A Method for Reconstructing Sonar Listening Signals Applicable to Different Sampling Frequencies

Abstract

The present invention discloses a method for reconstructing sonar listening signals applicable to different sampling frequencies. According to the sampling frequency fs1 of the original listening signal and the sampling frequency fs2 of the audio conversion module, the nearest point n1 in the original listening signal corresponding to the m1 point of the reconstructed signal is determined. Using a low-pass filter, the sonar listening signal is reconstructed into a signal adapted to the sampling frequency of the audio conversion module through the sum of multiple weighted sinc functions after shifting. The present invention solves the problem of the mismatch between the sampling frequency of the sonar listening signal and the sampling frequency of the audio conversion module. This method eliminates the upsampling and downsampling operations and has a small computational load.

Description

Technical Field:

[0001] The present invention relates to the field of sonar array signal processing for listening, and particularly to a method for reconstructing sonar listening signals applicable to different sampling frequencies. Background Art:

[0002] Sonar listening is an artificial recognition method that uses the human ear for listening and recognition, and is also a way for sonar operators to detect targets at an early stage. After decades of actual combat applications, this method has been proven to be an effective way to discriminate underwater targets. The listening signal of the sonar passes through a band-pass filter, and the band-pass operator of the filter can be selected. The listening signal provided by the sonar is transmitted to the audio conversion module through a network. The audio conversion module converts the digital signal into an analog signal through digital-to-analog conversion, and then sends it to a speaker or earphone through analog filtering and power amplification to achieve listening.

[0003] In actual engineering applications, the sampling frequency of the audio conversion module is determined at the beginning of the design and there is only one, while the sampling frequencies of different sonars may be different. When the audio conversion module is applied to different sonars, it will cause a mismatch in the sampling frequency, thus affecting the listening effect. Therefore, it is necessary to reconstruct the sonar listening signal. The traditional signal reconstruction method is to first determine the least common multiple sampling frequency of the sampling frequency of the audio conversion module and the sampling frequency of the sonar listening signal, then perform upsampling processing on the listening signal to the least common multiple sampling frequency, and then downsample it to the sampling frequency of the audio conversion module. This method mainly completes signal reconstruction through upsampling and downsampling. This reconstruction method has the following defects: when the least common multiple of the sampling frequency of the audio conversion module and the sampling frequency of the listening signal is very large, the computational complexity of the upsampling and downsampling operations will increase sharply. Summary of the Invention:

[0004] The technical problem to be solved by the present invention is to provide a method for reconstructing sonar listening signals applicable to different sampling frequencies to solve the deficiencies of the prior art. By using a low-pass filter, a signal adapted to the sampling frequency of the audio conversion module is reconstructed from the sonar listening signal through the sum of multiple weighted sinc functions after shifting, solving the problem of mismatch between the sampling frequency of the sonar listening signal and the sampling frequency of the audio conversion module. This method eliminates the upsampling and downsampling operations and has a small computational complexity.

[0005] The technical solution of the present invention is to provide a method for reconstructing sonar listening signals applicable to different sampling frequencies, and the method is as follows.

[0006] Assume that the sampling frequency of the original sonar listening signal is fs1, and the data sequence is x(n), where n represents the length of the sequence data, n = 0, 1,..., N - 1; the sampling frequency of the audio conversion module is fs2, and the reconstructed signal is y(m), where m = 0, 1,..., M - 1.

[0007] Set a low-pass filter, and its impulse response is

[0008]

[0009] where k is the filter length;

[0010] The listening signal passes through this filter to obtain a new reconstructed signal, that is

[0011]

[0012] The above formula is the formula for reconstructing a new signal from the original listening signal after changing the sampling frequency. This formula is an interpolation formula, and the interpolation function is sinc. A new signal is reconstructed by the sum of k weighted and shifted sinc functions.

[0013] Preferably, it includes the following steps.

