In order to resolve the maneuvering problem in target tracking, an algorithm based on interacting multiple model (IMM) method was presented.
针对目标跟踪中的目标机动问题提出了一种“基于自适应相互作用多模型”的算法。
This paper presents an algorithm for facial tracking and pose estimation based on skin color model and elliptical template.
文章提出了一种基于肤色模型，结合椭圆环模板进行人脸跟踪及姿态估计的算法。
Based on the adaptive Kalman filtering algorithm, an estimator for the GPS PN code tracking error with model bias is proposed.
在自适应卡尔曼滤波算法的基础上提出了一种带模型偏差的GPS伪码跟踪误差估计器。
As the basis of the tracking algorithm, an echo model is the key to radar altimeter design.
雷达高度计回波模型是设计、检验高度计跟踪算法的基础，是高度计设计的关键性环节。
First, we focus on the method of batch management, batch association, tracking BOM model, then propose the product tracking model and the algorithm that makes the tracking BOM based on time.
首先重点研究了批次管理的方法、批次关联、追踪bom模型，接着在此基础上提出了产品跟踪模型，并提出了基于时间的跟踪BOM生成算法。
The concept of an occlusion mesh model was introduced. A mesh tracking algorithm applied for occlusion was proposed.
引入遮挡网络模型的概念，提出了一种适用于遮挡的网格跟踪算法。
From mathematical model of target tracking, Performance of target tracking is impacted by three main factors of object state transition model, filtering algorithm and object modeling technique.
由目标跟踪的数学模型得出，影响目标跟踪性能的三个主要因素为目标状态转移模型、滤波算法和目标建模技术。
On the base of it, a decentralized bearings-only tracking algorithm based on the current statistical model was deduced and used to track bearings-only maneuvering target.
在此基础上，推导了基于当前统计模型的分散式纯方位跟踪算法并对纯方位机动目标实施跟踪。
The adaptive grid Interacting Multiple Model algorithm can adjust model parameter adaptively according to the target's mode, and thus realizes target tracking.
自适应网格交互多模算法能够根据目标的运动模式，自适应调整系统各模型参数，从而实现对目标的跟踪。
A new EMM algorithm for tracking maneuvering target is presented, which USES two models that consist of a normal CS model and an augmented CV model for interaction.
提出了一种使用两个模型实现对机动目标跟踪的多模型算法，采用当前统计模型和扩展后的常速模型组成的模型集进行交互。
Aiming at the problem of measurement conversion within the target tracking, a new algorithm combined best linear unbiased estimation with interacting multiple model methods is derived.
针对机动目标跟踪中常见的量测转换问题，提出了一种基于球坐标系下最优线性无偏估计滤波的交互多模型算法。
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。
A novel two-layer interactive multiple model (IMM) tracking algorithm for turn maneuver is proposed.
针对转弯机动目标跟踪，提出了一种两层交互多模型(IMM)跟踪算法。
On the basis of building target movement model and measuring equation, applying MGEKF algorithm, realizes the locating and tracking for mobile target.
在建立目标机动模型与测量方程的基础上，运用修正增益扩展卡尔曼滤波（MGEKF）算法，实现对机动目标进行定位与跟踪。
Because this algorithm use precision normal acceleration model, precision of tracking maneuvering target of algorithm is very well.
由于该算法对法向加速度精确建模，所以对机动目标的跟踪精度较高。
Because this algorithm USES precision normal acceleration model, precision of tracking maneuvering target of algorithm is very well.
由于该算法对法向加速度精确建模，所以对机动目标的跟踪精度较高。
Maneuvering target tracking algorithm based on adaptive Gauss model and EKF was built for improving the tracking performance in Multi-static systems.
为改善多基地雷达系统对高机动目标的跟踪性能，提出了基于自适应高斯模型和扩展卡尔曼滤波(ekf)的机动目标跟踪算法。
In this thesis, the related model and algorithm about moving objects detection and tracking are studied based on the visual information of time and space and their relationships.
本文利用视觉信息在时间和空间上的相关性，主要研究运动目标检测和跟踪的相关模型及算法。
So, we design a trajectory tracking algorithm based on NNs, considering both kinematic and dynamical model, and the simulation results demonstrate that this algorithm has good robustness.
因此，同时考虑机器人运动学和动力学模型，提出基于神经网络的轨迹跟踪算法，仿真结果表明算法具有较强的鲁棒性。
The paper describes an Adaptive Interacting Multiple-model(AIMM) algorithm for use in manoeuvring target tracking.
本文介绍了用于机动目标跟踪的自适应混合多模算法。
The variable structure multiple-model estimation filtering is the most effective approach for tracking maneuvering target, and the model set adaptation algorithm is the core of it.
变结构多模算法是最有效的机动目标跟踪滤波算法，其核心是模型集自适应策略。
The basic idea of the variable-structure multiple model algorithm is expatiated. A variable-structure IMM algorithm for tracking a maneuvering target is studied and designed.
将当前统计模型和变结构多模型估计算法相结合，阐述了变结构多模型算法的基本思想，研究和设计了一种用于跟踪机动目标的变结构交互多模型算法。
On this basis, combined with one sort of background updating model, vehicle tracking algorithm is presented through using two-dimension motion estimation technique in dynamic image processing.
在此基础上，使用动态图像处理技术中的二维运动估计技术，结合背景更新模型提出了一种车辆跟踪算法。
With the use of a robust error mapping function, an affine model-based target tracking algorithm is formulated, in which a quasi-Newton's iterative method is implemented in the optimization progress.
在采用一个鲁棒性匹配误差映射函数的基础上，使用一种类牛顿法的迭代优化方法实现了基于仿射模型的图像目标跟踪算法。
An adaptive tracking data rate algorithm based on interactive multi-model (IMM) is proposed.
针对交互式多模型(IMM)，提出一种自适应跟踪数据率的算法。
A rolling multiple model weighted average estimation algorithm is presented for tracking the fast time varying model parameters.
为了跟踪快时变参数，提出了一种滚动多模型加权平均参数估计算法。
Identification algorithm mix difference image method and 4-connected boundary tracking method, besides, we improved the difference image method and built a new moving detection model finally.
识别算法采用差影法与4邻域连通区域标记相结合，并对差影法进行改进，建立起一个新型的运动检测模型。
The interacting multiple model(IMM) algorithm has been shown to be one of the most effective estimation algorithms in the field of maneuvering target tracking.
在交互式多模型算法中引入神经网络算法以改进目标跟踪的精度。
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。
Proposes an algorithm of bi-iteration subspace tracking using instrumental variable, and it is a bi-iterate rank-one update model.
提出了一种运用辅助变量的双迭代子空间跟踪方法。
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