A method for modeling the sway noise of a magnetic detection buoy platform

Abstract

The application is a kind of magnetic detection buoy platform swing noise modeling method, belonging to the technical field of magnetic field detection; the application firstly establishes an attitude angle model, then connects the attitude angle with the magnetic field through the derivation of the conversion matrix of the earth and the platform coordinate system, establishes the buoy swing related magnetic field model of the buoy platform under different sea states, provides effective support for the magnetic detection under the offshore buoy platform, and lays a foundation for the subsequent swing noise cancellation and magnetic target detection. The application provides theoretical support for the magnetic detection of the buoy platform under various sea states, the central frequency of the buoy platform swing related magnetic field power spectrum simulated by the application under the 2nd sea state is 0.35Hz, the corresponding power gain reaches 80dB, and the measured buoy platform magnetic field power spectrum under the 2nd sea state is consistent, which proves the correctness of the buoy swing related magnetic field model; specifically, it also lays a foundation for eliminating the magnetic field noise in the subsequent buoy platform magnetic measurement experiment.

Description

Technical Field

[0001] This invention belongs to the field of magnetic field detection technology, specifically relating to a method for modeling the swaying noise of a magnetic detection buoy platform. Background Technology

[0002] Ship targets possess various physical fields, such as acoustic, magnetic, and electric fields. Among these, the target's magnetic field is the largest source of exposure after acoustic signals, and magnetic field detection has become an important technical means due to its advantages such as not being limited by hydrological conditions and being able to propagate across boundaries.

[0003] Magnetic field detection platforms include bottom-dwelling devices, buoys, or aircraft platforms. On buoys or aircraft platforms, vector magnetic sensors measure the projection of the Earth's magnetic field onto its x, y, and z components. These vector magnetic sensors can be used for target localization. Changes in the three-axis attitude (swaying) of the vector magnetic sensors on the detection platform due to sea surface fluctuations or aircraft maneuvers cause changes in the projection of the Earth's magnetic field onto its three components, resulting in sway-related magnetic field noise. This swaying noise is particularly pronounced when the buoy is operating in shallow water. Swaying noise is related to sea state and wave speed.

[0004] Existing technologies describe models for the swaying of a submerged platform. The submerged platform is fixed to a fixed point on the seabed and continuously sways; the projection of this motion onto the horizontal plane is described using a bitwist curve.

[0005] (x 2 +y 2 ) 2 -2a 2 (x 2 +y 2 )=0 (1)

[0006] There is currently little research on the magnetic field noise associated with the swaying of buoy platforms. Existing technologies only describe the swaying trajectory model of the bottom-sinking equipment and the attitude angle model of the buoy equipment, but have not yet proposed the variation of the magnetic field noise associated with the swaying of the buoy platform.

[0007] In complex marine environments, the constant movement of ocean waves causes buoy platforms to sway. The vector magnetic sensors mounted on the buoy rotate relative to the Earth's coordinate system as the platform sways, resulting in changes in the geomagnetic field measured in the three directions—a phenomenon known as sway-related magnetic field noise. This significantly interferes with the detection of weak magnetic targets. Therefore, to cancel this sway-related magnetic noise and to process the signal of the buoy magnetic detection system, it is urgently necessary to establish a buoy sway-related magnetic field model. Currently, no model has been provided for the buoy sway-related magnetic field caused by magnetic field noise and sea conditions, which is crucial for studying the detection of magnetic anomalies on swaying platforms. Summary of the Invention

[0008] The technical problem to be solved:

[0009] To overcome the shortcomings of existing technologies, this invention provides a method for modeling the sway noise of a magnetic buoy platform. This method is based on sea state parameters and a sway-related magnetic field transformation matrix to establish a buoy sway-related magnetic field model. The key points are the transformation matrix and the buoy sway-related magnetic field model. Building upon the attitude angle model, by deriving the transformation matrix between the geodetic and platform coordinate systems, the attitude angle is linked to the magnetic field, establishing a buoy sway-related magnetic field model for the buoy platform under different sea states. This provides effective support for magnetic detection on offshore buoy platforms and lays the foundation for subsequent sway noise cancellation and magnetic target detection.

