Improved time-frequency phase difference spectrum-based extremely low frequency electromagnetic signal detection method and system

Abstract

The application discloses a method and system for detecting extremely low frequency electromagnetic signals based on an improved time-frequency phase difference spectrum, and relates to the field of ocean electromagnetic signal detection, and comprises the following steps: calculating a time-frequency phase difference spectrum of a target signal and noise, wherein the target signal is an extremely low frequency electromagnetic signal; and performing non-dimensional processing on the time-frequency phase difference spectrum by an exponential weight mask mapping method to obtain a weighted coherence spectrum, which is used for detecting the extremely low frequency electromagnetic signal. The application has superior performance in the identification and separation of extremely low frequency electromagnetic signals and has important engineering application value.

Description

Technical Field

[0001] This invention relates to the field of marine electromagnetic signal detection, and more specifically, to a method and system for detecting extremely low frequency electromagnetic signals based on an improved time-frequency phase difference spectrum. Background Technology

[0002] The seabed electromagnetic detection station not only receives signals from controllable sources, but also simultaneously captures extremely low frequency electromagnetic signals generated by ship propulsion systems. These signals have significant harmonic characteristics and relatively stable periodicity, making them a potential source of interference in traditional marine geophysical exploration. Currently, it is difficult to effectively distinguish between marine environmental noise and target signals in signal detection. Summary of the Invention

[0003] To address the aforementioned problems, the present invention aims to provide an extremely low frequency electromagnetic signal detection technology, which effectively distinguishes marine environmental noise from target signals.

[0004] To achieve the above technical objectives, this application provides a method for detecting extremely low frequency electromagnetic signals based on an improved time-frequency phase difference spectrum, comprising the following steps: Calculate the time-frequency phase difference spectrum between the target signal and the noise, where the target signal is an extremely low-frequency electromagnetic signal; By using an exponential weighted mask mapping method, the time-frequency phase difference spectrum is dimensionlessly processed to obtain a weighted coherence spectrum, which is used for the detection of extremely low frequency electromagnetic signals.

[0005] Preferably, when acquiring the target signal, the target signal is simulated according to the magnetic dipole model, with a fundamental frequency of 2Hz, containing multiple harmonics, and Gaussian noise with a signal-to-noise ratio of 5 is added.

[0006] Preferably, when acquiring the time-frequency phase difference spectrum, a pair of orthogonal magnetic field component time series are collected, and after discretization, the time-frequency phase difference spectrum is obtained.

[0007] Preferably, when acquiring the time-frequency phase difference spectrum, the signal is discretized by short-time Fourier transform.

[0008] Preferably, when acquiring the weighted coherence spectrum, a local window is set, and the local phase difference standard deviation of the phase difference spectrum is calculated to obtain the final weighted mask of the exponential weighted mask mapping. The weighted coherence spectrum is obtained by weighting the time-frequency coherence.

[0009] Preferably, when obtaining the final weight mask, the final weight mask is obtained by calculating the root mean square deviation of the phase difference between adjacent time-frequency regions, and the exponential weight mask is mapped to the final weight mask.

[0010] This invention also discloses an ultra-low frequency electromagnetic signal detection system based on an improved time-frequency phase difference spectrum, used to implement the aforementioned ultra-low frequency electromagnetic signal detection method based on an improved time-frequency phase difference spectrum, comprising: The signal processing module is used to calculate the time-frequency phase difference spectrum between the target signal and the noise, wherein the target signal is an extremely low-frequency electromagnetic signal; The signal detection module is used to perform dimensionless processing on the time-frequency phase difference spectrum through an exponential weighted mask mapping method to obtain a weighted coherence spectrum, which is used to detect extremely low frequency electromagnetic signals.

[0011] Preferably, the target signal is obtained by simulation based on a magnetic dipole model, with a fundamental frequency of 2Hz, containing multiple harmonics, and Gaussian noise with a signal-to-noise ratio of 5 is added.

[0012] Preferably, the signal processing module is used to acquire a pair of orthogonal magnetic field component time series, perform discretization representation, and obtain the time-frequency phase difference spectrum, wherein the signal discretization processing is performed by short-time Fourier transform.

[0013] Preferably, the signal detection module is used to set a local window, calculate the local phase difference standard deviation of the phase difference spectrum to obtain the final weight mask of the exponential weight mask mapping, and obtain the weighted coherence spectrum by weighting the time-frequency coherence. The final weight mask of the exponential weight mask mapping is obtained by calculating the root mean square deviation of the phase difference in adjacent time-frequency regions.

