When using Kalman Filter to track a target, estimation of the initial state of the target is an important factor influencing tracking precision in the initial phase.
采用卡尔曼滤波器对目标进行跟踪时，目标初始状态估计是影响初始阶段跟踪精度的一个重要原因。
Extended Kalman Filter is an efficient tool for mobile robot position tracking, but it suffers from linearization errors due to linear approximation of nonlinear system equations.
扩展的卡尔曼滤波定位方法是一个常用的位置跟踪方法，但是在对非线性系统方程进行线性化近似过程中引入了线性化误差。
Extended Kalman Filter (EKF) and converted measurement Kalman Filter (CMKF) have been widely used in radar target tracking.
在雷达目标跟踪中，扩展卡尔曼滤波(ekf)和转换坐标卡尔曼滤波(CMKF)得到了广泛的应用。
Kalman filter is used to predict and track markers, making the tracking of markers more veracious.
利用卡尔曼滤波算法进行标记点预测和跟踪，提高了跟踪的准确性。
For the disadvantage of tracking the soft failure of the residual test based on Kalman filter, this paper makes an improvement on the method by using the state propagator.
针对基于卡尔曼滤波器的残差检验法会跟踪软故障的局限性，提出了一种基于状态递推器的改进方法。
In the tracking stage, track face using kalman filter and skin-color feature, if fail to track then turn into detecting stage.
跟踪阶段用卡尔曼滤波器结合肤色特征跟踪人脸，如果跟踪失败，转入检测阶段。
Using smoothing filter and average-force algorithm to position beacon's facula, then use kalman prediction algorithm with the adaptive capacity to achieve the recursive tracking algorithm.
以平均值平滑滤波法和质心法实现了对信标光斑定位，利用卡尔曼预测算法实现了具有自适应能力的递归跟踪算法。
In nonlinear systems, the fusion algorithm based on extended Kalman Filter suffers from the disadvantage that the tracking precision is not satisfied.
在非线性系统中，常用的跟踪滤波算法是基于扩展的卡尔曼滤波算法的融合算法，但是这种融合算法的跟踪精度并不是很高。
We promote the precision of control system by using Kalman filter to process the sample data and intensify the dynamic tracking properties by adding feed forward.
对采样数据进行卡尔曼滤波以提高控制的精度并且加入前馈增强系统的动态跟踪性能。
In order to effectively solve the problem that the loss of object information under occlusion causes the failure of tracking, moving objects tracking algorithm is presented based on Kalman filter.
为了有效解决运动目标遮挡时目标信息容易丢失从而导致跟踪失败的问题，提出一种基于卡尔曼滤波器的运动目标跟踪算法。
Accurate models and noise statistics are required in many tracking algorithms based on the traditional Kalman filter, which are difficult to be satisfied in engineering application.
在以常规卡尔曼滤波器为基础的各种跟踪算法中，要求精确的模型和噪声统计，但在实际问题中，大多数情况上述要求不能满足。
To improve the performance of object tracking, a particle filter algorithm was proposed which(uses) state partition technique and parallel extended kalman filter to construct proposal distribution.
为了进一步提高目标跟踪的性能，采用一种新的建议分布构造方法，即利用状态分割技术和平行扩展卡尔曼滤波技术构造建议分布。
In this paper, we proposed an adaptive tracking technique, based on extended Kalman filter approach, to identify the structural parameters and their changes.
本文采用了一种基于广义卡尔曼滤波的自适应追踪技术对结构的参数进行辨识。
A modified strong tracking Kalman filter (MSTKF) for linear stochastic systems is proposed.
针对线性随机系统提出了一种改进强跟踪卡尔曼滤波器(MSTKF)。
Concerning the problem to instability and low accuracy of the passive filter on bearings-only target tracking, a modified adaptive Extended Kalman filter algorithm on polar coordinate is presented.
在水下被动目标跟踪系统中，直角坐标系下的扩展卡尔曼滤波器容易发散而导致滤波精度很差。
In tracking aspect, use carrier tracking loop based on Kalman filter to improve tracking performance.
