Underwater target axis-frequency magnetic field detection background noise suppression and line spectrum enhancement method and device

Abstract

The present invention provides a method and device for underwater target axial-frequency magnetic field detection bottom noise suppression and line spectrum enhancement, including: performing Fourier transform on the target data segment to obtain the first noise amplitude spectrum and phase spectrum, performing Fourier transform on each segment of noise data segment to obtain a plurality of second noise amplitude spectra, and performing smoothing filtering on the noise amplitude spectra; superimposing the amplitude spectra of each segment to obtain an average amplitude spectrum as the bottom noise amplitude spectrum, and synthesizing a complete bottom noise frequency spectrum in combination with the phase spectrum of the target data segment; performing inverse Fourier transform on the estimated bottom noise frequency spectrum, and subtracting the estimated bottom noise time series from the target data segment; performing power spectrum analysis on the target data segment after noise reduction to obtain the axial-frequency line spectrum after noise reduction, and obtaining the line spectrum diagram of the target data segment according to the axial-frequency line spectrum; performing line spectrum detection on the line spectrum diagram of the target data segment. Applying the technical solution of the present invention can solve the technical problem that it is difficult to identify the line spectrum due to the large bottom noise intensity in the existing underwater target axial-frequency magnetic field detection.

Description

Technical Field

[0001] The present invention relates to the technical fields of geophysics and underwater target detection technology, and particularly relates to a method and device for suppressing background noise and enhancing line spectrum in underwater target axial frequency magnetic field detection. Background Art

[0002] Axial frequency magnetic field is an extremely low frequency alternating magnetic field generated by the rotation modulation of the main shaft of underwater targets such as propellers, which corrodes and prevents corrosion current. It has rich time-domain and frequency-domain information and is an important detection object for identifying and tracking underwater moving targets. In the marine environment, the axial frequency magnetic field will be superimposed with various environmental noise interferences, resulting in a large background noise intensity, weak target signals, and limited detectable range of underwater targets. Existing axial frequency magnetic field signal processing methods mainly include adaptive filtering, high-order spectrum analysis, wavelet transform, etc. The adaptive filtering algorithm needs to construct a reference signal, or approximately construct a reference signal by means such as shifting. When the original data is severely interfered by noise, it is difficult to construct the reference signal; the high-order spectrum analysis method can suppress Gaussian colored noise and symmetrically distributed noise, but it is mainly used in the case of relatively high signal-to-noise ratio, and the spectrum analysis effect is limited in the case of low signal-to-noise ratio. The wavelet transform method is mainly used to separate noise interferences that are significantly different from the target in the time scale, and the noise separation effect is affected by the selection of different wavelet basis functions. In summary, when the data background noise is strong, the existing signal processing methods have limited noise reduction ability and insufficient recognition ability for the target axial frequency line spectrum. Therefore, it is of great significance to study the background noise suppression and line spectrum enhancement methods starting from the original data of the underwater target axial frequency magnetic field. Summary of the Invention

[0003] The present invention provides a method and device for suppressing background noise and enhancing line spectrum in underwater target axial frequency magnetic field detection, which can solve the technical problem of difficult line spectrum recognition caused by large background noise intensity in existing underwater target axial frequency magnetic field detection.

[0004] According to one aspect of the present invention, a method for suppressing the background noise and enhancing the line spectrum of the shaft-frequency magnetic field detection of underwater targets is provided. The method for suppressing the background noise and enhancing the line spectrum of the shaft-frequency magnetic field detection of underwater targets includes: Step 1, observing multiple segments of shaft-frequency magnetic field data, selecting any one segment of the shaft-frequency magnetic field data as the target data segment, and the remaining segments as the noise data segments; Step 2, performing Fourier transform on the target data segment to obtain the first noise amplitude spectrum and phase spectrum, performing Fourier transform on each segment of the noise data segments to obtain multiple second noise amplitude spectra, and performing smoothing filtering on the first noise amplitude spectrum and the multiple second noise amplitude spectra to suppress the line spectrum signals in the noise; Step 3, superimposing the amplitude spectra of each segment after smoothing filtering to obtain the average amplitude spectrum as the background noise amplitude spectrum, and synthesizing the complete background noise spectrum in combination with the phase spectrum of the target data segment; Step 4, performing inverse Fourier transform on the estimated background noise spectrum to obtain the background noise time series, and subtracting the estimated background noise time series from the target data segment to obtain the denoised target data segment; Step 5, performing power spectrum analysis on the denoised target data segment to obtain the denoised shaft-frequency line spectrum, and obtaining the line spectrum diagram of the target data segment according to the denoised shaft-frequency line spectrum; Step 6, performing line spectrum detection on the line spectrum diagram of the target data segment, analyzing the local maxima in the line spectrum diagram of the target data segment, and judging whether there is a multiple relationship between the corresponding frequency points. If there is no multiple relationship, select the next data segment as the target data segment, and the remaining segments as the noise data segments, and repeat the above process until there is a multiple relationship between the frequency points corresponding to the local maxima in the line spectrum diagram of the target data segment; If there is a multiple relationship between the frequency points corresponding to the local maxima in the line spectrum diagram of the target data segment, complete the line spectrum detection and signal-to-noise ratio evaluation according to the line spectrum diagram of the target data segment, and realize the suppression of the background noise and the enhancement of the line spectrum of the shaft-frequency magnetic field detection of underwater targets.