[0014] The present invention discloses the following technical effects: This invention achieves deep fusion of phase difference features and power spectrum features through an exponential weighted mask, significantly improving signal feature utilization and detection clarity. This invention has superior performance in the identification and separation of extremely low frequency electromagnetic signals and has important engineering application value. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the joint detection process described in this invention; Figure 2 This is a simulated extremely low frequency magnetic field signal diagram as described in this invention; Figure 3 This is the time-frequency phase difference spectrum of the simulated signal described in this invention; Figure 4It is an exponentially weighted mask of the time-frequency phase difference spectrum of the simulated signal described in this invention; Figure 5 It is the weighted coherence spectrum of the joint detection described in this invention; Figure 6 It is the weighted coherence spectrum of the measured noise signal described in this invention; Figure 7 This is the weighted coherence spectrum of the measured extremely low frequency magnetic field signal described in this invention; Figure 8 This is a schematic diagram of the method described in this invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0018] like Figures 1-8 As shown, this invention provides a method for detecting extremely low frequency electromagnetic signals based on an improved time-frequency phase difference spectrum, comprising the following steps: Calculate the time-frequency phase difference spectrum between the target signal and the noise, where the target signal is an extremely low-frequency electromagnetic signal; By using an exponential weighted mask mapping method, the time-frequency phase difference spectrum is dimensionlessly processed to obtain a weighted coherence spectrum, which is used for the detection of extremely low frequency electromagnetic signals.

[0019] More preferably, the ultra-low frequency electromagnetic signal detection method based on the improved time-frequency phase difference spectrum provided by the present invention simulates the target signal according to the magnetic dipole model when acquiring the target signal. The fundamental frequency is 2Hz, it contains multiple harmonics, and Gaussian noise with a signal-to-noise ratio of 5 is added.

[0020] More preferably, the ultra-low frequency electromagnetic signal detection method based on the improved time-frequency phase difference spectrum provided by the present invention acquires a pair of orthogonal magnetic field component time series when acquiring the time-frequency phase difference spectrum, and then discretizes and represents them to obtain the time-frequency phase difference spectrum.

[0021] More preferably, the ultra-low frequency electromagnetic signal detection method based on the improved time-frequency phase difference spectrum provided by the present invention performs signal discretization processing through short-time Fourier transform when acquiring the time-frequency phase difference spectrum.

[0022] More preferably, the ultra-low frequency electromagnetic signal detection method based on the improved time-frequency phase difference spectrum provided by the present invention sets a local window and calculates the local phase difference standard deviation of the phase difference spectrum when acquiring the weighted coherence spectrum to obtain the final weighted mask of the exponential weighted mask mapping. By weighting the time-frequency coherence, the weighted coherence spectrum is obtained.

[0023] More preferably, the ultra-low frequency electromagnetic signal detection method based on the improved time-frequency phase difference spectrum provided by the present invention obtains the final weight mask by calculating the root mean square deviation of the phase difference in adjacent time-frequency regions and mapping the final weight mask to an exponential weight mask.

[0024] This invention discloses an ultra-low frequency electromagnetic signal detection system based on an improved time-frequency phase difference spectrum, used to implement the aforementioned ultra-low frequency electromagnetic signal detection method based on an improved time-frequency phase difference spectrum, comprising: The signal processing module is used to calculate the time-frequency phase difference spectrum between the target signal and the noise, wherein the target signal is an extremely low-frequency electromagnetic signal; The signal detection module is used to perform dimensionless processing on the time-frequency phase difference spectrum through an exponential weighted mask mapping method to obtain a weighted coherence spectrum, which is used to detect extremely low frequency electromagnetic signals.

[0025] More preferably, the target signal of the ultra-low frequency electromagnetic signal detection system based on the improved time-frequency phase difference spectrum disclosed in this invention is obtained by simulation based on the magnetic dipole model, with a fundamental frequency of 2Hz, containing multiple harmonics, and Gaussian noise with a signal-to-noise ratio of 5 added.

[0026] More preferably, the signal processing module of the ultra-low frequency electromagnetic signal detection system based on the improved time-frequency phase difference spectrum disclosed in this invention is used to acquire a pair of orthogonal magnetic field component time series, and after discretization, obtain the time-frequency phase difference spectrum, wherein the signal discretization processing is performed by short-time Fourier transform.

[0027] Further preferably, the signal detection module of the ultra-low frequency electromagnetic signal detection system based on the improved time-frequency phase difference spectrum disclosed in this invention is used to set a local window, calculate the local phase difference standard deviation of the phase difference spectrum to obtain the final weight mask of the exponential weight mask mapping, and obtain the weighted coherence spectrum by weighting the time-frequency coherence. In this case, the final weight mask of the exponential weight mask mapping is obtained by calculating the root mean square deviation of the phase difference in the adjacent time-frequency regions.