[0010] The technical solution of this invention is: a method for modeling the swaying noise of a magnetic buoy platform, characterized by the following specific steps:

[0011] Step 1: Establish the buoy attitude model;

[0012]

[0013] Where θ is the buoy's attitude angle, θ = {yaw angle α, roll angle β, pitch angle γ}; θ k The included angle θ corresponds to the amplitude value of the fluctuation at the frequency; δ θ The wave factor is the fluctuation factor of the included angle θ; the wave factor describes the magnitude of the change of the included angle θ with wave fluctuation. Different attitude angles correspond to different wave factors and initial phases, where the wave factor δ θ The phase ε must be determined based on the actual sea conditions. k Let ω be a random variable uniformly distributed on [0, 2π]. Let t represent the time interval for the buoy's attitude angle to change. k Here, k represents the angular frequency of the attitude angle, and M represents the number of frequency points of the angular frequency.

[0014] Step 2: Establish a magnetic field model related to buoy swaying;

[0015]

[0016] In the formula, α, β, and γ represent the buoy attitude model in step 1, corresponding to the yaw angle model, roll angle model, and pitch angle model, respectively. R α,β,γ This is the magnetic field transformation matrix related to the swaying motion.

[0017] A further technical solution of the present invention is: in step 1, the fluctuation amplitude θ k Represented as

[0018]

[0019] In the formula, θ is the attitude angle of the buoy. kThe included angle θ corresponds to the amplitude value of the frequency fluctuation; S p (ω) represents the wave spectrum in shallow water. The frequency band covered by the wave spectrum is divided into n equal parts, and Δω is the width of each frequency band.

[0020] A further technical solution of the present invention is: the shallow water wave spectrum S p (ω) is calculated using the following formula

[0021]

[0022] In the formula, The average wave height. Let λ be the average period of the ocean waves, d be the wavelength corresponding to the average period and ocean depth, ω0 be the circumference of a circle corresponding to the dominant period of the surface wave spectrum, ω be the frequency of the ocean wave undulation, and S be the mean period of the ocean waves. p For the soundtrack of ocean waves;

[0023]

[0024] The width of each frequency band is expressed as

[0025]

[0026] In the formula, ω0 is the circumference of a circle corresponding to the dominant period of the surface wave spectrum, n is the number of equal parts of the frequency bands covered by the wave spectrum, and Δω is the width of each frequency band.

[0027] A further technical solution of the present invention is: in step 2, R α,β,γ The sway-related magnetic field transformation matrix is ​​the transformation matrix L from the buoy platform coordinate system to the geodetic coordinate system.

[0028]

[0029] A further technical solution of the present invention is: assuming the magnetic field value of a stationary target in the Earth coordinate system is (B x B y B z The measured value in the buoy platform coordinate system is (B). x ',B y ',B z The conversion relationship is as follows:

[0030]

[0031] Beneficial effects

[0032] The beneficial effects of this invention are as follows: In actual buoy-type magnetic measurement platforms, it is difficult to directly extract effective target information from the data. Sway-related magnetic field noise is the main part of the measurement noise. This invention simulates the sway-related magnetic field under the buoy measurement platform based on the sway-related magnetic field transformation matrix proposed in step 2.

[0033] Sea experiments in high sea states are extremely difficult, especially when the sea state exceeds level 5, making it challenging to conduct normal sea experiments and obtain effective buoy platform data. This invention provides theoretical support for magnetic detection of buoy platforms under various sea states. The center frequency of the power spectrum of the buoy platform sway-related magnetic field simulated by this invention under sea state 2 is 0.35Hz, with a corresponding power gain of 80dB, which is consistent with the measured power spectrum of the buoy platform magnetic field under sea state 2, demonstrating the correctness of the buoy sway-related magnetic field model. Specifically, it also lays the foundation for eliminating magnetic field noise in subsequent buoy platform magnetic measurement experiments. Attached Figure Description

[0034] Figure 1 Wave spectrum model;

[0035] Figure 2 Roll angle model;

[0036] Figure 3 Pitch angle model;

[0037] Figure 4 Yaw angle model;

[0038] Figure 5 Simulated buoy attitude angle power spectrum for sea state 2;

[0039] Figure 6 Measured power spectrum of buoy attitude angle;

[0040] Figure 7 Earth and platform coordinate systems;

[0041] Figure 8 Flowchart of buoy swaying-related magnetic field modeling;

[0042] Figure 9 Three-dimensional weight vector adaptive filter;

[0043] Figure 10 The buoy's Z-axis magnetic field adaptively cancels out.