[0005] Further, the amplitude spectra of each segment of noise after smoothing filtering are where f is the frequency point after Fourier transform, A i (f) is the noise amplitude spectrum of each data segment, fft() is the Fourier transform operator, || is the absolute value symbol, smooth() is the smoothing filtering operator, and S k (t) is the k-th shaft-frequency data segment.

[0006] Further, the average amplitude spectrum can be calculated according to for acquisition.

[0007] Further, the complete background noise spectrum can be calculated according to for acquisition, where i is the imaginary symbol, is the phase spectrum obtained by performing Fourier transform on the target data segment, angle() is the operator for taking the phase of the Fourier transform result, and S o (t) is the target data segment.

[0008] Further, the background noise time series can be obtained according to calculation, where ifft() is the inverse Fourier transform operator and real() is the real part extraction operator.

[0009] Further, the target data segment after noise reduction is X o (t) = S o (t) - NT(t), where S o (t) is the target data segment and NT(t) is the background noise time series.

[0010] Further, the signal-to-noise ratio of the target data segment after noise reduction can be calculated according to where n is the frequency point f corresponding to the shaft frequency line spectrum 0 , 2f 0 , 3f 0 ,......, nf 0 , P(n) is the amplitude of each shaft frequency line spectrum, m is the other frequency points except the shaft frequency line spectrum, and P(m) is the amplitude of each other frequency point except the shaft frequency line spectrum.

[0011] According to another aspect of the present invention, there is provided an underwater target shaft frequency magnetic field detection background noise suppression and line spectrum enhancement system, and the underwater target shaft frequency magnetic field detection background noise suppression and line spectrum enhancement system uses the underwater target shaft frequency magnetic field detection background noise suppression and line spectrum enhancement method as described above for background noise suppression and line spectrum enhancement.

[0012] According to still another aspect of the present invention, there is provided a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the underwater target shaft frequency magnetic field detection background noise suppression and line spectrum enhancement method as described above.

[0013] According to yet another aspect of the present invention, there is provided a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of an underwater target shaft frequency magnetic field detection background noise suppression and line spectrum enhancement method as described above.

[0014] Applying the technical solution of the present invention, a method for suppressing the background noise and enhancing the line spectrum of underwater target shaft frequency magnetic field detection is provided. By observing multi-segment shaft frequency magnetic field data, since it is unknown which data segment the target signal is located in during actual operation, any one of the data segments is taken as the target data segment, and the remaining segments are noise data segments. Fourier transforms are respectively performed on the target data segment and each noise data segment to obtain amplitude spectra, and smoothing filtering is performed on each amplitude spectrum to suppress the line spectrum signals in the noise. The amplitude spectra of each segment are superimposed to obtain an average amplitude spectrum as the background noise amplitude spectrum, and a complete background noise spectrum is synthesized in combination with the phase spectrum of the target data segment. Fourier inverse transform is performed on the estimated background noise spectrum to obtain a background noise time series, and the estimated background noise time series is subtracted from the target data segment to obtain a denoised target data segment. Power spectrum analysis is performed on the denoised target data segment to obtain a line spectrum diagram of the denoised target data segment, and the local maxima in the line spectrum diagram of the target data segment are analyzed. If there is no multiple relationship between the frequency points corresponding to the local maxima in the line spectrum diagram of the target data segment, it indicates that the selected data segment does not contain the target signal. At this time, the next data segment is selected as the target data segment, and the remaining segments are noise data segments, and the above process is repeated until there is a multiple relationship between the frequency points corresponding to the local maxima in the line spectrum diagram of the target data segment. Line spectrum detection and signal-to-noise ratio evaluation are completed according to the line spectrum diagram of the target data segment, realizing background noise suppression and line spectrum enhancement of underwater target shaft frequency magnetic field detection. Therefore, compared with the prior art, the method for suppressing the background noise and enhancing the line spectrum of underwater target shaft frequency magnetic field detection provided by the present invention can realize background noise suppression and line spectrum enhancement of underwater target shaft frequency magnetic field detection, and thus effectively solve the technical problem that it is difficult to identify the line spectrum due to the large background noise intensity in the existing underwater target shaft frequency magnetic field detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings included are used to provide a further understanding of the embodiments of the present invention, and constitute a part of the specification, for illustrating the embodiments of the present invention, and are used to explain the principles of the present invention together with the text description. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings without creative efforts based on these drawings.

