An Improved Multi-Ridge Extraction Method Based on Differential Synchro-Squeezing Wavelet Transform
06 Jul 2021-IEEE Access (Institute of Electrical and Electronics Engineers (IEEE))-Vol. 9, pp 96763-96774
TL;DR: In this paper, an improved multi-ridge extraction method based on differential synchro-squeezing wavelet transform (DSWT) was proposed to reduce the computation time and image noise of SWT.
Abstract: It is very important to accurately extract the instantaneous frequency (IF) of complex non-stationary signals, so the signal processing methods based on IF are widely used in engineering. However, in non-stationary complex vibration signals, it is difficult to extract the instantaneous frequency under strong noise because the frequency changes rapidly. This paper proposes an improved multi-ridge extraction method based on differential synchro-squeezing wavelet transform (DSWT). First, an improved method DSWT is proposed to reduce the computation time and image noise of synchro-squeezing wavelet transform (SWT). The running time of the algorithm can be further reduced by segmenting the signal and compressing the time-frequency matrix. The image noise can be significantly reduced by differentiating SWT time-frequency matrix. It lays a good foundation for the extraction of the time-frequency ridge line. Secondly, an improved multi-ridge extraction method is proposed. The ridge jump due to end effect can be eliminated adaptively in segmented extraction. It further improves the time-frequency aggregation and extraction effect of the wavelet ridgeline image. Finally, the improved multi-ridge extraction method based on DSWT (DSWT-IMRE) is verified by the simulation data and experimental data under different conditions. Compared with the method proposed in previous study, the results show that DSWT-IMRE has higher extraction accuracy.
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TL;DR: In this paper , the authors used a single hydrophone to estimate the motion parameters of an AUV from the underwater acoustic signal excited by its propulsion motor, and then used the cumulative phase difference power amplification instantaneous frequency estimation method.
Abstract: This paper describes the use of a single hydrophone to estimate the motion parameters of an autonomous underwater vehicle (AUV) from the underwater acoustic signal excited by its propulsion motor. First, the frequency range of the hydroacoustic signal radiated by the AUV motor is determined, and a detection and recognition model is designed. In the case of uniform linear motion of the AUV, the geometric relationship between the Doppler frequency shift curve of the sound source is derived and the motion model of the sound source and sound line propagation is established. An estimation algorithm for the motion parameters of multiple AUVs based on data from a single hydrophone is derived. Then, for Doppler underwater acoustic signals disturbed by independent identically distributed noise with an arbitrary probability distribution, a cumulative phase difference power amplification instantaneous frequency estimation method is proposed. This method is based on the sum of multiple logarithmic functions. Finally, the effectiveness and accuracy of the algorithm in estimating the motion parameters of multiple AUVs are verified through simulations and experiments.
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TL;DR: A generalization of the short-time Fourier-based synchrosqueezing transform using a new local estimate of instantaneous frequency enables not only to achieve a highly concentrated time-frequency representation for a wide variety of amplitude- and frequency-modulated multicomponent signals but also to reconstruct their modes with a high accuracy.
Abstract: This paper puts forward a generalization of the short-time Fourier-based synchrosqueezing transform using a new local estimate of instantaneous frequency. Such a technique enables not only to achieve a highly concentrated time-frequency representation for a wide variety of amplitude- and frequency-modulated multicomponent signals but also to reconstruct their modes with a high accuracy. Numerical investigation on synthetic and gravitational-wave signals shows the efficiency of this new approach.
282 citations
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TL;DR: In this paper, a continuous wavelet transform is used to extract reliably the different components of the modulation model and the parameters characterizing them, and the results of a first test of the use of the synchro-squeezed representation for speaker identification are presented.
Abstract: This chapter aims to incorporate the wavelet transform and auditory nerve-based models into a tool that could be used for speaker identification, in the hope that the results would be more robust to noise than the standard methods. It utilizes the continuous wavelet transform to extract reliably the different components of the modulation model and the parameters characterizing them. The chapter shows that results of a first test of the use of the synchro-squeezed representation for speaker identification. It also shows that some results: the “untreated” wavelet transform of a speech segment, its squeezed and synchrosqueezed versions, and the extraction of the parameters used for speaker identification. The whole construction is based on a continuous wavelet transform. In practice, this is of course a discrete but very redundant transform, heavily oversampled both in time and in scale. The chapter concludes with some pointers to and comparisons with similar work in the literature, and with sketching possible future directions.
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