摘要
Ｂｅｒｎｏｕｌｉ－Ｇａｕｓｓｉａｎ白噪声的检测存在于具有跳变输入的Ｋａｌｍａｎ滤波与最优平滑等问题中，邻近信号间的干扰和信号点数目无限增多是其中存在的两个主要问题．针对上述问题提出了一种基于最优平滑反卷积的Ｂｅｒｎｏｕｌｉ－Ｇａｕｓｓｉａｎ白噪声检测方法和新的多值信号建模方法，并基于固定区间平滑的频域性质和极大似然原理，给出了一个最优似然比检测指标．仿真表明，该方法具有好的分辨率，为存在波形重叠信号的高分辨检测提供了新的途径．
,In detection of Bernoulli Gaussian processes for Kalman filtering and optimal smoothing with jumping input sequences, two main traditional difficulties are the interference from adjacent signals and the infinite increase of the number of detected signals. To solve these problems, a new detection method based on optimal deconvolution and a new modeling strategy for the multi valued input signals are proposed. Then, based on the frequency domain properties of fixed interval optimal smoothing and maximum likelihood principle, an optimal likelihood ratio detection index is derived. Simulation shows that the proposed method has high resolution and is a good candidate for the detection of signals with intersymbol interference.
出处
《自动化学报》
EI
CSCD
北大核心
1998年第2期179-185,共7页
Acta Automatica Sinica
基金
中国博士后科学基金
关键词
极大似然估计
码间干扰
BG白噪声
地震信号处理
,Detection, optimal smoothing, maximum likelihood estimation, likelihood ratio index, intersymbol interference