[0016] Figure 1 FIG. shows a flowchart of a method for suppressing background noise and enhancing line spectrum of underwater target shaft frequency magnetic field detection according to a specific embodiment of the present invention;

[0017] Figure 2a FIG. shows a time series signal before background noise suppression when the target data segment contains shaft frequency signals according to a specific embodiment of the present invention;

[0018] Figure 2b FIG. shows a time series signal after background noise suppression when the target data segment contains shaft frequency signals according to a specific embodiment of the present invention;

[0019] Figure 3a Shows the line spectrogram before background noise suppression when the target data segment provided according to a specific embodiment of the present invention contains shaft frequency signals;

[0020] Figure 3b Shows the line spectrogram after background noise suppression when the target data segment provided according to a specific embodiment of the present invention contains shaft frequency signals;

[0021] Figure 4a Shows the schematic diagram of the time series signal before background noise suppression when the target data segment provided according to a specific embodiment of the present invention is pure noise data;

[0022] Figure 4b Shows the schematic diagram of the time series signal after background noise suppression when the target data segment provided according to a specific embodiment of the present invention is pure noise data;

[0023] Figure 5a Shows the line spectrogram before background noise suppression when the target data segment provided according to a specific embodiment of the present invention is pure noise data;

[0024] Figure 5b Shows the line spectrogram after background noise suppression when the target data segment provided according to a specific embodiment of the present invention is pure noise data. Detailed implementation manners

[0025] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and in no way limits the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0026] It should be noted that the terms used herein are only for describing specific implementation manners and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless otherwise clearly specified in the context, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0027] Unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present invention. At the same time, it should be understood that, for the sake of convenience of description, the dimensions of the various parts shown in the drawings are not drawn in actual proportional relationship. Technologies, methods, and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and devices should be regarded as part of the authorization specification. In all the examples shown and discussed here, any specific value should be construed as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that like reference numerals and letters denote like items in the following drawings, and thus, once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0028] As Figures 1 to 5b shown, according to a specific embodiment of the present invention, a method for underwater target shaft-frequency magnetic field detection bottom noise suppression and line spectrum enhancement is provided. The method for underwater target shaft-frequency magnetic field detection bottom noise suppression and line spectrum enhancement includes: Step 1, observing multiple segments of shaft-frequency magnetic field data, and selecting any one segment of shaft-frequency magnetic field data from the multiple segments as the target data segment, and the remaining segments as noise data segments; Step 2, performing Fourier transform on the target data segment to obtain the first noise amplitude spectrum and phase spectrum, performing Fourier transform on each segment of noise data segments to obtain multiple second noise amplitude spectra, and performing smoothing filtering on the first noise amplitude spectrum and the multiple second noise amplitude spectra to suppress the line spectrum signals in the noise; Step 3, superimposing the amplitude spectra of each segment after smoothing filtering to obtain the average amplitude spectrum as the bottom noise amplitude spectrum, and synthesizing the complete bottom noise spectrum in combination with the phase spectrum of the target data segment; Step 4, performing inverse Fourier transform on the estimated bottom noise spectrum to obtain the bottom noise time series, and subtracting the estimated bottom noise time series from the target data segment to obtain the target data segment after noise reduction; Step 5, performing power spectrum analysis on the target data segment after noise reduction to obtain the shaft-frequency line spectrum after noise reduction, and obtaining the line spectrum diagram of the target data segment according to the shaft-frequency line spectrum after noise reduction; Step 6, performing line spectrum detection on the line spectrum diagram of the target data segment, analyzing the local maxima in the line spectrum diagram of the target data segment, and judging whether there is a multiple relationship between the corresponding frequency points. If there is no multiple relationship, then select the next data segment as the target data segment, and the remaining segments as noise data segments, and repeat the above process until there is a multiple relationship between the frequency points corresponding to the local maxima in the line spectrum diagram of the target data segment; If there is a multiple relationship between the frequency points corresponding to the local maxima in the line spectrum diagram of the target data segment, complete the line spectrum detection and signal-to-noise ratio evaluation according to the line spectrum diagram of the target data segment, and realize underwater target shaft-frequency magnetic field detection bottom noise suppression and line spectrum enhancement.

