摘要
针对扩频系统中的干扰抑制问题,本文首先将其建模为附加约束的最小化均值输出能量(MMOE)问题,然后借助正交分解将约束MMOE转化为无约束最小均方误差(MMSE),接着通过选择合适的状态变量、建立合适的状态方程和观测方程得到盲Kalman滤波(BKF)算法,最后分析了BKF算法性能.研究表明:BKF的收敛性能与输入相关矩阵几乎无关,能快速跟踪环境变化,稳态干扰抑制性能逼近最优性能;明显优于盲最小均方(BLMS)和盲递推最小二乘(BRLS)算法.
In this paper,the interference suppression of spread spectrum systems is treated as constrained minimum mean output energy（MMOE）.After an orthogonal decompose procedure for transforming the MMOE problem to unconstrained minimum mean square error（MMSE） one and a construction for state equation and observation equation,and then the blind Kalman filtering（BKF）,i.e.,absence of a desire signal,is developed and analyzed.The research results indicate that the BKF algorithm is insensitive to variations in the correlation matrix,fast response to the changing environment,and close to level of optimization with iterative operation.Hence,it is superior to the blind least mean square（BLMS） and blind recursive least squares（BRLS） algorithms.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2011年第10期2444-2448,共5页
Acta Electronica Sinica
关键词
扩频
干扰抑制
最小均值输出能量
盲最小均方算法
盲递推最小二乘算法
盲Kalman滤波
spread spectrum
interference suppression
minimum mean output energy（MMOE）
blind least mean square（BLMS） algorithm
blind recursive least squares（BRLS） algorithm
blind Kalman filtering（BKF）
