Open AccessApplication of adaptive line enhancer based on NLMS algorithm in shaft-rate electric field signal detection
Author(s) -
Wenshi Zeng,
Qiang Bian,
Yude Tong
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1930/1/012015
Subject(s) - electric field , signal (programming language) , rate of convergence , algorithm , feature (linguistics) , field (mathematics) , computer science , acoustics , control theory (sociology) , mathematics , artificial intelligence , physics , telecommunications , channel (broadcasting) , linguistics , philosophy , quantum mechanics , pure mathematics , programming language , control (management)
There is lots of useful signal feature in ship’s shaft-rate electric field. Extracting the signal feature is vital in underwater target recognition. In order to extract the feature of the shaft-rate electric field, the shaft-rate electric field is processed by ALE based on NLMS. The improved NLMS algorithm is proposed to construct an adaptive line-spectrum enhancer, and then the measured data of shaft-rate electric field is processed by ALE. The results show that the algorithm can effectively separate the weak shaft frequency electric field signal from the broadband background noise at low SNR. Compared with the ordinary ALE, the algorithm has more significant effect in improving SNR, faster convergence speed and smaller steady-state error, which greatly improves the detection ability of ship shaft frequency electric field.