[0029] Using this configuration method, a method for suppressing the background noise and enhancing the line spectrum of underwater target shaft-frequency magnetic field detection is provided. By observing multi-segment shaft-frequency magnetic field data, since it is unknown which data segment the target signal is located in during actual operation, any one of the data segments is taken as the target data segment, and the remaining segments are taken as noise data segments; the Fourier transform is respectively performed on the target data segment and each noise data segment to obtain the amplitude spectrum, and the amplitude spectrum of each segment is smoothed and filtered to suppress the line spectrum signal in the noise; the amplitude spectra of each segment are superimposed to obtain the average amplitude spectrum as the background noise amplitude spectrum, and the complete background noise spectrum is synthesized by combining the phase spectrum of the target data segment; the inverse Fourier transform is performed on the estimated background noise spectrum to obtain the background noise time series, and the estimated background noise time series is subtracted from the target data segment to obtain the denoised target data segment; the power spectrum analysis is performed on the denoised target data segment to obtain the line spectrum diagram of the denoised target data segment, and the local maximum values in the line spectrum diagram of the target data segment are analyzed. If there is no multiple relationship between the frequency points corresponding to the local maximum values in the line spectrum diagram of the target data segment, it indicates that the selected data segment does not contain the target signal. At this time, the next data segment is selected as the target data segment, and the remaining segments are taken as noise data segments, and the above process is repeated until there is a multiple relationship between the frequency points corresponding to the local maximum values in the line spectrum diagram of the target data segment. The line spectrum detection and signal-to-noise ratio evaluation are completed according to the line spectrum diagram of the target data segment, realizing the suppression of the background noise and the enhancement of the line spectrum of underwater target shaft-frequency magnetic field detection. Therefore, compared with the prior art, the method for suppressing the background noise and enhancing the line spectrum of underwater target shaft-frequency magnetic field detection provided by the present invention can realize the suppression of the background noise and the enhancement of the line spectrum of underwater target shaft-frequency magnetic field detection, and thus effectively solve the technical problem that it is difficult to identify the line spectrum due to the large background noise intensity in the existing underwater target shaft-frequency magnetic field detection.

[0030] Specifically, in the present invention, in order to realize the suppression of the background noise and the enhancement of the line spectrum of underwater target shaft-frequency magnetic field detection, it is first necessary to observe multi-segment shaft-frequency magnetic field data, and select any one of the multi-segment shaft-frequency magnetic field data as the target data segment, and the remaining segments as the noise data segments.

[0031] As a specific embodiment of the present invention, in shaft-frequency magnetic field detection, the data background noise is mainly caused by environmental noises such as geology, diurnal variation, and thunderstorms. Its time-frequency domain characteristics are basically stable and change little within a certain time and range. The shaft-frequency magnetic field signal is mainly generated by underwater moving targets. Compared with environmental noise, its signal intensity is small, the duration is short, and there are obvious line spectrum characteristics, which are significantly different from environmental noise. Therefore, multi-segment shaft-frequency magnetic field data are continuously observed within a period of time. Most of each segment is slowly changing environmental noise, and only individual data segments may contain target signals. Suppose the original shaft-frequency data observed is shown in the following formula:

[0032]

[0033] where t is the observation time, Sk (t) is the original data, including N data segments (t 1 ~t 2 ,t 2 ~t 3 ,t 3 ~t 4 ,t 4 ~t 5 ,……,t N-1 ~t N ). Then mark the data segment that needs to be detected as the target data segment S o (t), and the rest of the segments are noise data segments S n (t). For example, when it is necessary to determine whether there is a target signal at time t 3 ~t 4 , then mark S 3 (t) as the target data segment, and the rest of the segments are noise data segments, and then perform subsequent processing.

[0034] Furthermore, after selecting the target data segment and the noise data segments, the Fourier transform can be performed on the target data segment to obtain the first noise amplitude spectrum and phase spectrum, and the Fourier transform is performed on each noise data segment to obtain a plurality of second noise amplitude spectra, and the first noise amplitude spectrum and the plurality of second noise amplitude spectra are smoothed and filtered to suppress the line spectrum signals in the noise.

[0035] As a specific embodiment of the present invention, in actual work, whether there is an underwater target signal and in which data segment it exists are both unknown. Therefore, the target data segment and each noise data segment are used together for background noise estimation. First, the Fourier transform is performed on the target data segment and each noise data segment respectively. For the noise data segment, only the amplitude spectrum of each segment is retained. For the target data segment, while retaining the amplitude spectrum, the phase spectrum is also retained for the subsequent step three to synthesize the complete noise spectrum. Then the amplitude spectrum of the target data segment and the amplitude spectra of each noise data segment are used together to estimate the background noise amplitude spectrum. Because the underwater target state is unknown, there may be shaft frequency signals in both the target data segment and each noise data segment. At this time, there will be shaft frequency line spectra in the noise amplitude spectrum, which will bring deviations to the background noise estimation result. Therefore, it is necessary to suppress the possible line spectrum signals in the noise amplitude spectrum. The line spectrum signals are manifested as discrete line spectra. Therefore, smoothing and filtering the noise amplitude spectrum can suppress the line spectrum signals and retain the slowly changing background noise spectrum. The noise amplitude spectrum after the above processing is shown in the following formula:

[0036]

[0037] Among them, f is the frequency point after Fourier transform, A i(f) is the noise amplitude spectrum of each data segment, fft() is the Fourier transform operator, || is the absolute value symbol, smooth() is the smoothing filter operator, and S k (t) is the k-th shaft frequency data segment.

[0038] Furthermore, after performing smoothing filtering on the first noise amplitude spectrum and multiple second noise amplitude spectra to suppress the line spectrum signals in the noise, the amplitude spectra of each segment after smoothing filtering can be superimposed to obtain the average amplitude spectrum as the background noise amplitude spectrum, and the complete background noise spectrum can be synthesized by combining the phase spectrum of the target data segment.

