An Electromagnetic Field Modeling and Separation Method for Monitoring Ocean Wave Characteristics

Abstract

This invention belongs to the field of ocean wave characteristic monitoring technology, specifically relating to an electromagnetic field modeling and separation method for ocean wave characteristic monitoring. The method includes: performing Proni decomposition on a noise-interferenced ocean wave-induced electromagnetic field signal ( ) to obtain multiple Proni components, and calculating their amplitude, frequency, and attenuation factor; filtering the Proni components according to preset constraints to obtain filtered Proni components; removing repetition frequencies from the filtered Proni components to obtain effective signal components; establishing a sinusoidal signal and calculating its cross-correlation sequence with ( ), finding the peak position in the sequence to obtain the phase of the effective signal components; and constructing an ocean wave-induced electromagnetic model based on the frequency, amplitude, and phase of the effective signal components to obtain a clean ocean wave-induced electromagnetic field signal ( ). This invention can better separate the ocean wave-induced electromagnetic field from noise, solving the problem of difficulty in analyzing ocean wave dynamics characteristics due to noise interference.

Description

Technical Field

[0001] This invention belongs to the field of ocean wave characteristic monitoring technology, specifically relating to an electromagnetic field modeling and separation method for ocean wave characteristic monitoring. Background Technology

[0002] Highly conductive seawater generates induced electromagnetic signals as it moves, cutting through the Earth's magnetic field. This is especially true in shallow waters where wave motion is frequent and intense, with induced electromagnetic field amplitudes reaching approximately 100 µV / m and 20 nT. This electromagnetic field is closely related to wave dynamics, exhibiting a significant positive correlation between its intensity and wave height, and its peak frequency is highly sensitive to changes in wave motion cycles. With the continuous development of marine exploration technology, wave-induced electromagnetic fields are gradually becoming an emerging method for monitoring wave height, motion cycles, and other dynamic characteristics. Compared to traditional methods such as radar and remote sensing, it offers advantages such as a wider detection range and immunity to adverse weather conditions.

[0003] However, in complex marine environments, electromagnetic detection signals are highly susceptible to noise interference, including motion noise, environmental noise, etc. In particular, instrument swaying in severe sea conditions, human interference from offshore drilling platforms or near the shore, and magnetotelluric interference can completely submerge wave-induced electromagnetic signals in noise, making it difficult to analyze the true wave dynamics.

[0004] Patent CN118444398A discloses a method and system for reconstructing marine electromagnetic time series data. It utilizes earthquake first arrival picking methods, such as the long-short time window method, to record noise locations and remove identified noise by replacing it with identical values. For each noisy time series, the noise length K is defined as a sparse value in the compressed sensing algorithm, and a measurement matrix, a sparse matrix, and a sensing matrix are constructed. The reconstructed time series is obtained through a compressed sensing matching and tracking algorithm. Only the data from the reconstructed noise locations is used to replace the corresponding noise portion in the original time series, while other parts of the original time series remain unchanged. The program code automatically moves to the next noise location, constructs a time series x, a measurement matrix Φ, a sparse matrix ψ, a sensing matrix A, and a reconstructed time series θ to replace the noise data, until all identified noise is reconstructed and replaced, and outputs the reconstructed electromagnetic field time series file. However, this method treats wave-induced electromagnetic signals and environmental noise such as impulse noise as interference, separating them from marine magnetotelluric signals, thus failing to achieve accurate extraction of wave-induced electromagnetic signals.

[0005] Patent CN119573682A discloses a method for analyzing ocean wave characteristics based on electromagnetic field observation data. It uses dominant frequency analysis and bandpass filtering techniques to preprocess electromagnetic field data and obtain time domain data of ocean wave induced magnetic field. However, this method only focuses on background noise outside the passband and cannot suppress electromagnetic interference that overlaps with the effective signal spectrum. Summary of the Invention

[0006] To address the shortcomings of related technologies, this invention provides an electromagnetic field modeling and separation method for monitoring ocean wave characteristics, aiming to solve the problem of difficulty in analyzing ocean wave dynamic characteristics due to noise interference.

[0007] This invention provides an electromagnetic field modeling and separation method for monitoring ocean wave characteristics, comprising the following steps:

[0008] S1, Electromagnetic field signal induced by ocean waves affected by noise interference. Proni decomposition was performed to obtain multiple proni components. ;in, It is a sequence of sampling points. , The sequence length; , Let the order of the Proni decomposition be [the order of the decomposition].

