摘要
针对杂波干扰环境中的非高斯特性,发现海杂波噪声、闪烁噪声等具有显著尖峰的非高斯噪声可以采用α稳定分布来描述,用α稳定分布可以建立更符合实际的噪声模型。根据统计信号处理最新理论和技术,利用p阶分数相关和分数低阶协方差替代传统相关和协方差来改进Kalman滤波器,优化获得改进的基于分数低阶统计量Kalman滤波交互多模型算法(Based FLOS-Kalman-IMM),仿真验证了Based FLOS-Kalman-IMM滤波跟踪新算法可以更好地适应非高斯复杂环境,得到稳健的雷达跟踪效果。
Aimed at non-Gaussian characteristics in clutter jamming environment, this paper studies the significant peak non-Gaussian noises, such as sea clutter noise and glint noise, which can be described by al- pha stable distribution. The more practical noise model can be established by use of the alpha stable distribu- tion. According to the lastest theory and technology of statistic signal processing, p order fractional associat- ed and fractional lower order covariance is used to modify Kalman filter. The optimized fractional lower order covariance Kalman filter interacting multiple model algorithm is introduced to the target tracking for compli- cated non-Gaussian situation and the solid radar tracking effect is achieved.
出处
《雷达科学与技术》
2012年第4期391-395,共5页
Radar Science and Technology
关键词
雷达目标跟踪
非高斯杂波
KALMAN滤波
Α稳定分布
分数低阶统计量
交互多模型
radar target tracking
non-Gaussian clutter
Kalman filter
alpha stable distribution
frac-tional lower order statistics
interacting multiple model
作者简介
石一鸣女，1985年出生，黑龙江哈尔滨人，硕士研究生，助理工程师，研究方向为脉冲雷达测量与控制、信号处理等。E-mail：shiyimingl218@163．com