[0039] As a specific embodiment of the present invention, the estimated noise amplitude spectra of each data segment represent the noise frequency domain distribution characteristics of each time period. Further, the amplitude spectra of each segment are superimposed to obtain the average amplitude spectrum as shown in the following formula:

[0040]

[0041] wherein, through superposition averaging, the random perturbation components of the irregular parts superimposed on the noise amplitude spectrum can be eliminated, so as to extract the common components of the noise amplitude spectra in different time periods, and then use them as the estimated results of the background noise amplitude spectrum. Then, using the phase spectrum of the target data segment as the phase spectrum of the background noise of this segment, the complete background noise spectrum NF(f) is synthesized, as shown in the following formula:

[0042]

[0043] wherein, i is the imaginary symbol, is the phase spectrum obtained by performing Fourier transform on the target data segment, as follows:

[0044]

[0045] wherein, angle() is the operator for taking the phase of the Fourier transform result, and S o (t) is the target data segment.

[0046] Furthermore, after synthesizing the complete background noise spectrum, the estimated background noise spectrum can be subjected to inverse Fourier transform to obtain the background noise time series, and the estimated background noise time series is subtracted from the target data segment to obtain the denoised target data segment.

[0047] As a specific embodiment of the present invention, the inverse Fourier transform is performed on the synthesized complete background noise spectrum NF(f). Since the result of the inverse Fourier transform is a complex number, its real part is taken to obtain the estimated result NT(t) of the background noise time series, as shown in the following formula:

[0048]

[0049] Among them, ifft() is the inverse Fourier transform operator, and real() is the real part extraction operator. Then, from the target data segment S o (t), subtract the estimated background noise time series NT(t) to obtain the denoised target data segment X o (t), as shown in the following formula:

[0050] X o (t) = S o (t) - NT(t).

[0051] Furthermore, after obtaining the denoised target data segment, the denoised target data segment can be subjected to power spectrum analysis to obtain the denoised shaft frequency line spectrum, and based on the denoised shaft frequency line spectrum, the line spectrum diagram of the target data segment can be obtained.

[0052] As a specific embodiment of the present invention, the denoised target data segment is subjected to power spectrum analysis to obtain the denoised shaft frequency line spectrum, and then the amplitude spectrum P o (f) is obtained by taking the square root, as shown in the following formula:

[0053]

[0054] Among them, P o (f) is the equivalent amplitude spectrum, and PSD is the power spectrum analysis operator. Based on P o (f), the line spectrum diagram of the target data segment can be plotted.

[0055] Furthermore, after obtaining the line spectrum diagram of the target data segment, the line spectrum diagram of the target data segment can be subjected to line spectrum detection, analyze the local maxima in the line spectrum diagram of the target data segment, and determine whether there is a multiple relationship between the corresponding frequency points. If there is no multiple relationship, then select the next data segment as the target data segment, and the remaining segments as noise data segments, and repeat the above process until there is a multiple relationship between the frequency points corresponding to the local maxima in the line spectrum diagram of the target data segment; if there is a multiple relationship between the frequency points corresponding to the local maxima in the line spectrum diagram of the target data segment, complete the line spectrum detection and signal-to-noise ratio evaluation according to the line spectrum diagram of the target data segment, and realize the background noise suppression and line spectrum enhancement of underwater target shaft frequency magnetic field detection.

[0056] As a specific embodiment of the present invention, perform line spectrum detection on the line spectrum diagram of the target data segment, that is, analyze the local maxima in the line spectrum diagram, and determine whether there is a multiple relationship between the corresponding frequency points, that is, whether the frequency points corresponding to the local maxima satisfy f 0 , 2f 0 , 3f 0 ,......, nf 0 's distribution law. If the above law is satisfied, it indicates that there is a shaft frequency line spectrum signal, and the fundamental frequency is f 0At this time, the signal-to-noise ratio is calculated according to the following formula:

[0057]

[0058] where n is the frequency point f corresponding to the shaft frequency line spectrum 0 , 2f 0 , 3f 0 ,......, nf 0 , P(n) is the amplitude of each shaft frequency line spectrum, m is the other frequency points except the shaft frequency line spectrum, and P(m) is the amplitude of each other frequency point except the shaft frequency line spectrum. According to the original target data segment S o (t) and the data segment X o (t) after background noise suppression, the equivalent amplitude spectrum is calculated, and then the signal-to-noise ratios SNR origin and SNR denoise before and after noise reduction are obtained. The signal-to-noise ratio gain of the shaft frequency line spectrum can be calculated:

[0059] SNR gain = SNR denoise - SNR original

[0060] Through the above steps of processing, the background noise suppression and line spectrum enhancement of the shaft frequency magnetic field detection can be completed.