[0014] (1) According to the sampling frequency fs1 of the original listening signal and the sampling frequency fs2 of the audio conversion module, determine the nearest point n1 in the original listening signal corresponding to the m1-th point of the reconstructed signal, where [] is the rounding operation;

[0015] (2) Determine the length k of the filter and construct the filter

[0016] (3) After the original listening signal passes through this filter, the output result of the m1-th point is obtained, that is

[0017]

[0018] (4) Repeat steps (1) to (3) to complete the signal reconstruction.

[0019] After adopting the above solution, compared with the prior art, the present invention has the following advantages:

[0020] Pass the listening signal provided by the sonar through a low-pass filter, and reconstruct a signal adapted to the sampling frequency of the audio conversion module through the sum of multiple weighted and shifted sinc functions. This method eliminates the upsampling and downsampling operations and has a small computational amount. Description of the Drawings:

[0021] Figure 1Time-domain results of the original signal and the reconstructed signal in the embodiments of the present invention;

[0022] Figure 2 Frequency-spectrum results of the original signal and the reconstructed signal in the embodiments of the present invention;

[0023] Figure 3 is a partially enlarged view of the frequency-spectrum results of the original signal and the reconstructed signal in the embodiments of the present invention. Specific embodiments:

[0024] The present invention will be further described in detail below in conjunction with the accompanying drawings in terms of specific embodiments:

[0025] A sonar listening signal reconstruction method applicable to different sampling frequencies includes the following steps.

[0026] (1) Determine the nearest point n1 in the original listening signal corresponding to the m1-th point of the reconstructed signal according to the sampling frequency fs1 of the original listening signal and the sampling frequency fs2 of the audio conversion module, where [] represents the rounding operation;

[0027] (2) Determine the length k of the filter and construct the filter

[0028] (3) The output result of the m1-th point is obtained after the original listening signal passes through this filter, that is,

[0029]

[0030] (4) Repeat steps (1) to (3) to complete the signal reconstruction.

[0031] The original sonar listening signal is a sine signal with a frequency of 1000 Hz and a sampling frequency of 18000 Hz. Assume that the sampling frequency of the audio conversion module is 24000 Hz. The number of points of the original listening signal is 9000, the number of points of the reconstructed signal is 12000, and the length of the filter is taken as 32. The time-domain results and frequency-spectrum results of the reconstructed signal are as shown in Figure 1 、 Figure 2 、 Figure 3 shown.

[0032] From Figure 1 、 Figure 2 and Figure 3 it can be seen that the reconstructed signal is basically consistent with the original signal both in the time domain and in the frequency domain. There are only minor errors in the frequency domain, but the order of magnitude of the errors is only 10 -4 level, and the errors are very small and do not affect engineering use.

[0033] The above description is only for the preferred embodiments of the present invention and should not be construed as a limitation on the claims. Any equivalent structure or equivalent process transformation made using the description of the present invention is included within the scope of the patent protection of the present invention.

Claims

1. A method for reconstructing sonar listening signals applicable to different sampling frequencies, characterized in that: The method is as follows: Assume that the sampling frequency of the original acoustic detection signal provided by the sonar is fs1, and the data sequence is x(n), where n represents the length of the sequence data, n = 0, 1,..., N - 1; the sampling frequency of the audio conversion module is fs2, and the reconstructed signal is y(m), where m = 0, 1,..., M - 1. A low-pass filter is set, and its sampling response is where k is the filter length, and n1 is the point in the original audition signal that is closest to the m1-th point of the reconstructed signal. [] represents the rounding operation. The original listening signal passes through this filter to obtain a new reconstructed signal, that is 2. The method for reconstructing sonar listening signals applicable to different sampling frequencies according to claim 1, wherein: It includes the following steps: (1) According to the sampling frequency fs1 of the original listening signal and the sampling frequency fs2 of the audio conversion module, determine the closest point n1 in the original listening signal corresponding to the m1-th point of the reconstructed signal; (2) Determine the length k of the filter and construct the filter n = n1 - k + 1,..., n1 + k (3) After the original listening signal passes through this filter, the output result of the m1-th point is obtained, that is (4) Repeat steps (1) to (3) to complete the signal reconstruction.

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