...增长带来了维数增大问题,该文提出了一种新的高斯粒子联合概率数据关联滤波算法（GP-JPDAF）,在JPDA框架中引入高斯粒子滤波（GPF）的思想,通过高斯粒子而不是高斯量,来近似目标与观测的边缘关联概率,利用GPF计算目标状态的预测及更新分布。
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...6期—龙源期刊网 关键词：高斯粒子滤波; 非线性滤波; 目标跟踪; 重要性密度函数 [gap=726]Key words: Gaussian particle filter; nonlinear filter; target tracking; importance density function ..
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与高斯粒子滤波 Gaussian Particle Filter ; GPF
化无迹高斯粒子滤波 Simplified Unscented Gaussian Particle Filter
提出了高斯粒子滤波器 GPF ; GaussianParticle Filter
简化无迹高斯粒子滤波 Simplified Unscented Gaussian Particle Filter
高斯和粒子滤波 GSPF ; gaussian sum particle filter
高斯-厄米特粒子滤波 GHPF
高斯加和粒子滤波器 Gaussian sum particle filter
高斯混合采样粒子滤波 GMSPPF
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.
将TVAR模型的信号和反射系数矢量增广为状态矢量后，应用高斯粒子滤波器(GPF)估计TVAR的模型参数，构造了语音增强算法。
When TVAR model signal and reflection coefficients were extended to state vector, Gaussian Particle Filter (GPF) was applied to estimate parameters of TVAR model.
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.
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