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kalman_intro_chinese.rar
- 卡尔曼滤波器是一个“optimal recursive data processing algorithm（最优化自回归数据处理算法）”。对于解决很大部分的问题，他是最优，效率最高甚至是最有用的。他的广泛应用已经超过30年，包括机器人导航，控制，传感器数据融合甚至在军事方面的雷达系统以及导弹追踪等等。近年来更被应用于计算机图像处理，例如头脸识别，图像分割，图像边缘检测等等。,Kalman filter is an " optimal recursive data processing
kaiman2
- 一个二维的卡尔曼滤波程序，给定了状态方程和观测方程，对学习信息融合，滤波估计灯方面有积极的知道效果-A two-dimensional Kalman filtering process, given the state equation and observation equation, the study of information fusion, filtering light area is estimated to know there is a positive effect
fusionANDwk
- 基于matlab的几个kalman滤波以及多传感器融合和wk算法的程序-Matlab based on several kalman filtering and multi-sensor fusion algorithm and procedures wk
altitude
- 无人机高度基于matlab卡尔曼滤波程序 数据融合-UAV height matlab-based Kalman filter data fusion procedure
MSDF
- 基于无味卡尔曼滤波的多传感器数据融合，采用UK方法进行采样，获得系统中未知参数的辨识。-Unscented Kalman filter based on the multi-sensor data fusion, using UK methods of sampling, access to the system to identify the unknown parameters.
UKFleida
- kalman滤波程序 关于信息融合方面的程序 -kalman programme about information fusion s programme
INS_GPS_integrated_navigation_system
- 通过卡尔曼滤波并采用开环控制方式实现惯性导航和GPS的数据融合-Through the Kalman filter and use the open-loop control method to achieve inertial navigation and GPS, data fusion
Achieving_integrity_in_an_INS_GPS_navigation_loop_
- 本文主要介绍了用模糊自适应卡尔曼滤波技术实现惯导和GPS的数据融合。-This paper presents a fuzzy adaptive Kalman filter technology for inertial navigation and GPS-data fusion.
Kalmanandwinner
- 基于现代时间序列的多传感器信息融合Kalman滤波器与Wiener滤波器.NH格式论文-data fusion using kalman and winner filter
imustabilizer_090219
- (UAV) has grown rapidly over the past decade. UAV applications range from purely scientific over civil to military. Technical advances in sensor and signal processing technologies enable the design of light weight and economic airborne platform
kalman.1.3
- KALMAN滤波算法的实现，可用于天气数据纠正，以及POS数据融合等-KALMAN filtering algorithm, can be corrected for weather data, and POS data fusion
Data-Fusion
- 关于数据融合以及卡尔曼滤波器的文章，在测控系统中的应用-Data fusion and Kalman filter
2010041245
- 上传一个word档的联邦式扩展卡尔曼粒子滤波算法，大家学习粒子滤波有益，为了使联邦滤波器够有效处理非高斯、非线性系统的状态估计问题，提出将扩展卡尔曼粒子滤波引入联邦滤波结构中，得到一种新的联邦式扩展卡尔曼粒子滤波算法.使用扩展卡尔曼粒子滤波对联邦滤波子系统的多源数据进行处理，从而摆脱了经典卡尔曼滤波的限制，拓宽了联邦滤波器的实际应用范围.将联邦式扩展卡尔曼粒子滤波算法应用于非线性滤波器的一个标准验证模型进行了仿真实验，结果表明该算法是有效性的.-Abstract: A new particle
GPS_SINS
- 捷联惯导系统的导航算法，采用卡尔曼滤波对惯性信息和GPS信号进行融合，进行噪声处理-SINS navigation algorithm, Kalman filtering fusion of inertial information and GPS signal, noise processing
(EKF)-data-fusion
- 扩展卡尔曼滤波（EKF）实验报告,有详细代码和详细报告，可运行。有需要拿去-Extended Kalman filter (EKF) lab reports, detailed code and detailed reports can be run. The need to take
kalman
- 卡拉曼滤波是估计的基础，在信息融合中处于重要地位，且是入门必会的-Karaman filtering is estimated to be in an important position in the information fusion and entry will be the
Data-Fusion-Approach-for-Altitude-Location-Error.
- 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
Kalman
- 使用EKF（扩展卡尔曼滤波）解算姿态，加速度计、陀螺仪数据融合(EKF (extended Calman filtering) is used to solve the attitude, accelerometer and gyroscope data fusion)
SINS-GPS kalman
- SINS数据和GPS数据融合的kalman算法(Kalman Algorithm for Fusion of SINS Data and GPS Data)
kalman
- 静态数据和动态数据融合的kalman算法(Kalman algorithm for the fusion of static data and dynamic data)