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 initial angular positions of the joints are estimated by the extended Kalman filter algorithm, then the manipulator's absolute locating accuracy in its workspace is guaranteed indirectly.
利用扩展卡尔曼滤波算法估计机械手各关节的初始角位置，从而间接地保证机械手在工作空间内的绝对定位精度。
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。
Unscented Kalman Filter (UKF), which is an evolutional algorithm of Extended Kalman Filter (EKF), has been successfully applied in many nonlinear estimation problems.
无轨迹卡尔曼滤波器(ukf)作为扩展卡尔曼滤波器(ekf)的进化算法在许多非线性估计问题上取得了成功的应用。
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 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。
Concerning the problem of instability and low accuracy of passive filter in underwater target tracking, a modified adaptive extended kalman filter (MAEKF) algorithm is presented.
针对在被动方式下进行水下目标跟踪容易导致滤波发散和收敛精度不高的问题，介绍了一种改进的自适应推广卡尔曼滤波算法。
Concerning the problem of instability and low accuracy of passive filter in underwater target tracking, a modified adaptive extended kalman filter (MAEKF) algorithm is presented.
针对在被动方式下进行水下目标跟踪容易导致滤波发散和收敛精度不高的问题，介绍了一种改进的自适应推广卡尔曼滤波算法。
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