Description: 扩展KALMAN滤波方面的应用，应用于系统跟踪等方面的问题-extended Kalman filter on the application, application tracking systems and other issues Platform: |
Size: 1024 |
Author:zhang |
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Description: A method is presented for augmenting an extended
Kalman filter with an adaptive element. The resulting estimator
provides robustness to parameter uncertainty and unmodeled
dynamics.-A method is presented for augmenting an ext Kalman ended with an adaptive filter element. T he resulting estimator provides robustness to parameter uncertainty and unmodeled dynamics . Platform: |
Size: 338944 |
Author:rifer |
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Description: 目标跟踪的扩展卡尔曼滤波算法主函数的文件是：kal_demo.m
近似网格滤波的主函数文件是：bayes_demo.m
近似网格滤波划分网格的方法是：以目标上一个时刻的位置作为中心进行网格的划分，每个网格大小为1，总的区域为5*5
改进后算法的主函数文件是：trackiing_demo.m-Target tracking extended Kalman filter algorithm is the main function of the document: kal_demo.m approximate mesh filter paper is the main function: bayes_demo.m approximate mesh filter into the grid method is: in order to target the location of a moment as the central to carry out the division of the grid, each grid size of 1, with a total area of 5* 5 to improve the algorithm Platform: |
Size: 138240 |
Author:Lin |
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Description: Comparison of two IMM tracking and classifier architectures based on Extended and Unscented
Kalman Filter with CRLB-Comparison of two IMM tracking and classifier architectures based on Extended and UnscentedKalman Filter with CRLB Platform: |
Size: 128000 |
Author:ajie |
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Description: 目标跟踪的扩展卡尔曼滤波算法主函数的文件是：kal_demo.m 近似网格滤波的主函数文件是：bayes_demo.m 近似网格滤波划分网格的方法是：以目标上一个时刻的位置作为中心进行网格的划分，每个网格大小为1，-Target tracking extended Kalman filter algorithm is the main function of the document: kal_demo.m approximate mesh filter paper is the main function: bayes_demo.m approximate mesh filter into the grid method is: in order to target the location of a moment as the central to carry out the division of the grid, each grid size of 1, Platform: |
Size: 94208 |
Author:王明 |
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Description: 跟踪相关论文，《基于彩色图像的机器人视觉跟踪》《基于扩展卡尔曼滤波的主动视觉跟踪技术》《基于视觉和扩展卡尔曼滤波的位姿和运动估计新方法》《一种运动目标检测与跟踪快速算法的研究》-Tracking the relevant papers, based on the color image of the robot visual tracking , Extended Kalman Filter based on active vision tracking technology, Based on the visual and extended Kalman filter and the position and orientation of new motion estimation method , a moving target detection and fast algorithm for tracking of Study Platform: |
Size: 1433600 |
Author:王云 |
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Description: 扩展卡尔曼滤波与粒子滤波的比较，对某复杂函数曲线的跟踪。-Extended Kalman filter and particle filter compared to the complexity of a function curve tracking. Platform: |
Size: 2048 |
Author:summer |
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Description: 在飞机无源跟踪中，用扩展卡尔曼滤波算法来实现平面变角速度模型。-Passive tracking the aircraft, using extended Kalman filter algorithm to achieve the flat model of variable angular velocity. Platform: |
Size: 10240 |
Author:刘浩明 |
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Description: 程序可以实现三维目标的跟踪监控，利用的是扩展卡尔曼滤波器EKF算法-Program can achieve the three-dimensional target tracking control, the use of the extended Kalman filter EKF algorithm Platform: |
Size: 1024 |
Author:张肖 |
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Description: 用MATLAB编写的单目标跟踪算法程序，采用了递归式算法，包括极大似然然估计，卡尔曼滤波，扩展卡尔曼滤波和无迹卡尔曼滤波，带有注释，易于理解。-Written with the MATLAB program single-target tracking algorithm, using recursive algorithms, including maximum likelihood estimation, Kalman filtering, extended Kalman filter and unscented Kalman filter, with comments, easy to understand. Platform: |
Size: 11264 |
Author:asd |
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Description: 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 all. Platform: |
Size: 4096 |
Author:yang |
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Description: 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) the new method. The method of iterative filtering theory is introduced to the extended Kalman filter method, the effective measurement of repeated use of the new information, also using Levenberg-Marquardt method to adjust the covariance matrix of prediction algorithm to ensure global convergence. Experimental results show that the proposed method has higher estimation accuracy, is a high efficiency, good performance tracking methods. Platform: |
Size: 1527808 |
Author:李辉 |
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