粒子滤波方法由于能够灵活地处理非线性非高斯系统而被广泛地应用。
Particle filter is widely used because of its flexibility to deal with the nonlinear non-Gaussian systems.
目前在信息融合领域广泛使用的融合算法是卡尔曼滤波，它在线性高斯模型下能得到最优估计，但在非线性非高斯模型下则无法应用。
The Kalman Filter is widely applied in the Information Fusion at the present, which can get the optimal estimate in the Linear-Gaussian model, but not applied in the nonlinear and non-Gaussian model.
由于我们实际生活中的系统基本上都是非线性的，因此本文研究的是专门用于非线性非高斯系统跟踪的粒子滤波算法(PF)的基本原理及其具体应用。
Since the real life systems basically are nonlinear, so this paper study the basic principles and specific applications of Particle Filter (PF) specially used for non-linear non-Gaussian tracking.
为了解决非线性、非高斯系统估计问题，讨论了一种新的滤波方法——高斯粒子滤波算法。
A new Gaussian particle filter (GPF) is discussed to solve estimation problems in nonlinear non-Gaussian systems.
在非线性、非高斯条件下进行动基座传递对准，如果采用卡尔曼滤波会出现误差较大甚至发散的问题。
In moving base transfer alignment under nonlinear and non-Gaussian situation, using Kalman Filtering could cause large error or even divergence.
粒子滤波算法由于其在非线性、非高斯模型中所表现出的优良性能，使得其越来越受到人们的重视。
Particle filter algorithm has shown its good performance in non-linear and non-Gaussian models and is paid more and more attention.
粒子滤波技术是近几年出现的一种非线性滤波技术，它适用于非线性系统以及非高斯噪声模型。
The particle filtering is a nonlinear filtering technology, which is suitable for the nonlinear system and non-Gaussian noise model.
本文提出了一种在非零均值非平稳高斯激励下获得非线性多自由度系统响应的等效线性化方法。
An equivalent linearization method for obtaining the response of nonlinear multi-degree-of-freedom dynamic systems to nonstationary gaussian excitation with nonzero mean is presented.
该文描述了基于贝叶斯推理的目标跟踪算法，可应用于非线性、非高斯系统中。
The paper introduces the target tracking algorithms based on Bayesian inference, which can be applied in the systems of nonlinearity and non-Gaussianity.
针对非线性、非高斯系统状态的在线估计问题，本文提出一种新的基于序贯重要性抽样的粒子滤波算法。
In this paper, a new particle filter based on sequential importance sampling (SIS) is proposed for the on-line estimation problem of non-Gauss nonlinear systems.
它可以处理模型方程为非线性、噪声分布为非高斯分布的问题，在许多领域得到了成功的应用。
The Particle Filter can resolve a problem on nonlinear and non-Gaussian model, and has been applied successfully in many fields.
本论文以非线性、非高斯噪声环境下的目标跟踪为主要背景，研究弹道导弹目标粒子滤波算法。
In this paper, research on particle filter algorithm for ballistic target tracking is carried on under the main background of nonlinearity, non-Gaussian noise.
天文导航系统是典型的非线性和噪声非高斯分布的系统。
Autonomous celestial navigation system is a typical nonlinear, non-Gaussian dynamic system.
首先，将拦截器反导作战模型考虑为一类非线性、非高斯追逃拦截问题，建立了噪声环境中追逐-逃逸对策模型；
First, based on the consideration that the model for anti-missiles is a nonlinear and non-Gaussian problem, a model is built of guiding a missile towards an evading agile target in noisy environments.
首先，将拦截器反导作战模型考虑为一类非线性、非高斯追逃拦截问题，建立了噪声环境中追逐-逃逸对策模型；
First, based on the consideration that the model for anti-missiles is a nonlinear and non-Gaussian problem, a model is built of guiding a missile towards an evading agile target in noisy environments.
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