[0044] Figure 11 Magnetic field model related to buoy swaying;

[0045] Figure 12 Magnetic field power spectrum related to buoy swaying;

[0046] Figure 13 Actual measurement of the magnetic field related to the buoy's swaying;

[0047] Figure 14 Measured power spectrum of magnetic field related to buoy swaying. Detailed Implementation

[0048] The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the invention, and should not be construed as limiting the invention.

[0049] This embodiment presents a method for modeling the swaying noise of a magnetic buoy platform, with the following specific steps:

[0050] Step 1: Buoy Attitude Model

[0051] Ocean waves in calm sea states can be considered as a stable, ergodic random process. The wave can be viewed as a superposition of infinitely many simple cosine waves with unequal amplitudes and initial phases, propagating in the x and y planes at different angles θ to the x-axis. The wave surface equation for a fixed point can be expressed as:

[0052]

[0053] a n ω represents the amplitude of a single component wave. n ε is the angular frequency of a single component wave; n Let t represent the initial phase of a single component wave, t represent the time of oscillation at this fixed point, n represent the number of frequency points of the angular frequency, and η represent the wavefront height at the fixed point.

[0054] The change in the buoy's attitude angle can be compared with the model of the change in wave height at a fixed point.

[0055]

[0056] In the formula, θ is the attitude angle of the buoy. k The included angle θ corresponds to the amplitude value of the fluctuation at the frequency; δ θ Let δ be the wave factor for the included angle θ. The wave factor describes the magnitude of the change in included angle θ with wave undulation. Different attitude angles correspond to different wave factors and initial phases, where the wave factor δ is... θ The phase ε must be determined based on the actual sea conditions. k Let ω be a random variable uniformly distributed on [0, 2π]. Let t represent the time interval for the buoy's attitude angle to change. k Let ω be the angular frequency of the attitude angle, k represent the number of frequency points of the angular frequency, and M represent the total number of angular frequency points.

[0057] Wave amplitude θ k It can be represented as

[0058]

[0059] In the formula, θ is the attitude angle of the buoy.k The included angle θ corresponds to the amplitude value of the frequency fluctuation; S p (ω) represents the wave spectrum in shallow water. The frequency band covered by the wave spectrum is divided into n equal parts, and Δω is the width of each frequency band.

[0060] The wave spectrum in the shallow water area S p (ω) is calculated using the following formula

[0061] (5)

[0062] The average wave height. Let λ be the average period of the ocean waves, d be the wavelength corresponding to the average period and ocean depth, ω0 be the circumference of a circle corresponding to the dominant period of the surface wave spectrum, ω be the frequency of the ocean wave undulation, and S be the mean period of the ocean waves. p To compose a score for the ocean waves.

[0063]

[0064] The width of each frequency band is expressed as

[0065]

[0066] In the formula, ω0 is the circumference of a circle corresponding to the dominant period of the surface wave spectrum, n is the number of equal parts of the frequency bands covered by the wave spectrum, and Δω is the width of each frequency band.

[0067] The simulation parameters are set as follows: sampling frequency fs = 200Hz, sampling time t = 100s, and water depth d = 28m. Substituting the average wave height, average period, and average wavelength from Table 1 into Equation 5 yields wave spectrum models for different sea states. Figure 1 As shown, it can be seen that as the sea state level increases, the center frequency of the wave spectrum shifts to the left, and the corresponding amplitude increases.

[0068] Substituting the parameters into Equation 3 yields the buoy attitude model, such as... Figure 2 , Figure 3 , Figure 4 As shown.

[0069] The simulated three-axis attitude angle power spectrum under sea state 2 is as follows: Figure 5 As shown, the measured attitude angle power spectrum of the buoy platform is as follows: Figure 6 As shown, the center frequencies of the two are the same (around 0.35Hz), and the power gains of the three-axis attitude angles are both around 25dB. This proves the correctness of the buoy attitude model.

[0070] Step 2: Magnetic field model related to buoy swaying

[0071] In practical applications, buoy platforms can measure three-axis attitude and magnetic field data. However, due to the constant swaying caused by ocean currents, the magnetic field data is not the actual magnetic field value in the geodetic coordinate system. Therefore, it is necessary to convert the magnetic field values ​​from the platform's coordinate system to the geodetic coordinate system, such as... Figure 7 As shown in the figure, α, β, and γ represent the yaw angle, roll angle, and pitch angle, respectively.

