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Abstract
To solve the problem that the time-frequency resolution of Short-Time Fourier Transform (STFT) is constrained by the window length and the moving step of the short time window, and to utilize the merits of a widely linear method, a novel instantaneous frequency estimation method in vector hydrophone was proposed. In this paper, a complex variable was constructed. It is composed of sound pressure and particle velocity as its real part and imaginary part, respectively. The constructed variable was approved to be second order noncircular (improper). For the modelling of noncircular signals, the standard linear estimation is not adequate and the pseudo-covariance matrix should also be taken into consideration. As a result, a widely linear adaptive instantaneous frequency estimation algorithm and its three solutions based on the augmented complex least mean square (ACLMS) method are presented to estimate the instantaneous frequency in vector hydrophones. The results of simulations and laboratory experiments prove that this approach based on a widely linear model performs better compared to STFT and strict linear filter methods.
Highlights
Instantaneous frequency estimation is an important issue in underwater acoustic signal processing.The most widely adopted method used to estimate the frequency in underwater acoustics systems is the Short-Time Fourier Transform (STFT), which is a traditional instantaneous frequency estimation method widely used in the time-frequency analysis field because of its simplicity
We propose to use the recently introduced widely linear modelling- based adaptive filtering algorithm, called the Augmented Complex Least Mean Square (ACLMS) to deal with instantaneous frequency estimation in vector hydrophones
The applied to estimate the fundamental frequency from sampled values of voltage signals in vector applied to estimate the fundamental frequency from sampled values of voltage signals in vector hydrophones, and andcompared comparedwith withthe thestandard standardCLMS
Summary
Instantaneous frequency estimation is an important issue in underwater acoustic signal processing. The sound pressure and particle velocity have a phase difference of 90◦ , which provides the possibility that a noncircular complex signal can be constructed and it can be used for widely linear frequency estimation based on the most recent advances in augmented complex-valued second order statistics. We propose to use the recently introduced widely linear modelling- based adaptive filtering algorithm, called the Augmented Complex Least Mean Square (ACLMS) to deal with instantaneous frequency estimation in vector hydrophones. This is a novel approach towards frequency estimation in underwater acoustic signal processing, because nearly no one has introduced this method in vector hydrophones before. Simulation results and the results of laboratory experiments prove that this widely linear based method performs better compared to STFT and other linear filtering methods
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