Description: Knowledge of the process noise covariance matrix
is essential for the application of Kalman filtering. However,
it is usually a difficult task to obtain an explicit expression of
for large time varying systems. This paper looks at an adaptive
Kalman filter method for dynamic harmonic state estimation and
harmonic injection tracking.-Knowledge of the process noise covariance matrix is essential for the application of Kalm an filtering. However, it is usually a difficult task to obtain an expli cit for large expression of time varying system s. This paper looks at an adaptive Kalman filter method for dynamic estimation a harmonic state nd harmonic injection tracking. Platform: |
Size: 419840 |
Author:rifer |
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Description: 该程序为基于粒子滤波的一种新算法,综合MCMC Bayesian Model Selection即MONTE CARLO马尔克夫链的算法,用来实现目标跟踪,多目标跟踪,及视频目标跟踪及定位等,解决非线性问题的能力比卡尔曼滤波,EKF,UKF好多了,是我珍藏的好东西,现拿出来与大家共享,舍不得孩子套不着狼,希望大家相互支持,共同促进.-the program based on particle filter for a new algorithm, Integrated Bayesian MCMC Model Selection MONTE CARLO that Ma Erkefu chain algorithm, which can be used for target tracking, multi-target tracking, and video tracking and positioning. solve nonlinear problems of capacity than Kalman filtering, EKF, UKF much better, and I treasure the good stuff, now up with the share could not bear children, she sets the wolf, we hope that support each other and work together to promote. Platform: |
Size: 14336 |
Author:zhang |
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Description: 卡尔曼滤波C程序 卡尔曼滤波器是一个“optimal recursive data processing algorithm（最优化自回归数据处理算法）”。
对于解决很大部分的问题，他是最优，效率最高甚至是最有用的。他的广泛应用已经超过30年，包括机器人导航，控制，
传感器数据融合甚至在军事方面的雷达系统以及导弹追踪等等。近年来更被应用于计算机图像处理，
例如头脸识别，图像分割，图像边缘检测等等。-Kalman filtering C program Kalman filter is an "optimal recursive da ta processing algorithm (since the handover optimization algorithm for data processing). " For most of the solution, he is the best, most efficient, if not the most useful. He has the broad application of more than 30 years, including robot navigation, control, sensor data fusion even in the military aspects of the radar system and missile tracking, and so on. In recent years, it has been used in computer image processing, such as humans recognition, image segmentation, image edge detection, and so on. Platform: |
Size: 1024 |
Author:于军相 |
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Description: 卡尔曼滤波器是一个“optimal recursive data processing algorithm（最优化自回归数据处理算法）”。
对于解决很大部分的问题，他是最优，效率最高甚至是最有用的。他的广泛应用已经超过30年，包括机器人导航，控制，
传感器数据融合甚至在军事方面的雷达系统以及导弹追踪等等。近年来更被应用于计算机图像处理，
例如头脸识别，图像分割，图像边缘检测等等。-Kalman filter is an "optimal recursive data proces sing algorithm (since the handover optimization algorithm for data processing). " For most of the solution, he is the best, most efficient, if not the most useful. He has the broad application of more than 30 years, including robot navigation, control, sensor data fusion even in the military aspects of the radar system and missile tracking, and so on. In recent years, it has been used in computer image processing, such as humans recognition, image segmentation, image edge detection, and so on. Platform: |
Size: 1024 |
Author:于军相 |
Hits:
Description: 卡尔曼滤波器是一个“optimal recursive data processing algorithm（最优化自回归数据处理算法）”。
对于解决很大部分的问题，他是最优，效率最高甚至是最有用的。他的广泛应用已经超过30年，包括机器人导航，控制，
传感器数据融合甚至在军事方面的雷达系统以及导弹追踪等等。近年来更被应用于计算机图像处理，
例如头脸识别，图像分割，图像边缘检测等等。-Kalman filter is an "optimal recursive data proces sing algorithm (since the handover optimization algorithm for data processing). " For most of the solution, he is the best, most efficient, if not the most useful. He has the broad application of more than 30 years, including robot navigation, control, sensor data fusion even in the military aspects of the radar system and missile tracking, and so on. In recent years, it has been used in computer image processing, such as humans recognition, image segmentation, image edge detection, and so on. Platform: |
Size: 1024 |
Author:于军相 |
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Description: kalman滤波用于目标二维运动情况下的蒙特卡罗法仿真跟踪滤波器-Kalman filter for 2-D movement of the Monte Carlo simulation tracking filter Platform: |
Size: 1024 |
Author:sunqiang |
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Description: 卡尔曼在目标跟踪中的应用本文对作匀速运动的二维空中机动目标进行研究，利用交互式多模型方法对雷达目标进行跟踪-target tracking in the application of this uniform motion for the two-dimensional aerial maneuvers goals, use of interactive multi-model approach to tracking radar targets Platform: |
Size: 10240 |
Author:zhangyun |
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Description: 目标跟踪，程序利用卡尔曼滤波器实现了对机动目标的跟踪。效果较好的运动模型。
-Target tracking, procedures realize the use of Kalman filter for maneuvering target tracking. Better model of the movement. Platform: |
Size: 7168 |
Author:zzw19831114 |
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Description: 书籍《多传感器数据融合》P44页算法的具体实现，可用于目标跟踪、卫星定位的仿真程序。-Books, multi-sensor data fusion P44-page concrete realization of algorithm can be used for target tracking, satellite positioning the simulation program. Platform: |
Size: 2048 |
Author:宋俊典 |
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Description: kalman滤波实验，目标轨迹跟踪，很好用的例子，供大家学习用-kalman filtering experiments, the target trajectory tracking, with a good example for all to learn Platform: |