[0072] Establish a three-dimensional coordinate system and use a magnetic dipole model to simulate the magnetic field of the static buoy platform. Let the magnetic dipole be the origin of the coordinate system, and the spatial magnetic field at the location (x, y, z) of the buoy platform be:

[0073]

[0074] In the formula, Let μ be the straight-line distance from the buoy platform to the center of the magnetic dipole, and μ0 be the magnetic permeability in the seawater medium. x B y B z (m) represents the spatial magnetic field at the location (x, y, z) of the buoy platform. x ,m y ,m z ) represents the magnetic moment of a magnetic dipole.

[0075] The transformation matrix from the platform coordinate system to the geodetic coordinate system is:

[0076]

[0077] In the formula, L is the transformation matrix between the platform and the geodetic coordinate system, and α, β, and γ are the yaw angle, roll angle, and pitch angle of the platform.

[0078] Suppose there is a stationary target with a magnetic field value of (B) in the Earth coordinate system. x B y B z The measured value in the buoy platform coordinate system is (B). x ',B y ',B z If '), then the following transformation relationship exists:

[0079]

[0080] From equations 8 and 9, the formula for calculating the magnetic field measured under buoy platform swaying conditions can be obtained as follows:

[0081]

[0082] In the formula, R α,β,γ For the swaying related magnetic field transformation matrix, (B x B y B z(B) represents the magnetic field of a static buoy platform. x ',B y ',B z ') represents the magnetic field that causes the buoy platform to sway.

[0083]

[0084] In the formula, α, β, and γ represent the buoy attitude model in step 1, corresponding to the yaw angle model, roll angle model, and pitch angle model, respectively. R α,β,γ This is the magnetic field transformation matrix related to the swaying motion.

[0085] In summary, firstly, key parameters under different sea states, such as mean wave height and mean period, are obtained to establish a wave spectrum model. Then, based on the wave surface equation at a fixed point on the sea surface, a buoy attitude model is established. Finally, the buoy sway-related magnetic field model is obtained through the sway-related magnetic field transformation matrix, as shown below. Figure 8 As shown.

[0086] The peak-to-peak values ​​of attitude and magnetic field changes under different sea states are shown in the table below:

[0087] Table 1. Parameter values ​​for different sea states.

[0088]

[0089] The three-axis attitude data α(t), β(t), and γ(t) are used as the input signals of the adaptive filter, and the reference signal is the simulated Z-axis magnetic field H of the buoy platform. z It is the Z-axis wobble-related noise B simulated by Equation 11. z The simulated target is composed of a curve (the desired signal), and the filter output y(t) will eventually approach B infinitely. z ', Reference signal H z Subtracting it yields the useful signal e(t), which will continue to participate in adjusting the value of the three-dimensional weight vector in the next iteration. The overall adaptive filtering process and effect are as follows: Figure 9 , Figure 10 As shown.

[0090] Example:

[0091] Simulated magnetic field and power spectrum of buoy swaying under sea state 2, such as Figure 11 , Figure 12 As shown.

[0092] Measured buoy magnetic field data (sea state 2) under the buoy platform, as follows: Figure 13 , Figure 14As shown, by comparing the buoy sway-related magnetic field model and the measured buoy magnetic field data through time-domain waveforms and power spectra, it was found that the peak-to-peak values ​​of the simulated data and the measured data are basically the same in the time domain, and both are concentrated around 0.35Hz in the frequency domain, with corresponding power gains of around 80dB, proving the correctness of the buoy sway-related magnetic field model.

[0093] This embodiment describes a method for modeling the swaying noise of a magnetic buoy platform. The specific steps are as follows:

[0094] 1. For shallow sea wave spectrum modeling, shallow sea wave spectra from multiple sea areas summarized by Chinese marine scientists were adopted:

[0095]

[0096] In the formula, The average wave height. Let λ be the average period of the ocean waves, and λ be the wavelength corresponding to the average period and sea depth. The selection of parameters for different sea states is shown in the table. Water depth d = 28m, frequency ω = 2π(0:0.001:1), ω0 is pi corresponding to the dominant period of the surface wave spectrum, ω is the frequency of the ocean wave undulation, and S... p To compose a score for the ocean waves.