[0061] According to another aspect of the present invention, there is provided an underwater target shaft frequency magnetic field detection background noise suppression and line spectrum enhancement system, and this underwater target shaft frequency magnetic field detection background noise suppression and line spectrum enhancement system uses the underwater target shaft frequency magnetic field detection background noise suppression and line spectrum enhancement method as described above for background noise suppression and line spectrum enhancement.

[0062] By applying this configuration method, an underwater target shaft-frequency magnetic field detection background noise suppression and line spectrum enhancement system is provided. The system observes multi-segment shaft-frequency magnetic field data. Since it is unknown which data segment the target signal is located in during actual operation, any one of the data segments is used as the target data segment, and the remaining segments are used as noise data segments. Fourier transforms are respectively performed on the target data segment and each noise data segment to obtain amplitude spectra, and smoothing filtering is performed on each amplitude spectrum to suppress the line spectrum signals in the noise. The amplitude spectra of each segment are superimposed to obtain an average amplitude spectrum as the background noise amplitude spectrum, and a complete background noise spectrum is synthesized in combination with the phase spectrum of the target data segment. The estimated background noise spectrum is subjected to an inverse Fourier transform to obtain a background noise time series, and the estimated background noise time series is subtracted from the target data segment to obtain a denoised target data segment. Power spectrum analysis is performed on the denoised target data segment to obtain a line spectrum diagram of the denoised target data segment, and the local maxima in the line spectrum diagram of the target data segment are analyzed. If there is no multiple relationship between the frequency points corresponding to the local maxima in the line spectrum diagram of the target data segment, it indicates that the selected data segment does not contain the target signal. At this time, the next data segment is selected as the target data segment, and the remaining segments are used as noise data segments, and the above process is repeated until there is a multiple relationship between the frequency points corresponding to the local maxima in the line spectrum diagram of the target data segment. Line spectrum detection and signal-to-noise ratio evaluation are completed according to the line spectrum diagram of the target data segment, realizing underwater target shaft-frequency magnetic field detection background noise suppression and line spectrum enhancement. Therefore, compared with the prior art, the underwater target shaft-frequency magnetic field detection background noise suppression and line spectrum enhancement system provided by the present invention can achieve underwater target shaft-frequency magnetic field detection background noise suppression and line spectrum enhancement, and thus effectively solve the technical problem of difficult line spectrum recognition caused by high background noise intensity in existing underwater target shaft-frequency magnetic field detection.

[0063] According to another aspect of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the underwater target shaft-frequency magnetic field detection background noise suppression and line spectrum enhancement method as described above.

[0064] According to still another aspect of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, wherein the computer program, when executed by the processor, implements the steps of an underwater target shaft-frequency magnetic field detection background noise suppression and line spectrum enhancement method as described above.

[0065] For a further understanding of the present invention, the following combines Figures 1 to 5b to elaborate in detail on the underwater target shaft-frequency magnetic field detection background noise suppression and line spectrum enhancement method provided by the present invention.

[0066] As Figures 1 to 5bAs shown, a method for underwater target shaft-frequency magnetic field detection bottom noise suppression and line spectrum enhancement according to a specific embodiment of the present invention includes: Step 1, observing multiple segments of shaft-frequency magnetic field data, selecting any one segment of shaft-frequency magnetic field data from the multiple segments as the target data segment, and the remaining segments as noise data segments; Step 2, performing Fourier transform on the target data segment to obtain the first noise amplitude spectrum and phase spectrum, performing Fourier transform on each segment of noise data segment to obtain the second noise amplitude spectrum, and performing smoothing filtering on the first noise amplitude spectrum and multiple second noise amplitude spectra to suppress the line spectrum signal in the noise; Step 3, superimposing the amplitude spectra of each segment after smoothing filtering to obtain the average amplitude spectrum as the bottom noise amplitude spectrum, and synthesizing the complete bottom noise frequency spectrum in combination with the phase spectrum of the target data segment; Step 4, performing inverse Fourier transform on the estimated bottom noise frequency spectrum to obtain the bottom noise time series, and subtracting the estimated bottom noise time series from the target data segment to obtain the denoised target data segment; Step 5, performing power spectrum analysis on the denoised target data segment to obtain the shaft-frequency line spectrum after denoising, and obtaining the line spectrum diagram of the target data segment according to the shaft-frequency line spectrum after denoising; Step 6, performing line spectrum detection on the line spectrum diagram of the target data segment, analyzing the local maximum values in the line spectrum diagram of the target data segment, and judging whether there is a multiple relationship between the corresponding frequency points. If there is no multiple relationship, select the next data segment as the target data segment, and the remaining segments as noise data segments, and repeat the above process until there is a multiple relationship between the frequency points corresponding to the local maximum values in the line spectrum diagram of the target data segment; If there is a multiple relationship between the frequency points corresponding to the local maximum values in the line spectrum diagram of the target data segment, complete the line spectrum detection and signal-to-noise ratio evaluation according to the line spectrum diagram of the target data segment, and realize underwater target shaft-frequency magnetic field detection bottom noise suppression and line spectrum enhancement.

