In this paper, research on particle filter algorithm for ballistic target tracking is carried on under the main background of nonlinearity, non-Gaussian noise.
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。
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。
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.
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。
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.
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。
The Particle Filter can resolve a problem on nonlinear and non-Gaussian model, and has been applied successfully in many fields.
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。
A new Gaussian particle filter (GPF) is discussed to solve estimation problems in nonlinear non-Gaussian systems.
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。
In MMW radar tracking, the classical Kalman filter will degrade seriously when observation noise is non-Gaussian because of target glint.
在毫米波雷达目标跟踪中，角闪烁的非高斯特性将使得经典的卡尔曼滤波器失效。
Particle filter is widely used because of its flexibility to deal with the nonlinear non-Gaussian systems.
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。
The receiver structure based on discrete-time bistable system is designed for the constant binary signal detection, and it is compared with the matched filter in some cases of non-Gaussian noise.
然后根据离散时间双稳态系统，设计了处理常值二进制信号的接收器结构，在一些非高斯噪声下对接收器的检测性能与匹配滤波器进行了比较分析。
The receiver structure based on discrete-time bistable system is designed for the constant binary signal detection, and it is compared with the matched filter in some cases of non-Gaussian noise.
然后根据离散时间双稳态系统，设计了处理常值二进制信号的接收器结构，在一些非高斯噪声下对接收器的检测性能与匹配滤波器进行了比较分析。
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