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在对船用陀螺漂移数据建立时间序列模型的基础上，采用卡尔曼滤波算法对捷联陀螺漂移数
据进行了处理，以提高陀螺静态漂移误差系数的估计精度，并把得到的陀螺漂移误差模型实时补偿到捷联系统中，得到了满意的效果。-Marine gyro drift in the data time series model based on the Kalman filter algorithm using inertial gyro drift data were processed to enhance the g
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Calculates adaptive autoregressive (AAR) and adaptive autoregressive moving average estimates (AARMA)of real-valued data series using Kalman filter algorithm.
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数字罗盘实时接收姿态角数据，并用卡尔曼滤波处理后的曲线显示-Receive real-time digital compass attitude angle data, and treated with the Kalman filter and show the curves
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To model the robot position we wish to know its x and y coordinates and its
orientation. These three parameters can be combined into a vector called a state
variable vector. The robot uses beacon distance and angle measurements and
locomotion i
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实现卡尔曼滤波，可以看出，滤波过程是以不断地“预测—修正”的递推方式进行计算，先进行预测值计算，再根据观测值得到的新信息和kalman 增益（加权项），对预测值进行修正。由滤波值可以得到预测，又由预测可以得到滤波，其滤波和预测相互作用，并不要求存储任何观测数据，可以进行实时处理。-Kalman filtering, can be seen, the filtering process is constantly " forecast- Fixed" recursive mann
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可以看出，滤波过程是以不断地“预测—修正”的递推方式进行计算，先进行预测值计算，再根据观测值得到的新信息和kalman 增益（加权项），对预测值进行修正。由滤波值可以得到预测，又由预测可以得到滤波，其滤波和预测相互作用，并不要求存储任何观测数据，可以进行实时处理。-It can be seen, the filtering process is constantly " forecast- Fixed" recursive manner calculated to predic
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Calculates adaptive autoregressive (AAR) and adaptive autoregressive moving average estimates (AARMA) of real-valued data series using Kalman filter algorithm.
REFERENCE:
A. Schloegl (2000), The electroencephalogram and the adaptive autoregre
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卡尔曼滤波器的算法C实现
最佳线性滤波理论起源于40年代美国科学家Wiener和前苏联科学家Ｋолмогоров等人的研究工作，后人统称为维纳滤波理论。从理论上说，维纳滤波的最大缺点是必须用到无限过去的数据，不适用于实时处理。为了克服这一缺点，60年代Kalman把状态空间模型引入滤波理论，并导出了一套递推估计算法，后人称之为卡尔曼滤波理论。卡尔曼滤波是以最小均方误差为估计的最佳准则，来寻求一套递推估计的算法，其基本思想是：采用信号与噪声的状态空间模型，利用前一时刻地估计值和现时刻的观测值来
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Altitude location for UAV by using federated filter
is discussed, the fourth structure is selected, because its two
sub-filters involving altitude sensor and the difference Global
Positioning System (d-GPS) respectively are fully isolated from
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用卡尔曼滤波对一段相位差及其变化率数据进行滤波处理,给出结果并与真实的相位差变化率数据进行仿真对比.结果说明卡尔曼滤波有效-Kalman filter for a period of phase change rate data filtering and processing, given the results of phase with the real rate of change of the simulation data comparison results illustrate
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Headtracker using sensors: ADXL345 (acc), ITG3200 (gyro), HMC5843 (mag) with data fusion using an extended kalman filter on STM32F10x and data output via USB to PC. Code (sensor reading, filter) written by me. Validated on real hardware.
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Hi
I like to integrate GPS and INS using kalman filter to predict the
position of a vehicle.
first of all i like to use GPS sensor readings with kalman filter .
I have read lot of research papers for that purpose but I donot know how
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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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数据滤波是去除噪声还原真实数据的一种数据处理技术, Kalman滤波在测量方差已知的情况下能够从一系列存在测量噪声的数据中，估计动态系统的状态. 由于, 它便于计算机编程实现, 并能够对现场采集的数据进行实时的更新和处理(Data filtering is to remove noise and a data processing technique of real data reduction, Kalman filter can from a series of measurement no
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