[0067] The performance of this method is analyzed through simulation data. A set of shaft-frequency magnetic field time series with noise interference and four sets of pure noise interference time series are simulated and generated. First, use the shaft-frequency magnetic field time series with noise interference as the target data segment, and the remaining four sets of pure noise interference time series as noise data segments, and process them according to Step 2 to Step 5 to obtain the time series signals of the target data segment before and after bottom noise suppression as Figure 2a and Figure 2b shown. Before bottom noise suppression, the peak-to-peak value of the data is about 47 pT, and after bottom noise suppression, the peak-to-peak value of the data is about 22 pT. The line spectrum diagram of the target data segment after bottom noise suppression is obtained through power spectrum analysis as Figure 3b shown. Through bottom noise suppression, the shaft-frequency magnetic field line spectra of 1 Hz, 2 Hz, 3 Hz, 4 Hz, 5 Hz, 6 Hz, 7 Hz, 8 Hz, 9 Hz, and 10 Hz are enhanced, and it is calculated that the signal-to-noise ratio of the shaft-frequency line spectrum after bottom noise suppression is increased by about 4 dB.

[0068] Since it is unknown which data segment the target signal is located in during actual work, further use a certain pure noise time series as the target data segment, the shaft frequency magnetic field time series with noise interference and the other four pure noise time series as the noise data segments, and process them according to steps two to five to obtain the time series signals of the target data segment before and after background noise suppression as Figure 4a and Figure 4b shown. Before background noise suppression, the peak-to-peak value of the data is about 38 pT, and after background noise suppression, the peak-to-peak value of the data is about 17 pT. The line spectrum diagram of the target data segment after background noise suppression is obtained through power spectrum analysis as Figure 5b shown. After background noise suppression, the amplitude spectrum of the data decreases, and at the same time, there is no shaft frequency line spectrum with a multiple relationship between frequency points, indicating that the processing method in this paper will not bring false anomalies of shaft frequency line spectra.

[0069] In summary, the present invention provides a method for background noise suppression and line spectrum enhancement of underwater target shaft frequency magnetic field detection. By observing multiple segments of shaft frequency magnetic field data, since it is unknown which data segment the target signal is located in during actual work, any one of the data segments is used as the target data segment, and the remaining segments are used as the noise data segments; Fourier transforms are respectively performed on the target data segment and each noise data segment to obtain the amplitude spectra, and smoothing filtering is performed on each amplitude spectrum to suppress the line spectrum signals in the noise; the amplitude spectra of each segment are superimposed to obtain the average amplitude spectrum as the background noise amplitude spectrum, and the complete background noise spectrum is synthesized in combination with the phase spectrum of the target data segment; the estimated background noise spectrum is subjected to inverse Fourier transform to obtain the background noise time series, and the estimated background noise time series is subtracted from the target data segment to obtain the target data segment after noise reduction; power spectrum analysis is performed on the target data segment after noise reduction to obtain the line spectrum diagram of the target data segment after noise reduction, and the local maxima in the line spectrum diagram of the target data segment are analyzed. If there is no multiple relationship between the frequency points corresponding to the local maxima in the line spectrum diagram of the target data segment, it means that the selected data segment does not contain the target signal. At this time, select the next data segment as the target data segment, and the remaining segments as the noise data segments, and repeat the above process until there is a multiple relationship between the frequency points corresponding to the local maxima in the line spectrum diagram of the target data segment. Line spectrum detection and signal-to-noise ratio evaluation are completed according to the line spectrum diagram of the target data segment, and background noise suppression and line spectrum enhancement of underwater target shaft frequency magnetic field detection are realized. Therefore, compared with the prior art, the method for background noise suppression and line spectrum enhancement of underwater target shaft frequency magnetic field detection provided by the present invention can realize background noise suppression and line spectrum enhancement of underwater target shaft frequency magnetic field detection, and thus effectively solve the technical problem that it is difficult to identify line spectra due to the large background noise intensity in existing underwater target shaft frequency magnetic field detection.

[0070] For ease of description, spatial relative terms such as "above", "over", "on the upper surface", "upper" etc. can be used here to describe the spatial positional relationship of a device or feature shown in the figure with other devices or features. It should be understood that the spatial relative terms are intended to encompass different orientations in use or operation in addition to the orientation depicted in the figure. For example, if the device in the figure is inverted, the device described as "above" or "over" other devices or structures will then be positioned "below" or "under" other devices or structures. Thus, the exemplary term "above" can include both the orientations of "above" and "below". The device can also be positioned in other different ways (rotated 90 degrees or in other orientations), and corresponding interpretations should be made for the spatial relative descriptions used here.

[0071] In addition, it should be noted that the use of terms such as "first", "second" etc. to limit components is only for the convenience of differentiating the corresponding components. Without additional statements, the above terms have no special meanings, and thus should not be construed as limiting the protection scope of the present invention.

