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kalmanestimate
- Kalman滤波在状态估计中的matlab编程，Kalman滤波是状态估计中比较常用的方法，可用于连续系统的状态估计-Kalman filter state estimation in the matlab programming, Kalman filter is more commonly used in state estimation method, can be used for continuous system state estimation
YuErjian_power-system
- 《电力系统状态估计》于尔铿 电科院于尔铿老师的《电力系统状态估计》一书是电力系统状态估计的经典著作，但因为是专业书籍，年代也比较早，一般的书店很难有卖- --" Power System State Estimation" in Erkeng EPRI in Erkeng teacher' s " power system state estimation," a book is a classic power system state est
kftry
- 卡尔曼滤波算法是一种状态估计算法，它是最小二乘法的特殊形式，所以，卡尔曼滤波算法也能做系统辨识，这个代码是自己写的，基于卡尔曼滤波算法的系统辨识，希望对大家有用-Kalman filter algorithm is a state estimation algorithm, which is a special form of least squares method, so the Kalman filter algorithm can do system identification, th
multi-target-tracking
- 多目标跟踪的主程序，包含跟踪起始，数据关联，目标状态估计等过程-The main process of multi-target tracking, including track initiation, data association, target state estimation process
An-improved-variable-
- 一种改进的变参数粒子群优化算法，该方法以进化状态因子计算策略和进化状态估计模型-An improved particle swarm optimization variable parameters, the method to calculate evolutionary strategies and evolutionary state factor model of state estimation
particalCode
- This function demonstrates a simple implementation of the basic particle filter. It follows faithfully the first example from the paper: 'Novel Approach To Nonlinear/Non-Gaussian Bayesian State Estimation' by Gordon et al.
DATA-FUSION4
- H-∞滤波理论在多传感器信息融合状态估计中的应用研究方面的一篇博士论文，值得一看-H-∞ filtering theory in multi-sensor information fusion state estimation of Applied Research
0999
- 卡尔曼滤波是一种数据处理方法，它是一种线性最小方差无偏估计准则，基于系统 状态估计和当前观测，通过引入状态空间而获得的新的状态估计.本篇论文陈述了卡尔曼滤 波的基本思路和算法；并通过仿真，显示卡尔曼滤波的功能，以及如何用它来跟踪方向确定、速度恒定的飞行器。-Kalman filter is a data processing method, which is a linear minimum variance unbiased estimation criteria, based on
alphaBetaFilter
- The function alphaBetaFilter implements a generic algorithm for an alpha-beta filter that is a linear state estimation for position and velocity given an observed data. It acts like a smoothing. Also closely related to Kalman filters and to linear st
TransformerHse
- 变电站谐波状态估计程序，通过量测两个节点的电压和电流，计算得到另一个节点的电压电流相量，两个量测节点相角不同步，以一个节点相角为基准。-Substation harmonic state estimation procedure, by measuring the voltage and current of two nodes, one node is calculated voltage and current phasor, two phase angle measurement node
WLS
- 用最小二乘法进行电力系统状态估计，包含IEEE30节点的电力系统图-Using least squares power system state estimation, including IEEE30 bus power system diagram
QuadRotor_MA8.2
- MB8四旋翼自动驾驶仪的源码，包括姿态采集，状态估计以及控制输出。不推荐直接使用，但是可以作为学习-MB8 four rotor autopilot source, including posture acquisition, state estimation and control output. Not recommended for direct use, but can be used as learning
StateEST_Kestrel
- c++的卡尔曼状态估计程序，程序可以直接使用。来源于Ka的控制器。-c++ Kalman state estimation, the program can be used directly. Ka from the controller.
fcn_SR_KF
- This file compares three different versions of the Kalman filter. The Kalman filter is used for recursive parameter estimation. The Kalman filter can handle noisy measurements. The first implemented filter (fcn_KF) is the Kalman filter with
Multi-UAVs-Target-Tracking
- 多无人机（Unmanned Aerial Vehicle，UAV）协同目标跟踪在军/民用方面有 着广泛而又迫切的应用需求和重要的理论研究价值，是目前多 UAV 系统自主控制 领域的一个重要研究方向。本文以 UAV 执行对地侦察打击任务为应用背景，针对 复杂环境中多 UAV 协作式跟踪地面移动目标问题，重点围绕目标状态融合估计和 观测航迹优化两项关键内容展开研究-Multi-UAV (Unmanned Aerial Vehicle, UAV) has a broad and col
IEEE34
- pscad环境下搭建的一个IEEE34节点的，测试模型，可以用于电力系统潮流计算、状态估计等-pscad environment to build a IEEE34 node under test model can be used to power flow calculation, state estimation, etc.
A-Bayesian-estimation-for-single-target-tracking-
- A bayesian estimation for single target tracking based on state mixture models
distributed-wls
- 分布式电力系统状态估计完整程序，下载下来即可运用-Distributed power system state estimation complete program
My-understanding-of-control
- 飞机姿态算法。从这篇文章是我尝试的飞行器姿态检测采用四元数方法,然后利用卡尔曼滤波算法,并尝试卡尔曼滤波器耦合的多个状态变量可以是一个复杂的过程,线性系统状态估计进行了简单的解耦,将最优估计的态度和最优估计陀螺漂移,通过这种方式,可以通过直观的方法来调整参数的两个部分。-Aircraft attitude algorithm.From this article is my attempt to spacecraft attitude detection by using the quaterni
5_Vishal_Awasthi_Review_Article_Feb_2011
- A Survey on the Algorithms of Kalman Filter and Its Variants in State Estimation.