[0009] S2, Calculate the Proni component amplitude ,frequency and attenuation factor ;

[0010] S3. Apply the preset constraints to all Proni components. The proni components were obtained by filtering. , … denoted as its frequency , … ;in, The number of proni components after screening;

[0011] S4. Repeat frequency elimination is performed on the filtered Proni components to identify the effective signal components. , … denoted as its frequency , … Its amplitude is denoted as , … ;in, The number of valid signal components after identification;

[0012] S5, Establish A sinusoidal signal , expressed as equation (1), where, ; Calculate the sinusoidal signal Electromagnetic field signals induced by ocean waves and noise interference The cross-correlation sequence is used to find the peak positions in the cross-correlation sequence and obtain the phase of the effective signal component. ;

[0013] (1);

[0014] S6. Based on the frequency of the effective signal components ,amplitude and phase A wave-induced electromagnetic model is constructed, expressed as Equation (2), thereby obtaining a pure wave-induced electromagnetic field signal. This achieves the separation of wave-induced electromagnetic fields from noise;

[0015] (2).

[0016] In some embodiments, in step S2, the proni component amplitude ,frequency and attenuation factor The calculation includes the following steps:

[0017] Electromagnetic field signals induced by ocean waves that are affected by noise It is approximately a linear combination of complex exponential functions, and its mathematical expression is given by equation (3), where, , , For the initial phase, The sampling period is Represents the imaginary part;

[0018] (3);

[0019] The linear combination in equation (3) is represented by a matrix. This matrix is ​​further represented by equation (4);

[0020] (4);

[0021] Calculate the Proni component according to equations (5), (6), and (7) respectively. amplitude Attenuation factor ,frequency ;

[0022] (5);

[0023] (6);

[0024] (7).

[0025] In some embodiments, the preset constraint in step S3 includes an attenuation factor threshold. and effective frequency band range ,in, This is the lower limit threshold of the frequency band. This is the upper limit threshold of the frequency band;

[0026] like and Then As the filtered Proni component;

[0027] like and / or Then As noise components that are filtered out.

[0028] In some embodiments, the attenuation factor threshold The calculation is performed according to equation (8), where, It is a constant. The range of values ​​is ;

[0029] (8).

[0030] In some embodiments, the lower bandwidth threshold The upper limit threshold of the frequency band is calculated according to equation (9). The calculation is performed according to equation (10), where, and All are constants. and The range of values ​​is , This represents the lower limit of the high-energy frequency band. This represents the upper limit of the high-energy frequency band.

[0031] (9);

[0032] (10).

[0033] In some embodiments, the lower limit of the high-energy frequency band and the upper limit of high-energy frequency bands The acquisition includes the following steps:

[0034] Suppose the electromagnetic field signal induced by ocean waves is subject to noise interference. The spectral sequence is The modulus maxima sequence of this spectral sequence is , For frequency sampling points;

[0035] Set the lower limit of the high-energy frequency band The initial value is Frequency step is , and All are constants. and The range of values ​​is Let there be a sequence of positive integers. ;

[0036] Starting from 1, the value is incremented by 1 each time until it reaches 1. Established, according to the current situation Value, determining the lower limit of the high-energy frequency band. ;

[0037] Then, Continue adding 1 each time until it makes Established, according to the current situation Value, determining the upper limit of the high-energy frequency band. .

[0038] In some embodiments, step S4, the repetition frequency elimination of the screened proni components includes the following steps:

[0039] First of all, The selected proni components are sorted in ascending order of frequency, and their frequencies are denoted sequentially as follows: , … ;

[0040] Then, according to equation (11), a difference operation is performed on adjacent frequencies to obtain the frequency interval. ,in, ;

[0041] (11);

[0042] When frequency interval Less than the preset frequency difference At that time, The Proni component, as the effective signal component after identification, will be... The Proni component is treated as a noise component to be removed.

[0043] When frequency interval Not less than the preset frequency difference At that time, The Proni component to which it belongs, All of the Proni components are used as valid signal components after identification.