[0072] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for suppressing background noise and enhancing line spectrum in underwater target axial frequency magnetic field detection, characterized in that: The method for suppressing background noise and enhancing line spectrum in underwater target axial frequency magnetic field detection comprises: Step 1, observing multiple sections of shaft-frequency magnetic field data, selecting any section of shaft-frequency magnetic field data from the multiple sections of shaft-frequency magnetic field data as a target data section, and the remaining sections as noise data sections; Step 2: Performing Fourier transformation on the target data segment to obtain a first noise amplitude spectrum and a phase spectrum, performing Fourier transformation on each noise data segment to obtain a plurality of second noise amplitude spectra, and performing smoothing filtering on the first noise amplitude spectrum and the plurality of second noise amplitude spectra to suppress line spectrum signals in the noise; Step 3, superimposing the amplitude spectra of each segment after smoothing filtering to obtain an average amplitude spectrum as the background noise amplitude spectrum, and combining the phase spectrum of the target data segment to synthesize a complete background noise spectrum; Step 4, performing inverse Fourier transform on the estimated background noise spectrum to obtain a background noise time series, and subtracting the estimated background noise time series from the target data segment to obtain a denoised target data segment; Step 5, performing power spectrum analysis on the target data segment after noise reduction to obtain the axial frequency line spectrum after noise reduction, and obtaining the line spectrum diagram of the target data segment according to the axial frequency line spectrum after noise reduction; Step six, perform line spectrum detection on the target data segment line spectrum, analyze the local maximum in the target data segment line spectrum, and determine whether there is a multiple relationship between the corresponding frequency points. If there is no multiple relationship, select the next data segment as the target data segment, and the remaining segments as noise data segments. Repeat the above process until there is a multiple relationship between the frequency points corresponding to the local maximum in the target data segment line spectrum; if there is a multiple relationship between the frequency points corresponding to the local maximum in the target data segment line spectrum, complete line spectrum detection and signal-to-noise ratio evaluation according to the target data segment line spectrum, and realize the background noise suppression and line spectrum enhancement of underwater target axial frequency magnetic field detection.

2. The method for suppressing background noise and enhancing line spectrum of underwater target shaft frequency magnetic field detection according to claim 1, characterized in that: The noise amplitude spectrum of each segment after smoothing filtering is: k=1,2,3,...,N, where f is the frequency after Fourier transform, A k (f) is the noise amplitude spectrum of each data segment, fft() is the Fourier transform operator, || is the absolute value sign, smooth() is the smoothing filter operator, S k (t) is the kth axis frequency data segment.

3. The method for suppressing background noise and enhancing line spectrum of underwater target shaft frequency magnetic field detection according to claim 2, characterized in that: The average amplitude spectrum According to k=1,2,3,...,N is calculated and obtained.

4. The method for suppressing background noise and enhancing line spectrum of underwater target shaft frequency magnetic field detection according to claim 3 is characterized in that: The complete noise floor spectrum can be obtained according to Calculate and obtain, where i is the imaginary number symbol, is the phase spectrum obtained by Fourier transforming the target data segment, angle() is the operator for taking the phase of the Fourier transform result, S o (t) is the target data segment.

5. The method for suppressing background noise and enhancing line spectrum of underwater target shaft frequency magnetic field detection according to claim 4, characterized in that: The background noise time series can be based on Calculate and obtain, where ifft() is the inverse Fourier transform operator and real() is the real part operator.

6. The method for suppressing background noise and enhancing line spectrum of underwater target shaft frequency magnetic field detection according to claim 5, characterized in that: The target data segment after noise reduction is X o (t) = S o (t)-NT(t), where S o (t) is the target data segment, and NT(t) is the background noise time series.

7. The method for suppressing background noise and enhancing line spectrum of underwater target shaft frequency magnetic field detection according to claim 6, characterized in that: The signal-to-noise ratio of the target data segment after noise reduction can be calculated based on Among them, n is the frequency point f0, 2f0, 3f0, ..., nf0 corresponding to the axial frequency line spectrum, P (n) is the amplitude of each axial frequency line spectrum, m is the other frequency point except the axial frequency line spectrum, and P (m) is the amplitude of each other frequency point except the axial frequency line spectrum.

8. A system for suppressing background noise and enhancing line spectrum for underwater target axial frequency magnetic field detection, characterized in that: The underwater target shaft frequency magnetic field detection The background noise suppression and line spectrum enhancement system uses the underwater target shaft frequency magnetic field detection as described in any one of claims 1 to 7 The background noise suppression and line spectrum enhancement method performs background noise suppression and line spectrum enhancement.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: The processor executes the computer program to implement the steps of the method for suppressing background noise and enhancing line spectrum in underwater target axial frequency magnetic field detection according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of a method for suppressing background noise and enhancing line spectrum in underwater target axial frequency magnetic field detection as described in any one of claims 1 to 7 are implemented.

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