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5下载：
轨迹跟踪---船舶航迹控制，典型的欠驱动控制问题。两种算法，采用了matlab---simulink，直观明了。-Sailing ship trajectory tracking control, a typical under-actuated control. Two algorithms using matlab--- simulink, intuitive and clear.
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Mobile Robots
非线性跟踪-Mobile Robots nonlinear tracking
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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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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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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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"A Tutorial on Particle Filters for Online Nonlinear Non-Gaussian Bayesian Tracking"
This is a paper about tracking by particle filter.
This is very useful.
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the attached file consists of matlab code for implementation of sequential importance sampling particle filter given in IEEE paper entitled as "A TUTORIAL ON PARTICLE FILTERS FOR ONLINE NONLINEAR NON GUASSIAN BAYESIAN TRACKING"
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在机动目标跟踪中，机动目标模型是机动目标跟踪的基本要素之一，一般希望机动目标模型能准确表征目标机动时的各种运动状态。比较常用的模型有匀速运动(CV)模型、匀加速运动(CA) 模型、时间相关模型（Singer）和机动目标“当前”统计模型。上述模型均采用机动频率表征目标的机动情况。在应用当中，通常采用固定的机动频率，这就表示机动目标的机动时间是一定的，而实际上机动目标的机动时间是不断变化的，也就是说机动频率是不断变化的，采用固定机动频率必然会带来误差。采样周期在0.5—2S时，机动频率越小跟踪精度越
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This thesis aimed to eliminate tracking
error of traveling a circular profile on the CNC machine tools. Friction is one of the
most significant source of nonlinear disturbance for the motion control which caused
by the relative motion of differ
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粒子滤波matlab程序，可用于机动目标跟踪，适用于非线性系统-Particle filter matlab program can be used for maneuvering target tracking for nonlinear systems
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非线性滤波算法中的粒子滤波，用于目标定位与跟踪。-Nonlinear filtering algorithm in the particle filter for target tracking.
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一种基于运动模型的扩展卡尔曼滤波（EKF）算法,该方法适用于任何能用状态空间模型表示的非线性系统，精度可以逼近最优估计.-an EKF positioning and tracking algorithm based on kinematic model. This method can apply to any state-space model which is the nonlinear system, and the accuracy can approach to best of al
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本文对于非线性非高斯问题，提出了一种改进扩展卡尔曼滤波（NIEKF）新方法。该方法将迭代滤波理论引入到扩展卡尔曼滤波器方法中，有效地重复利用新的测量信息，还利用Levenberg-Marquardt 方法调整预测协方差阵以保证算法具有全局收敛性。实验结果表明，所提方法具有更高的估计精度，是一种效率较高、性能较好的跟踪方法。-This non-Gaussian for nonlinear problems, an improved extended Kalman filter (NIEKF) th
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EKF仅仅利用了非线性函数Taylor展开式的一阶偏导部分（忽略高阶项），常常导致在状态的后验分布的估计上产生较大的误差，影响滤波算法的性能，从而影响整个跟踪系统的性能。最近，在自适应滤波领域又出现了新的算法——无味变换Kalman滤波器（Unscented Kalman Filter-UKF）。UKF的思想不同于EKF滤波，它通过设计少量的σ点，由σ点经由非线性函数的传播，计算出随机向量一、二阶统计特性的传播。因此它比EKF滤波能更好地迫近状态方程的非线性特性，从而比EKF滤波具有更高的估计精
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Extended kalamn filter for tracking manuers linear and nonlinear in motion
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本文讨论了小波神经网络在机动多目标跟踪中的应用,多目标跟踪就是主体为了维持对多个目标(客体)当前状态的估计而对所接收的量测信息进行处理的过程。以非线性大规模并行分布式处理为特征的神经网络可以解决传统的目标跟踪方法的难以解决的计算量组合爆炸问题以及需要确定机动目标的数学模型的问题, 将小波分析原理与神经网络相融合,提出了基于小波神经网络的目标跟踪方法来提高系统的学习能力、表达能力以及机动多目标状态的估计精度。-This article discusses the application of wa
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Tayfun Ç imen , Stephen P. Banks, "Nonlinear optimal tracking control with application to super-tankers for autopilot design " , Automatica 40 (2004).
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A Comparative Study of Nonlinear Filters for
Target Tracking in Mixed Coordinates
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This paper presents a simple and robust speed control scheme of Permanent Magnet Synchronous Motor (PMSM). It is to achieve
accurate control performance in the presence of load torque and plant parameter variation. A Kalman filter is used to estim
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关于非线性跟踪微分器的源程序，有需要的朋友可以看一看-About nonlinear tracking differentiator source, a friend in need can take a look
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