基于修正扩展卡尔曼滤波和粒子滤波的混沌信号检测与跟踪  

Chaotic Signal Detection and Track Based on Modified Extended Kalman Filter and Particle Filtering

作　　者：徐茂格[1] 宋耀良[1] 刘力维[2] 

机构地区：[1]南京理工大学电子工程与光电技术学院,江苏南京210094 [2]南京理工大学理学院,江苏南京210094

出　　处：《南京理工大学学报》2007年第4期514-517,共4页Journal of Nanjing University of Science and Technology

基　　金：南京理工大学博士研究生创新培养基金

摘　　要：针对恶劣环境下混沌信号的检测与跟踪这一难题,以及基于一阶线性化的扩展卡尔曼滤波(EKF)技术存在的严重退化现象,提出了具有较强稳健性的修正EKF技术,获得了与Un-scented Kalman filter相匹配的性能。针对上述两种滤波方法在低信噪比情况下存在跟踪误差大的问题,为此引入了新颖的粒子滤波技术并且分析了该技术的可行性,最后仿真实验验证了该技术在低信噪比环境下的优越性。In view of the difficult problem in the chaotic signal detection and track in the abominable environments, and the degenerate phenomenon of the traditional extended Kalman filter （EKF） which is based on the first order linearization, a modified EKF is developed that has much better robustness than the traditional EKF and gets almost the same performance as the Unscented Kalman filter. The two filters mentioned above experience large track error in the low signal noise ratio （SNR）, and a novel particle filter which can be used in the nonlinear and non-Gaussian environ- ments is introduced and also its feasibility is analyzed. The simulation demonstrates the superiorities of particle filtering in the low SNR

关 键 词：混沌信号 信号检测 扩展卡尔曼滤波 粒子滤波 

分 类 号：TN911.23[电子电信—通信与信息系统]