Abstract
Adaptive filtering has the advantages of real-time processing, small computational complexity, and good adaptability and robustness. It has been widely used in communication, navigation, signal processing, optical fiber sensing, and other fields. In this paper, by adding an interferometer with the same parameters as the signal interferometer as the reference channel, the sensing signal of the interferometric fiber-optic hydrophone is denoised by two adaptive filtering schemes based on the least mean square (LMS) algorithm and the normalized least mean square (NLMS) algorithm respectively. The results show that the LMS algorithm is superior to the NLMS algorithm in reducing total harmonic distortion, improving the signal-to-noise ratio and filtering effect.
Highlights
In many studies of fiber optic hydrophone, the source of noise in the system is mainly the noise generated by the light source and other optical transmissions, in addition to environmental factors such as vibration, bending, and temperature changes
The other is the normalized least mean square (NLMS) algorithm, the fixed step size parameters α are tested in advance, 0.2 is the best value, and the step size parameter changes with the energy of x (n)
Adaptive filtering could adjust its own parameters with signal changes to achieve the best filtering effect
Summary
In many studies of fiber optic hydrophone, the source of noise in the system is mainly the noise generated by the light source and other optical transmissions, in addition to environmental factors such as vibration, bending, and temperature changes. It causes random changes in parameters such as length and refractive index, and introduces strong background noise in the system [1,2,3]. From the perspective of real-time processing and convergence speed, the least mean square algorithm (LMS) and the normalized least mean square algorithm (NLMS) are used to compare the noise reduction effects of the two adaptive algorithms in the fiber optic hydrophone
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