[0028] Example 1: This invention provides a method for detecting low-frequency electromagnetic signals of the axial pole based on an improved time-frequency phase difference spectrum, specifically including the following: Step 1: Calculate the time-frequency phase difference spectrum between the target signal and the noise: Based on the time series of a pair of orthogonal magnetic field components collected by the sensor and Their discrete forms are respectively and The short-time Fourier transform is defined as:

[0029] in, For time frame indexing, Angular frequency ( For frequency, (sampling rate) Let n be a window function, t be a discrete time point, and x be a continuous time point. m This represents the time series of the m-th magnetic field component. This represents a complex exponential function (which belongs to the frequency domain basis functions in the short-time Fourier transform).

[0030] For each time frequency point The results of SFTF all have corresponding complex values: ; In the formula, This represents the phase information of the short-time Fourier transform result at the time-frequency point; Phase can be represented as: ; In the formula, Im[] represents taking The imaginary part of , Re[] means taking The real part; Considering that the STFT results of the two signals are respectively and Their phases are as follows: ; Then at the corresponding time and frequency points Above, the phase difference is defined as: ; Step 2: Time-frequency phase difference spectrum processing: The time-frequency phase difference spectrum can reflect the phase correlation of two signals to a certain extent. However, since the magnitude of the phase difference reflects the periodicity of the signal, while the power spectrum reflects the energy characteristics of the signal, the two spectral features cannot be jointly detected by simple linear superposition. Therefore, the time-frequency phase difference spectrum needs to be processed to facilitate subsequent joint detection.

[0031] This invention proposes an exponential weighted mask mapping method to perform dimensionless processing on the time-frequency phase difference spectrum. First, this invention calculates the local phase difference standard deviation of the phase difference spectrum, assuming the local window is... Then it is defined as the root mean square deviation of the phase difference in the adjacent time-frequency regions:

[0032] in, for The circular mean of the inner phase difference, The minimum periodic angular distance, This indicates the time and frequency point. The phase difference at a given time, i.e., the difference between two signals or different components of the same signal at that time. ,frequency The phase difference value below. , It represents a specific point in time, a subdivision of time t, and is used to describe a specific time location within a time-frequency region. It represents a specific frequency point, which is a subdivision of frequency f and is used to describe the specific frequency location within the time-frequency region.

[0033]

[0034] in, and The selected lower and upper bounds, This indicates the time and frequency point. The root mean square deviation of the phase difference is used to measure the dispersion of the phase difference within that time-frequency region.

[0035] Exponential weight mask mapping to the final weight mask Defined as: ; In the formula, This represents the weight adjustment coefficient, used to control the exponential weight mask. For the normalized root mean square deviation of phase difference; Weighting the time-frequency coherence, we obtain the weighted coherence spectrum as follows: .

[0036] Example 2: A flowchart of the method for detecting low-frequency electromagnetic signals of the axial poles according to the present invention is shown below. Figure 1 As shown, based on the magnetic dipole model, a set of extremely low frequency magnetic field signals Hx and Hy components were simulated, with a fundamental frequency of 2Hz, containing multiple harmonics, and Gaussian noise with a signal-to-noise ratio of 5 was added: (e.g.) Figure 2(As shown). Since the two signals originate from the same source, they should exhibit phase coherence at their harmonics, while noise does not. The time-frequency phase difference spectrum of this set of signals is calculated as follows: Figure 3 As shown: (e.g.) Figure 3 As shown). Analysis of the time-frequency phase difference spectrum of the simulated signal reveals that there is an initial phase difference of approximately 180° between 20 and 30 seconds, followed by a phase difference of 0° between 30 and 40 seconds. This is largely consistent with the waveform of the simulated signal. However, due to noise, the region with consistent phase is difficult to extract. Therefore, this invention further processes the time-frequency phase difference spectrum using the proposed method to obtain its weight mask (e.g., ...). Figure 4 As shown). Applying the mask to the coherent power spectrum of the signal yields a weighted coherent spectrum, which includes the power spectrum characteristics while preserving the stable phase difference portion between signals, eliminating incoherent noise components, and further improving signal detection accuracy (e.g.). Figure 5 (As shown).