在跟踪方面，采用了基于卡尔曼滤波的载波跟踪环来提高跟踪环的性能。
At present, there are many algorithms to achieve position tracking, such as the Kalman filter algorithm, extended Kalman filter algorithm, particle filter algorithm and so on.
目前，实现定位跟踪的算法有很多，如卡尔曼滤波算法、扩展卡尔曼滤波算法、粒子滤波算法等。
The results show that the tracking accuracy, the responsibility to target mobility and the implementation of steady Kalman filter are good.
结果表明：恒定增益卡尔曼滤波器在跟踪精度，对目标机动的响应能力以及可实现性等指标上都具有较好的特性。
It succeeds in exemplificative images by improving the method of tracking origination and finality, using Kalman Filter to forecast the next position and the nearest rule to associate data.
改进跟踪起始和跟踪终结算法，用卡尔曼滤波预测位置，最近邻原则进行数据关联，实现了对实验图像中多个目标的良好跟踪。
The results of simulation indicate that this new approach has a better accuracy than the traditional Kalman filter and strong tracking Kalman filter in the field of maneuvering target tracking.
仿真结果表明，该改进滤波器跟踪机动目标的精度高于常规卡尔曼滤波器和强跟踪卡尔曼滤波器。
Kalman has already replaced the classic Wiener filter theory for it can not meet the development of modern target tracking system.
目前卡尔曼滤波理论基本上取代了维纳滤波理论，经典的维纳滤波方法基本上不适应现代目标跟踪系统的需求。
For satellite formation flying orbit adjustment situation, which only used radio measurement, a strong tracking unscented Kalman filter (UKF) algorithm was introduced to the simulation.
并针对编队卫星进行轨道机动时仅采用无线电进行测量的工况，采用强跟踪离散卡尔曼滤波(ukf)算法进行仿真计算。
In MMW radar tracking, the classical Kalman filter will degrade seriously when observation noise is non-Gaussian because of target glint.
在毫米波雷达目标跟踪中，角闪烁的非高斯特性将使得经典的卡尔曼滤波器失效。
In the part of tracking, combining the improved Mean-Shift algorithm and Kalman filter prediction.
在跟踪部分，采用改进的均值漂移算法和卡尔曼滤波预测结合。
A self-adapting Kalman Filter based on the principle of stochastic approximatation is introduced in the paper. This filter provides an ideal means for the tracking of underwater noise source.
本文根据随机逼近原理提出了一种自适应卡尔曼滤波器，适用于被动声纳对水下噪声源的跟踪。
The final tracking results can be obtained through dispersion processing multimode tracking data with Kalman filter and performing global fusion for the processed results.
通过卡尔曼滤波分散处理多个模式跟踪结果数据，再将处理结果进行全局融合得出跟踪最终结果。
Firstly, we introduce the Kalman filter which is extensively used in position tracking, and the Markov localization method which has made many successes in global localization.
首先，介绍了位置跟踪广泛应用的卡尔曼滤波方法和在全局定位方面取得一定成功的马尔可夫定位方法。
A linear state equation is got from selection of maneuvering acceleration. The adaptivity of adaptive tracking Kalman filter is represented by estimation of maneuvering commander at real time.
由于选择了新的机动加速度量，从而得出线性的状态方程，由机动指令的实时估计得到机动目标自适应跟踪卡尔曼滤波器。
After analyzing the model of high dynamic signals, a quasi-open-loop carrier tracking method based on unscented Kalman filter (UKF) is proposed.
在分析高动态载波信号模型的基础上，提出了一种基于无迹卡尔曼滤波(ukf)的准开环载波跟踪方法。
After analyzing the model of high dynamic signals, a quasi-open-loop carrier tracking method based on unscented Kalman filter (UKF) is proposed.
在分析高动态载波信号模型的基础上，提出了一种基于无迹卡尔曼滤波(ukf)的准开环载波跟踪方法。
应用推荐