strategies and basic testing. First of all, the situations in which wind–wave measurements are either essential, or useful for real-time tsunami detection are discussed. In the second place, already existing algorithms are recalled, specifying their characteristics and fields of application. Then, the characteristics of the new proposed algorithm – mainly based on an infinite impulse response, time domain filter – are illustrated and analyzed. Performance and efficiency of the considered algorithms are compared using synthetic time series. The second part of the paper discusses the algorithms' use in the framework of Tsunami Early Warning Systems (TEWS), testing them in actual cases.