Sinusoidal Signal Estimation at Low Signal-to-Noise Ratio

• Main Authors: Kuen-Chang Lin, 林坤昌
• Other Authors: Wen-Rong Wu
• Format: Others
• Language: en_US
• Published: 1994
• Online Access: http://ndltd.ncl.edu.tw/handle/14412882053276732682

碩士 === 國立交通大學 === 電信研究所 === 82 === Sinusoidal estimation in additive white noise is one of important problems in digital signal processing. In this thesis, techniques for estimating sinusoidal signals at low SNR are presented. Our approach is to apply conventional estimators in the subband domain. For block estimation, we choose the iterative filtering algorithm as the frequency estimator. For adaptive estimation, we use the prediction error filtering. Besides, we also propose a new type of adaptive LMS algorithm to reduce the influence of white noise. Simulation results show that sinusoidal estimation in the subband domain gives better performance than that in the full-band, and our new adaptive algorithm outperform the conventional ones.