[0044] In some embodiments, in step S1, the Proni decomposition order is... ,and It is a positive integer; in step S3, the number of filtered Proni components It is a positive integer, and In step S4, the number of valid signal components after identification is... It is a positive integer, and .

[0045] Based on the above technical solution, the electromagnetic field modeling and separation method for monitoring ocean wave characteristics in this embodiment of the invention obtains the effective signal components of the ocean wave-induced electromagnetic field by performing Proni decomposition on the noise-interferenced ocean wave-induced electromagnetic field signal, and by subjecting the decomposed Proni components to multiple constraints of attenuation factor and frequency, and elimination of repetition frequency. Then, based on the frequency, amplitude and phase of each effective signal component, an ocean wave-induced electromagnetic field model is constructed, thereby realizing the separation of the ocean wave-induced electromagnetic field from noise, obtaining a more accurate and pure ocean wave-induced electromagnetic field signal, greatly improving the authenticity, accuracy and reliability of subsequent analysis and estimation of ocean wave dynamic characteristic parameters, and solving the problem that ocean wave dynamic characteristics are difficult to analyze due to noise interference in the prior art. Attached Figure Description

[0046] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0047] Figure 1 This is a flowchart of the electromagnetic field modeling and separation method for monitoring ocean wave characteristics according to the present invention.

[0048] Figure 2 The time-domain plots show the electromagnetic field signal induced by ocean waves under noise interference (i.e., the original signal) and the ideal signal.

[0049] Figure 3 Time-domain plots of an ideal signal and a pure wave-induced electromagnetic field signal obtained using this invention;

[0050] Figure 4 The time-domain plots show the ideal signal and the pure wave-induced electromagnetic field signal obtained using the wavelet thresholding method commonly used in existing technologies. Detailed Implementation

[0051] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0052] The terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature.

[0053] refer to Figure 1 As shown, this invention provides an electromagnetic field modeling and separation method for monitoring ocean wave characteristics, which is used to process ocean wave-induced electromagnetic field signals that are affected by noise interference. It is mainly applied to the modeling and separation of ocean wave-induced electromagnetic fields. The method includes the following steps S1 to S6.

[0054] Step S1: Input the electromagnetic field signal induced by ocean waves that is subject to noise interference. ,in, It is a sequence of sampling points. , The sequence length; further explanation: wave-induced electromagnetic field signals affected by noise. This can be understood as electromagnetic field signals induced by pure ocean waves. and noise interference Composition, that is Pure ocean wave-induced electromagnetic field signal It typically exhibits periodic oscillations in the time domain and is an extremely low-frequency narrowband signal in the frequency domain. The peak frequency decreases as the wave motion period increases, with effective frequencies below 1 Hz. The amplitude is positively correlated with wave height. (Noise interference) Electromagnetic noise includes motion noise and environmental noise. Motion noise is caused by the heave of the detection instrument as it moves with the seawater; this noise frequency is typically below 0.1 Hz and causes signal baseline drift in the time domain. Environmental noise includes ocean magnetotelluric signals and random environmental noise, which are non-stationary signals with a wide spectral range, reaching up to 10 Hz. -3 Up to 10 3 Hz.

[0055] Electromagnetic field signals induced by ocean waves affected by noise Proni decomposition was performed to obtain multiple proni components. ;in, , Let be the order of the Proni decomposition, that is, multiple Proni components can be expressed as: , , , Furthermore, the order of Proni decomposition ,and It is a positive integer.

[0056] Step S2: Calculate each Proni component amplitude ,frequency and attenuation factor .

[0057] Further explanation of the proni component amplitude ,frequency and attenuation factor The calculation includes the following steps:

[0058] Electromagnetic field signals induced by ocean waves that are affected by noise It is approximately a linear combination of a certain number of complex exponential functions, and its mathematical expression is given by equation (3), where, , , For the initial phase, The sampling period is Represents the imaginary part;

[0059] (3);

[0060] The linear combination in equation (3) is represented by a matrix. This matrix is ​​further represented by equation (4);

[0061] (4);

[0062] Solution of the matrix It can be used to calculate the amplitude of the Proni component, that is, to calculate the Proni component according to equation (5). amplitude And calculate the Proni component according to equation (6). attenuation factor The Proni component is calculated according to equation (7). frequency ;

[0063] (5);

[0064] (6);

[0065] (7).