Size: 121856 |
Author:sdfs |
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Description: 本文提出了一种静止摄像机条件下的运动目标检测与跟踪算法。 它以一种改进的自适应
混合高斯模型为背景更新方法，用连通区检测算法分割出前景目标，以 Kalman滤波为运动模型实现对运动目标的连续跟踪。在目标跟踪时，该算法针对目标遮挡引起的各种可能情况.-In this paper, a stationary camera under the conditions of the moving target detection and tracking algorithm. It is an improved adaptive mixed-Gaussian model for the background update method, connected areas of the prospect of partition detection algorithm targets to Kalman filtering model for the movement to realize the continuous tracking of moving targets. In target tracking, the algorithm for the target occlusion caused by a variety of possible scenarios. Platform: |
Size: 452608 |
Author:Jenifer |
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Description: 利用Kalman Filter进行机动目标跟踪的例子,附有详细的说明文档-Use of Kalman Filter for Maneuvering Target Tracking example with detailed description of the document Platform: |
Size: 91136 |
Author:hehe |
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Description: 用一观测器从t=1秒开始对一个运动目标的距离进行连续地跟踪测量，假设观测的间隔为一秒钟，雷达到运动目标之间的距离为S(t)（1） 统计特性的初值为
（2）观测误差是与和均不相关的白噪声序列，并且有
（3）观测数据存放在附加的文件中（单位：m）。
要求：分析上述对象，建立系统模型，构造卡尔曼滤波器，编程计算，求：
（1） 距离S(t)的最佳估计及估计误差，
（2） 距离S(t-5)的最佳平滑及估计误差，
（3） 距离S(t+5)的最佳预测及估计误差，
（4） 对结果进行分析讨论。
-By one observer from the t = 1 PST on a moving target tracking for distance measurement, assuming that the observation interval is one second, the radar that the distance between the moving target for the S (t) (1) the statistical characteristics of the initial condition (2) observational error is not associated with white noise sequence, and (3) observational data stored in the attached document (unit: m). Requirements: Analysis of the above-mentioned object, the establishment of the system model, constructed Kalman filter, programming terms, seeking: (1) distance from S (t) the best estimate and the estimation error, (2) distance from S (t-5) the most good smoothing and estimation error, (3) distance from S (t+ 5) the best prediction and estimation error, (4) the results analyzed and discussed. Platform: |
Size: 2048 |
Author:裴海波 |
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Description: A new approach toward target representation and localization, the central component in visual tracking
of non-rigid objects, is proposed. The feature histogram based target representations are regularized
by spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity functions
suitable for gradient-based optimization, hence, the target localization problem can be formulated using
the basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyya
coefficient as similarity measure, and use the mean shift procedure to perform the optimization. In the
presented tracking examples the new method successfully coped with camera motion, partial occlusions,
clutter, and target scale variations. Integration with motion filters and data association techniques is also
discussed. We describe only few of the potential applications: exploitation of background information,
Kalman tracking using motion models, and face tracking.-A new approach toward target representation and localization, the central component in visual trackingof non-rigid objects, is proposed. The feature histogram based target representations are regularizedby spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity functionssuitable for gradient-based optimization, hence, the target localization problem can be formulated usingthe basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyyacoefficient as similarity measure, and use the mean shift procedure to perform the optimization. In thepresented tracking examples the new method successfully coped with camera motion, partial occlusions, clutter, and target scale variations. Integration with motion filters and data association techniques is alsodiscussed. We describe only few of the potential applications: exploitation of background information, Kalman tracking using motion models, and face tracking . Platform: |
Size: 2779136 |
Author: |
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Description: 卡尔曼滤波器是一个“optimal recursive data processing algorithm（最优化自回归数据处理算法）”。对于解决很大部分的问题，他是最优，效率最高甚至是最有用的。他的广泛应用已经超过30年，包括机器人导航，控制，传感器数据融合甚至在军事方面的雷达系统以及导弹追踪等等。近年来更被应用于计算机图像处理，例如头脸识别，图像分割，图像边缘检测等等。-Kalman filter is an " optimal recursive data processing algorithm (optimal autoregressive data-processing algorithm)." To address the very most of the questions, he is the best, most efficient, if not the most useful. He has been widely used for more than 30 years, including robot navigation, control, sensor data fusion and even in military radar systems and missile tracking and so on. Recent years been applied to computer image processing, such as头脸recognition, image segmentation, image edge detection and so on. Platform: |
Size: 570368 |
Author:曲晓川 |
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Description: 本程序是基于机动目标跟踪课题的整个算法程序，其中包括卡尔曼，扩展卡尔曼和粒子滤波程序及其仿真代码和仿真的图形。-This procedure is based on the subject of maneuvering target tracking algorithm for the whole procedure, including Kalman, extended Kalman and particle filter process and its simulation code and simulation graphics. Platform: |
Size: 124928 |
Author:liujun |
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Search - kalman for tracking