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matlab状态方程的设计和一个自己编的小小的filter文件请指教！！1-Matlab equation of state of their own design and a series of small filter paper please enlighten! ! 1
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卡尔曼滤波程序，两变量滤波；正弦信号跟踪；卡尔曼差分到状态方程的转换；卡尔曼同滑动平均比较,Kalman filtering process, the two variable filter sinusoidal signal tracking Kalman differential equation of state of the conversion Kalman compared with moving average
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集合卡尔曼滤波(EnKF) 数据同化方法可以避免了EKF 中协方差演变方程预报过程中出现的计算不准确和关于协方差矩阵的大量数据的存储问题,最主要的是可以有效的控制估计误差方差的增长,改善预报的效果。-Ensemble Kalman Filter (EnKF) data assimilation methods can be avoided in the EKF covariance forecasting the evolution equation arising in the course
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卡尔曼滤波的vb源程序(现设线性时变系统的离散状态防城和观测方程)-Kalman Filter vb source (now based linear time-varying systems of discrete state Fangcheng and observation equation)
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THIS PROGRAM IS FOR IMPLEMENTATION OF DISCRETE TIME PROCESS UNSCENTED KALMAN FILTER FOR GAUSSIAN AND LINEAR STOCHASTIC DIFFERENCE EQUATION.
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Ensemble Kalman Filter (EnKF) data assimilation methods can be avoided in the EKF covariance forecasting the evolution equation arising in the course of the calculation is not accurate and on the covariance matrix of a large amount of data storage pr
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建立了捷联管道系统初始对准的误差模型和卡尔曼滤波模型观测方程，进行了卡尔曼滤波仿真。-The error function for initial alignment of SINS and the observation equation of Kalman filter model is built．Simulation of Kalman filter presented．
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EKF仅仅利用了非线性函数Taylor展开式的一阶偏导部分（忽略高阶项），常常导致在状态的后验分布的估计上产生较大的误差，影响滤波算法的性能，从而影响整个跟踪系统的性能。最近，在自适应滤波领域又出现了新的算法——无味变换Kalman滤波器（Unscented Kalman Filter-UKF）。UKF的思想不同于EKF滤波，它通过设计少量的σ点，由σ点经由非线性函数的传播，计算出随机向量一、二阶统计特性的传播。因此它比EKF滤波能更好地迫近状态方程的非线性特性，从而比EKF滤波具有更高的估计精
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姿态信息是飞行控制中最关键的参数之一,因此姿态测量成为飞行控制系统首要解决的问题。利用多MEMS传感器研制了一种微型姿态测量系统。利用三轴MEMS加速度计和三轴MEMS陀螺数据,由方向余弦矩阵的姿态表示形式推导了扩展Kalman滤波方程,解算出飞行器的俯仰角和横滚角 设计专家系统判断飞行器的运动状态,并根据该状态调整滤波算法中的测量噪声矩阵,使系统可同时满足静态情况和动态情况的使用 利用空速和高度数据对俯仰角进行修正,利用GPS解算航向角。将实验结果与国外最新
的商用自动驾驶仪的姿态结果进行
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kalman正弦信号跟踪： 红色为原始状态输出；绿色为量测方程输出；黑色为状态方程输出；蓝色为卡尔曼滤波输出-kalman tracking sinusoidal signals: red output to its original state green measurement equation output black output for the equation of state blue for the Kalman filter output
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利用kalman滤波算法对状态空间描述的位移测量系统进行了滤波处理，对系统输出的真实位移、测量位移和滤波位移进行了对比，显示了kalman滤波算法较好的滤波性能。-Displacement measurement system described by the equation of states were filtered by Kalman filter algorithm. The output of the system, including the real displacement,
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设一个系统的真实值为余弦函数，加入的系统过程噪声和测量噪声都满足正态分布，状态方程和量测方程都是线性的，用卡尔曼滤波求出最优结果-Set up a system of real value cosine function, the process of adding system noise and measurement noise are normally distributed, the state equation and measurement equation is linear,
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用非线性kalman filter，也就是扩展kalman filter 实现对非线性状态方程的估计，能够很好地追踪目标。-Nonlinear kalman filter, which is extended kalman filter to achieve the estimated nonlinear equation of state can be a good track targets.
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这个是自适应卡尔曼滤波的程序，可以不用已知观测方程以及状态方程的噪声，能够在滤波时学习出-This is an adaptive Kalman filtering program that can do the known equations of state and noise measurement equation can learn while filtering out
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卡尔曼滤波(Kalman filtering)一种利用线性系统状态方程，通过系统输入输出观测数据，对系统状态进行最优估计的算法。本程序使用opencv进行卡尔曼滤波。-Kalman filter (Kalman filtering) A linear system equation of state, observation data input and output through the system, the system state optimal estimation algorith
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该文件用于编写无迹卡尔曼滤波算法及其测试主要子程序包括：轨迹发生器、系统方程测量方程、UKF滤波器-Kalman filter algorithm and its main routine test used to write the file without a trace comprising: trajectory generator, system of equations measurement equation, UKF filter
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卡尔曼滤波(Kalman filtering)一种利用线性系统状态方程，通过系统输入输出观测数据，对系统状态进行最优估计的算法。由于观测数据中包括系统中的噪声和干扰的影响，所以最优估计也可看作是滤波过程。(Kalman filtering, Kalman filtering) a system of linear equation of state, through the system input and output data, the optimal estimation of the s
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基于卡尔曼滤波对现有采样数据进行滤波，有效降低观测值的误差。卡尔曼滤波是一种时域方法，它把状态空间的概念引入随机估计理论，用状态方程、观测方程和噪声激励递推估计测量噪声，便于实现实时应用。(The existing sampled data is filtered based on Kalman filter, which can effectively reduce the error of the observed value. Kalman filtering is a time doma
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卡尔曼滤波（Kalman filtering）一种利用线性系统状态方程，通过系统输入输出观测数据，对系统状态进行最优估计的算法。由于观测数据中包括系统中的噪声和干扰的影响，所以最优估计也可看作是滤波过程。(Calman filter (Kalman filtering) uses the state equation of linear system and optimally estimates the state of the system by input and output obser
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容积卡尔曼滤波测量方程基于统计数据，利用蒙特卡罗方法抽取私家电动汽车一次出行里程数，根据电池充电特性及车辆行驶习惯获得电动汽车充电的起始荷电状态、充电功率和起始充电时间，建立了一个较为精确的预测无线充电私家电动汽车充电负荷的数学模型，(The volume Calman filter measurement equation is based on the statistical data, using Monte Carlo method to extract the first trip m
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