[0066] Step S3: Apply preset constraints to all Proni components. The proni components were obtained by filtering. , … denoted as its frequency , … ;in, The number of proni components after screening; further, It is a positive integer, and .

[0067] To further explain, the preset constraints include the attenuation factor threshold. and effective frequency band range ,in, This is the lower limit threshold of the frequency band. This is the upper limit threshold of the frequency band; if and Then As the filtered Proni component; if and / or Then As noise components to be filtered out. That is, it is determined whether the frequency of the Proni component is within the effective frequency band and whether the absolute value of the attenuation factor is less than the threshold requirement. Proni components whose frequency is within the effective frequency band and whose absolute value of the attenuation factor is less than the threshold requirement are selected as Proni components after filtering, while Proni components whose frequency is outside the effective frequency band and / or whose absolute value of the attenuation factor exceeds the threshold requirement are selected as noise components to be filtered out.

[0068] Furthermore, the attenuation factor threshold The calculation is performed according to equation (8), where, It is a constant. The range of values ​​is ;

[0069] (8).

[0070] Furthermore, the lower limit threshold of the frequency band The upper limit threshold of the frequency band is calculated according to equation (9). The calculation is performed according to equation (10), where, and All are constants. and The range of values ​​is , This represents the lower limit of the high-energy frequency band. This represents the upper limit of the high-energy frequency band.

[0071] (9);

[0072] (10).

[0073] To further explain, the lower limit of the high-energy frequency band and the upper limit of high-energy frequency bands The acquisition includes the following steps:

[0074] Suppose the electromagnetic field signal induced by ocean waves is subject to noise interference. The spectral sequence is The modulus maxima sequence of this spectral sequence is , For frequency sampling points;

[0075] Set the lower limit of the high-energy frequency band The initial value is Frequency step is , and All are constants. and The range of values ​​is Let there be a sequence of positive integers. ;

[0076] Starting from 1, the value is incremented by 1 each time until it reaches 1. Established, according to the current situation Value, determining the lower limit of the high-energy frequency band. ;

[0077] Determine the lower limit of the high-energy frequency band back, Continue adding 1 each time until it makes Established, according to the current situation Value, determining the upper limit of the high-energy frequency band. .

[0078] Step S4: The filtered proni components ( , … Repeat frequency elimination is performed to identify valid signal components. , … denoted as its frequency , … Its amplitude is denoted as , … ;in, The number of valid signal components after identification; valid signal components can be uniformly represented as Its frequency is expressed as Its amplitude is expressed as ,in, Furthermore, It is a positive integer, and .

[0079] To further explain, the repetition frequency removal of the screened proni components includes the following steps:

[0080] First of all, The selected proni components are sorted in ascending order of frequency, and their frequencies are denoted sequentially as follows: , … ;

[0081] Then, according to equation (11), a difference operation is performed on adjacent frequencies to obtain the frequency interval. ,in, ;

[0082] (11);

[0083] When frequency interval Less than the preset frequency difference At that time, The Proni component, as the effective signal component after identification, will be... The Proni component is treated as a noise component to be removed.

[0084] When frequency interval Not less than the preset frequency difference At that time, The Proni component to which it belongs, All of the Proni components are used as valid signal components after identification;

[0085] For example, the frequency intervals can be expressed as follows: , , , Preset frequency difference When the value is 0.0001Hz, if Hz, then , with lower frequency The Proni component, being treated as a noise component to be removed, includes those with higher frequencies. The Proni component is used as the effective signal component after identification.

[0086] Step S5, Establish A sinusoidal signal , expressed as equation (1), where, ; Calculate the sinusoidal signal Electromagnetic field signals induced by ocean waves and noise interference The cross-correlation sequence is used to find the peak positions in the cross-correlation sequence and obtain the phase of the effective signal component. The calculation of cross-correlation sequences is well known to those skilled in the art and will not be elaborated here.

[0087] (1).

[0088] Step S6: Based on the frequency of the effective signal component ,amplitude and phase A wave-induced electromagnetic model is constructed, expressed as Equation (2), thereby obtaining a pure wave-induced electromagnetic field signal. This allows for the separation of wave-induced electromagnetic fields from noise.

[0089] (2).