[0037] Example 3: To further verify the effectiveness of the method in actual sea trial data, this invention selected measured extremely low frequency electromagnetic data for processing, and processed a set of noise signals and a set of extremely low frequency electromagnetic signals respectively (e.g. Figure 6 As shown). Following the process of this invention, a weighted coherence spectrum after weight masking was obtained (as shown). Figure 7 (As shown) This invention innovatively combines the harmonic characteristics of shipboard extremely low frequency (ULF) electromagnetic signals with the phase difference of the magnetic field components based on a magnetic dipole model, proposing a joint detection technique based on an improved time-frequency phase difference spectrum. This technique achieves deep fusion of phase difference and power spectrum characteristics through an exponentially weighted mask, significantly improving signal feature utilization and detection clarity. Simulation analysis and sea trial data verification demonstrate that this technique possesses superior performance in the identification and separation of ULF electromagnetic signals, and has significant engineering application value.

[0038] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0039] In the description of this invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0040] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for detecting extremely low frequency electromagnetic signals based on an improved time-frequency phase difference spectrum, characterized in that, Includes the following steps: Calculate the time-frequency phase difference spectrum between the target signal and the noise, where the target signal is an extremely low-frequency electromagnetic signal; By using an exponential weighted mask mapping method, the time-frequency phase difference spectrum is dimensionlessly processed to obtain a weighted coherence spectrum, which is used for the detection of extremely low frequency electromagnetic signals.

2. The method for detecting extremely low frequency electromagnetic signals based on an improved time-frequency phase difference spectrum according to claim 1, characterized in that: When acquiring the target signal, the target signal was simulated based on the magnetic dipole model. The fundamental frequency was 2Hz, containing multiple harmonics, and Gaussian noise with a signal-to-noise ratio of 5 was added.

3. The method for detecting extremely low frequency electromagnetic signals based on an improved time-frequency phase difference spectrum according to claim 2, characterized in that: When acquiring the time-frequency phase difference spectrum, a pair of orthogonal magnetic field component time series are collected, and after discretization, the time-frequency phase difference spectrum is obtained.

4. The method for detecting extremely low frequency electromagnetic signals based on an improved time-frequency phase difference spectrum according to claim 3, characterized in that: When acquiring the time-frequency phase difference spectrum, the signal is discretized using short-time Fourier transform.

5. The method for detecting extremely low frequency electromagnetic signals based on an improved time-frequency phase difference spectrum according to claim 4, characterized in that: When acquiring the weighted coherence spectrum, a local window is set, and the local phase difference standard deviation of the phase difference spectrum is calculated to obtain the final weighted mask of the exponential weighted mask mapping. The weighted coherence spectrum is obtained by weighting the time-frequency coherence.

6. The method for detecting extremely low frequency electromagnetic signals based on an improved time-frequency phase difference spectrum according to claim 5, characterized in that: When obtaining the final weight mask, the root mean square deviation of the phase difference in the adjacent time-frequency regions is calculated to obtain the exponential weight mask mapping to the final weight mask.

7. An ultra-low frequency electromagnetic signal detection system based on an improved time-frequency phase difference spectrum, used to implement the ultra-low frequency electromagnetic signal detection method based on an improved time-frequency phase difference spectrum as described in claim 1, characterized in that, include: The signal processing module is used to calculate the time-frequency phase difference spectrum between the target signal and the noise, wherein the target signal is an extremely low-frequency electromagnetic signal; The signal detection module is used to perform dimensionless processing on the time-frequency phase difference spectrum through an exponential weighted mask mapping method to obtain a weighted coherence spectrum, which is used to detect extremely low frequency electromagnetic signals.

8. The ultra-low frequency electromagnetic signal detection system based on the improved time-frequency phase difference spectrum according to claim 7, characterized in that: The target signal is obtained by simulation based on the magnetic dipole model, with a fundamental frequency of 2Hz, containing multiple harmonics, and Gaussian noise with a signal-to-noise ratio of 5 is added.

9. The ultra-low frequency electromagnetic signal detection system based on the improved time-frequency phase difference spectrum according to claim 8, characterized in that: The signal processing module is used to acquire a pair of orthogonal magnetic field component time series, perform discretization representation, and obtain the time-frequency phase difference spectrum, wherein the signal discretization processing is performed by short-time Fourier transform.

10. The ultra-low frequency electromagnetic signal detection system based on the improved time-frequency phase difference spectrum according to claim 9, characterized in that: The signal detection module is used to set a local window, calculate the local phase difference standard deviation of the phase difference spectrum to obtain the final weight mask of the exponential weight mask mapping, and obtain the weighted coherence spectrum by weighting the time-frequency coherence. The final weight mask of the exponential weight mask mapping is obtained by calculating the root mean square deviation of the phase difference in adjacent time-frequency regions.

Images