The dissertation demonstrates the maneuvering target imaging model with acceleration and rotating motion and its signal processing to solve attitude perturbation of the targets.
针对机动目标存在的姿态扰动，研究了具有加速度和旋转运动的机动目标成像模型及其信号处理过程。
This paper presents an interactive multiple model algorithm (IMM) utilizing adaptive turn rate models to track a maneuvering target.
给出了一种利用自适应转弯速率模型的IMM跟踪算法，可以用于机动目标的跟踪中。
The Stochastic mathematic model of maneuvering reentry warhead was proposed, and the rational slide switch surface was chosen based on the desire of attacking ground target.
建立了机动再入弹头随机数学模型，根据攻击目标的要求选择合理的滑模变结构开关面。
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。
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。
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。
In view of maneuvering target tracking in cluttered environment, this paper reviews two existing gating techniques, namely, Model Based gating (MBG) and Centralized gating (CG).
针对杂波环境下跟踪机动目标问题，研究了两种现行的跟踪门，模型跟踪门(mbg)和集中跟踪门(CG)。
For resolving the important problem in engineering accomplishing, an adaptive statistical model of target maneuvering was proposed.
为解决工程实现的关键问题，提出了目标机动加速度模型。
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。
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。
With the algorithm, the current state of maneuvering target can be estimated directly and correctly without assuming the model of maneuvering acceleration.
该算法不需要假定目标的机动加速度模型，而是直接正确地估计出机动目标的当前状态，不存在任何估计滞后与修正问题。
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。
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。
Because this algorithm can estimate the normal and tangent acceleration, it may be used to implement the tracking for the complexly and highly maneuvering target after appropriate model-set design.
由于本算法能够估计出目标的法向和切向加速度，进行适当的模型集设计后，可以实现对复杂、快速机动目标的全过程跟踪，具有可扩展性的应用前景。
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。
One maneuvering target tracking method in which RBF neural network is applied to correct Kalman filter result in standard Interacting Multi Model (IMM) is proposed in this paper.
文中提出了一种应用rbf神经网络对标准IMM算法中的卡尔曼滤波结果进行校正的方法。
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。
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。
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