[0090] refer to Figures 2-4 As shown, the electromagnetic field modeling and separation method for monitoring ocean wave characteristics provided by this invention is verified through simulation experiments, and the invention is compared with the commonly used wavelet thresholding method in the prior art. The simulation experiments were conducted in the MATLAB R2024a programming environment, and the specific details are as follows:

[0091] 1) Constructing a wave-induced electromagnetic field signal affected by noise interference This is used as the original signal; This includes simulated, pure electromagnetic field signals induced by ocean waves. and random white noise The simulated pure electromagnetic field signal of ocean waves will be used. As an ideal signal, random white noise As noise interference signals to be separated.

[0092] To further explain, It can be considered as a superposition of multiple sinusoidal signals, with a frequency band of 0.1–0.3 Hz and an amplitude of less than 15 nT. In the time domain, it exhibits an approximately periodic signal oscillation pattern, and its waveform is as follows: Figure 2 As shown by the green dashed line; It can be broadband random white noise, with low-amplitude frequency components present across the entire frequency band; The waveform is as follows Figure 2 As shown by the solid black line, although an approximate periodic oscillation trend can be observed in the time domain after being affected by noise interference, the local random fluctuation characteristics are obvious.

[0093] 2) Using steps S1 to S6 of this invention, a pure wave-induced electromagnetic field signal is obtained. Specifically, in step S1, the Proni decomposition order is... The value is 500; in step S3, the constant , and The values ​​are 0.9, 1.1, and -3 respectively; in step S4, the preset frequency difference... The value is 0.0001Hz. The pure ocean wave induced electromagnetic field signal obtained using this invention... Its waveform is as follows Figure 3 As shown by the red dashed line, it can be observed that the pure wave-induced electromagnetic field signal obtained by this invention exhibits an approximately periodic oscillation pattern, which basically coincides with the ideal signal.

[0094] The pure wave-induced electromagnetic field signal obtained using the wavelet thresholding method commonly used in existing technologies... Its waveform is as follows Figure 4 As shown by the purple dashed line, it can be observed that the pure wave-induced electromagnetic field signal obtained by existing technology still exhibits random fluctuation characteristics and has a low degree of fitting with the ideal signal.

[0095] As can be seen from the above simulation experiments, compared with the existing technology, the present invention can obtain a more accurate and pure wave-induced electromagnetic field signal, better separate the wave-induced electromagnetic field from noise, and thus significantly improve the authenticity, accuracy and reliability of subsequent wave dynamics feature analysis.

[0096] Through the description of several embodiments of the electromagnetic field modeling and separation method for monitoring ocean wave characteristics according to the present invention, it can be seen that the present invention has at least one or more of the following advantages:

[0097] 1) This invention decomposes the noise-affected wave-induced electromagnetic field signal into Proni, and then applies multiple constraints on the attenuation factor and frequency of the decomposed Proni components, as well as the elimination of repetition frequencies, to obtain the effective signal components of the wave-induced electromagnetic field. Based on the frequency, amplitude, and phase of each effective signal component, a wave-induced electromagnetic field model is constructed, thereby achieving the separation of the wave-induced electromagnetic field from noise and obtaining a more accurate and pure wave-induced electromagnetic field signal. This greatly improves the authenticity, accuracy, and reliability of the subsequent analysis and estimation of wave dynamic characteristic parameters.

[0098] 2) By employing multiple constraints of attenuation factor and frequency, this invention can accurately identify and suppress impulse noise, frequency band aliasing noise, etc., especially noise that is superimposed on the effective signal throughout the entire time period and is severely aliased in the characteristic frequency band of ocean waves. Therefore, it has significant application value for the extraction of ocean wave induced electromagnetic field and can effectively solve the problem that ocean wave dynamic characteristics are difficult to analyze due to noise interference such as motion noise and environmental noise.

[0099] Finally, it should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0100] The above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them; although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications can still be made to the specific implementation of the present invention or equivalent substitutions can be made to some technical features without departing from the spirit of the technical solutions of the present invention, and all such modifications and substitutions should be covered within the scope of the technical solutions claimed in the present invention.

