A digital tracking filter method is put forward, its approach realizing adaptive tracking ability is simple and easy, and good effect of noise cancellation can be obtained.
提出了数字跟踪窄带滤波方法，实现的自适应跟踪方法简便，消噪效果良好。
This paper presents an adaptive fault prediction method based on strong tracking filter, which can predict faults in a class of nonlinear time varying systems.
本文提出了一种基于强跟踪滤波器的自适应故障预报方法，能够对一类带时变参数的非线性系统进行故障预报。
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。
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 this paper, an adaptive particle filter for tracking application is proposed, which is based on tuning particle number and sampling interval.
本文提出了一种用于跟踪系统的可在线调整采样周期和粒子数目的自适应粒子滤波器。
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。
Adaptive Kalman filter algorithm study (1) Based on the study of the passive target tracking in modified polar coordinates, the nonlinear dynamic model is devised.
自适应滤波算法(1)研究了极坐标系下的水下目标被动跟踪问题，建立了被动跟踪的动力学模型。
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。
Kalman filter of the kind of equations was calculated with T-SFIMMA algorithm based on adaptive Kalman filter algorithm of T-S fuzzy model, realize the tracking and automatic switchover of models.
对各方程序卡尔曼滤波，通过T -SFIMMA算法进行基于T - S模糊模型的自适应卡尔曼滤波计算，实现系统模型的实时跟踪与自动转换。
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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