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工学博士学位论文
目前,扩展卡尔曼滤波是研究初始对准和惯性/GPS组合导航问题的一个主要手段。
但初始对准和惯性/GPS组合导航问题本质上是非线性的,对模型进行线性化的扩展卡
尔曼滤波在一定程度上影响了系统的性能。近年来,直接使用非线性模型的
UKF(Unscented Kalman Filtering, UKF)和粒子滤波,正在逐渐成为研究非线性估计问题
的热点和有效方法。
本文研究了UKF和粒子滤波两种非线性滤波方法,并将其应用于非线性静基座对
准和惯性
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根据二维空间内目标作匀速直线运动和匀速圆周运动的特点,在建立目标运动模型和观测模型的基础上采用基于交互多模算法(IMM)的卡尔曼滤波器对机动目标进行跟踪。仿真结果表明,该算法不仅能够对匀速直线运动和匀速圆周运动的目标进行跟踪,而且在运动模型发生变化时,滤波误差也比较小。
关键词:卡尔曼滤波器;目标跟踪;机动;交互多模(IMM)
-two-dimensional space under target for uniform linear motion and uniform circula
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基于“当前”统计模型的模糊自适应跟踪算法
我存的一篇论文,拿来与大家共享-Current statistical model needs to pre-define the value of maximum accelerations of maneuvering targets.So it
may be difficult to meet all maneuvering conditions.The Fuzzy inference combined with Current stati
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离散线性随机系统Kalman滤波,对问题进行了描述,分析并提出解决方案,并附加了相应程序-Discrete linear stochastic system Kalman filter, a descr iption of the problem, analyze and propose solutions, and attach the appropriate procedures
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结合雷达跟踪的空中目标的实际情况,针对目标运动模型中的线性运动和非线性运动,分别设计了两种模型,并用马尔科夫状态转移矩阵实现IMM算法。最后对交互多模型卡尔曼滤波算法进行了Matlab仿真及结果分析。-Combined with radar tracking air targets, for linear and non-linear movement of target motion model, two models were designed and used a Markov state
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用MATLAB实现的卡尔曼滤波,根据有用信号和干扰噪声的统计特性(自相关函数或功率谱),以线性最小均方误差(MSE),能最大程度的滤除干扰噪声,提取有用信号。-Kalman filter using MATLAB, based on the statistical properties of the useful signal and interference noise (autocorrelation function or power spectrum), linear minimum m
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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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this file contains 4 parts:
1- sherlock C code for plagiarism detection in text document
2-linear kalman filter in simulink
3-sfclfunc m file for Superconducting fault current limiter
4-lightning protection is GUI matlab file for lightning pr
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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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matlab卡尔曼滤波文件,实现线性和非线性卡尔曼滤波,内容丰富实用-matlab Kalman filter files to achieve linear and nonlinear Kalman filtering, content-rich and practical
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输入为九轴数据,运用线性卡尔曼滤波,模拟出物体运动轨迹-For the nine-axis data input using the linear Kalman filter to simulate the trajectory of moving objects
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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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针对线性高斯系统,采用共轭分布实现量测噪声未知情况下的状态估计和噪声方差辨识。(For linear Gaussian system, a conjugate distribution is adopted to estimate system state and identificate measurement noise variance.)
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基本卡尔曼滤波,python实现。 目标跟踪,物体匀速运动。(basic linear kalman filter, implemented by python.)
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一个关于姿态的卡尔曼滤波器用着非常不错大家都来用用(A linear Kalman filter estimating altitude and vertical velocity by doing sensor fusion of acceleration and any altitude measurement such as e.g. barometer or SONAR.)
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