Claims

1. A method for electromagnetic field modeling and separation for sea wave feature monitoring, characterized in that, The method comprises the following steps: S1, sea wave induced electromagnetic field signal disturbed by noise performing prony decomposition to obtain a plurality of prony components ; wherein, is a sequence of sampling points, , is a sequence length; , is a prony decomposition order; S2, compute prony components amplitude , frequency and decay factor ; S3. Apply the preset constraints to all Proni components. The proni components were obtained by filtering. , … denoted as its frequency , … ;in, The number of proni components after screening; S4, repeat frequency elimination is performed on the screened prolate components to identify valid signal components 、 、…、 , and the frequency of the valid signal components is recorded as 、 、…、 , and the amplitude of the valid signal components is recorded as 、 、…、 ; wherein is the number of identified valid signal components S5, establish a sinusoidal signal , represented as equation (1), wherein, ; calculate the cross-correlation sequence of the sinusoidal signal and the noise-affected sea-induced electromagnetic field signal , find the peak position in the cross-correlation sequence, and obtain the phase of the effective signal component ; (1)； S6、According to the frequency of the effective signal component , amplitude and phase Construct a sea wave induced electromagnetic model, expressed as formula (2), so as to obtain a pure sea wave induced electromagnetic field signal , realize the separation of sea wave induced electromagnetic field and noise; (2)。 2. The electromagnetic field modeling and separation method for sea wave feature monitoring according to claim 1, characterized in that, In step S2, the Prony component The calculation of the amplitude , frequency and damping factor of the Prony component comprises the following steps, Noise disturbed sea wave induced electromagnetic field signals is approximately a linear combination of complex exponentials, mathematically expressed as equation (3), where, , , is the initial phase, is the sampling period, represents the imaginary part; (3)； The linear combination in formula (3) is represented by a matrix which is further represented by formula (4); (4)； The Prony components are calculated according to the formula (5), formula (6), formula (7), respectively amplitude of , attenuation factor , frequency ; (5)； (6)； (7)。 3. The electromagnetic field modeling and separation method for sea wave feature monitoring according to claim 1, characterized in that, In step S3, the preset constraint condition comprises a decay factor threshold and an effective frequency band range wherein, is a lower frequency band threshold, is an upper frequency band threshold; If and then is the prony component after screening; If and / or then are filtered out as noise components.

4. The electromagnetic field modeling and separation method for sea wave feature monitoring according to claim 3, characterized in that, the attenuation factor threshold The calculation is made according to equation (8) where, is a constant, ranges from 0 to 1, ; (8)。 5. The electromagnetic field modeling and separation method for sea wave feature monitoring according to claim 3, characterized in that, the lower band threshold the upper band threshold is calculated according to equation (9) wherein, and are constants, and have a value in the range , is the lower limit of the high energy band, is the upper limit of the high energy band; (9)； (10)。 6. The electromagnetic field modeling and separation method for sea wave feature monitoring according to claim 5, characterized in that, the lower limit of the high energy band and the upper limit of the high energy band The acquisition of the lower limit of the high energy band comprises the following steps: Sea wave induced electromagnetic field signal disturbed by noise a frequency sequence of a sequence of modulus maxima of the frequency sequence , is a frequency sampling point; Let the lower limit of the high-energy frequency band be , , , , , , , , ; from 1 and successively adding 1 until is established, according to the value of at this time, the lower limit of the high-energy frequency band is determined ; Then, Continuing incrementing by one until is established, according to the value of at this time, the upper limit of the high-energy frequency band is determined.

7. The electromagnetic field modeling and separation method for sea wave feature monitoring according to claim 1, characterized in that, In step S4, the repeated frequency elimination on the screened Prooni component comprises the following steps: In step S4, the repeated frequency elimination on the screened Prooni component comprises the following steps: First, the filtered prony components are sorted by their frequencies in ascending order, and their frequencies are sequentially recorded as , , , ; Then, the adjacent frequencies are differenced according to formula (11) to obtain the frequency interval wherein ; (11)； When the frequency interval is smaller than a preset frequency difference , the Prooni component belonging thereto is taken as the identified effective signal component, and the Prooni component belonging thereto is taken as the eliminated noise component. When the frequency interval is not less than a preset frequency difference , the Prooni component belonging to the same group, Prooni component belonging to the same group is also an effective signal component after identification.

8. The electromagnetic field modeling and separation method for sea wave feature monitoring according to claim 1, characterized in that, In step S1, the order of the Proth decomposition , and is a positive integer; in step S3, the number of the Proth components after the screening is a positive integer, and ; In step S4, the number of recognized valid signal components is a positive integer, and .

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