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13下载：
这是一个采用扩展卡尔曼滤波算法估计电池SOC的程序，希望对大家有所帮助！-This is a program about battery SOC estimation with kalman filtering algorithm.
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This paper studies the problem of tracking a ballistic object in
the reentry phase by processing radar measurements. A suitable
(highly nonlinear) model of target motion is developed and the
theoretical Cramer—Rao lower bounds (CRLB) of estimat
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introduction to nonlinear estimation with EKF and an example in Matlab-introduction to nonlinear estimation with EKF and an example in Matlab
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Matlab 粒子滤波器源代码，状态估计，别且与EKF滤波器做比较-Matlab source code particle filter, state estimation, do not and compared with the EKF filter
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Start with the runlocalization track.m which is
the entrance function to your lab. This function reads two les determined by
simout le and map le input arguments which contain information about sensor
readings and the map of the environment re
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用泰勒级数展开的形式表示高动态的载波相位参数, 给出了对高动态载体和各阶频率参数
估计的四阶加权扩展卡尔漫滤波器(EKF) , 以及实现高动态跟踪滤波器必须的状态转移矩阵和动
态噪声协方差矩阵. 计算机模拟实验分析了对载波相位和各阶频率的跟踪结果.-Taylor series expansion with the form that the carrier phase high-dynamic parameters, given the high-order dynamic freq
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有关非线性滤波程序的说明文档，包括KF,EKF,UKF,GHF等各种方法-The documentation demonstrates the use of software as well as state-space estimation with Kalman filters in general. The purpose is not to give a complete guide to the subject, but to discuss the implementation an
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包括kf，ekf，pf，upf可以自己定制模型参数，完成滤波-ReBEL currently contains most of the following functional units which can be used for state-, parameter- and joint-estimation:
Kalman filter
Extended Kalman filter
Sigma-Point Kalman filters (SPKF)
Unscented
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基于EKF的神经网络自适应在线学习算法，包含例子和文档。-We show that a hierarchical Bayesian modeling approach allows us to perform
regularization in sequential learning. We identify three inference
levels within this hierarchy: model selection, parameter estimation, and
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利用IMU数据（陀螺仪，加速度计，磁场计）结合EKF进行实时位姿估计-pose estimation based on EKF with the data of IMU
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用EKF和AEKF方法对导弹状态进行估计仿真，并进行对比分析-Missile state estimation simulation with EKF and AEKF methods of comparative analysis
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无香粒子滤波的一个matlab例程，其中有ekf,ukf,pf,upf-In these demos, we demonstrate the use of the extended Kalman filter (EKF), unscented Kalman filter (UKF), standard particle filter (a.k.a. condensation, survival of the fittest, bootstrap filter, SIR, sequential M
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利用扩展卡尔曼算法( EKF)对高动态直接扩频信号的载波相位和频率进行了估计,并利用载波辅助技术测量载波相位的变化值来
校正伪码延时环,减小多普勒频移对伪码延时的影响,得到了精确的延时估计值,提
高了伪码延时锁定环的动态跟踪性能.-The PN delay loop is adjusted through measuring the varied value of carrier phase with carrier aiding technology. The effect of Do
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state estimation on a simple 2nd order LTI system using kf, ekf, ukf, cdkf, srukf, crcdkf
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state estimation with kalman filter, kf, ekf, ukf, cdkf, srukf, srcdkf
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基于扩展卡尔曼滤波的电池soc估计simulink模型，将模型计算得到的电池soc与扩展卡尔曼滤波得到的电池soc进行比较。(Based on the Simulink model of battery SOC estimation with extended Kalman filter, the battery SOC calculated by the model is compared with the battery SOC obtained by extended Kalman fil
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扩展卡尔曼滤波算法锂离子电池SOC估计中有较广泛的应用，其精度高，鲁棒性好，算法简单(The extended Kalman filtering algorithm has a wide range of applications in SOC estimation of lithium-ion batteries, with high accuracy, good robustness, and simple algorithm)
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扩展卡尔曼滤波可通过将非线性系统在其参考点处作泰勒级数展开，取其一阶线性部分作为该非线性模型的逼近，从而得到非线性系统在当前时刻的线性化描述。(Extended Kalman filter (EKF) can get the linearized descr iption of the nonlinear system at the current time by expanding the nonlinear system with Taylor series at its reference
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