[0097]

[0098] Sea state name Mean wave height / m Average period / s Average wavelength / m 1 microwave 0.06 1.4 2 2 Xiaolang 0.3 2.9 8 3 Light Waves 0.6 4 18 4 Mid-wave 1.2 5.1 27 5 Big Wave 1.5 5.7 34 6 Giant Wave 2.5 7 50 7 Wild Waves 4.2 8.6 76 8 Raging Waves 8.5 11.4 135 9 Raging waves 12.2 13.1 180

[0099] 2. For buoy platform attitude angle modeling, based on the wave equation of a fixed point on the sea surface, the time-domain waveforms of the buoy's three-axis attitude angles under different sea states are generated.

[0100]

[0101] In the formula, θ is the attitude angle of the buoy. k Let θ be the amplitude value of the fluctuation corresponding to the frequency, and δ be the angle between them. θ Let ω be the fluctuation factor of the included angle θ, t represent the time of change of the buoy attitude angle, and ω be the oscillation factor. k Let be the angular frequency of the attitude angle, k represent the number of frequency points, the total number of angular frequency points M = 1001, and the sampling frequency fs = 200Hz. The fluctuation factor δ... θ The phase ε must be determined based on the actual sea conditions. k Let be a random variable uniformly distributed on [0, 2π].

[0102]

[0103] In the formula, θ is the attitude angle of the buoy. k The included angle θ corresponds to the amplitude value of the frequency fluctuation; S p(ω) represents the wave spectrum in shallow water. The frequency band covered by the wave spectrum is divided into M equal parts, and Δω is the width of each frequency band.

[0104] The width of each frequency band is expressed as

[0105]

[0106] In the formula, ω0 is the π corresponding to the dominant period of the surface wave spectrum, M is the number of equal parts of the frequency band covered by the wave spectrum, and Δω is the width of each frequency band.

[0107] 3. For the calculation formula of the magnetic field related to buoy swaying, a transformation matrix R for the magnetic field related to swaying is proposed based on the transformation matrix L of the earth-platform coordinate system.

[0108]

[0109]

[0110] In the formula, α, β, and γ are the yaw angle, roll angle, and pitch angle, respectively, and their corresponding wave factors are δ. α =25, δ β =15, δ γ =11.

[0111] 4. For the buoy swaying-related magnetic field model, based on the spatial magnetic field calculation formula of a certain point in the magnetic dipole model and the proposed swaying-related magnetic field transformation matrix, the variation of the buoy swaying-related magnetic field in the time domain and frequency domain was simulated.

[0112]

[0113] In the formula (B) x B y B z The magnetic field at the location (x, y, z) of the buoy platform is the magnetic field of the static buoy platform, and the permeability of the seawater medium is μ0 = 4π × 10⁻⁶. -7 H / m, the straight-line distance between the buoy platform and the center of the magnetic dipole. The magnetic moment of the magnetic dipole is m x =m y =m z = (2×10 6 ,0,0)A·m 2 .

[0114]

[0115] In the formula, R α,β,γ This is the magnetic field transformation matrix related to the swaying motion. (B) x B y B z( ) represents the magnetic field of a static buoy platform.

[0116] (B x ',B y ',B z ') represents the magnetic field that causes the buoy platform to sway.

[0117] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the present invention.

Claims

1. A method for modeling the swaying noise of a magnetic buoy platform, characterized in that... The specific steps are as follows: Step 1: Establish the buoy attitude model; in, Let be the attitude angle of the buoy. ={Yaw angle Roll angle Pitch angle }; Angle The amplitude value of the fluctuation corresponding to the frequency; Angle Volatility factor; volatility factor describes the angle As the magnitude of the wave fluctuation changes, different attitude angles correspond to different wave factors and initial phases, where the wave factor... The phase must be determined based on the actual sea conditions. for A random variable that is uniformly distributed on the upper bound. This indicates the time it takes for the buoy's attitude angle to change. Let be the angular frequency of the attitude angle. The number of frequency points representing angular frequency. The total number of points representing the angular frequency; Fluctuation Amplitude Represented as: In the formula, Let be the attitude angle of the buoy. Angle The amplitude value of the fluctuation corresponding to the frequency; For the shallow water wave spectrum, the frequency bands covered by the wave spectrum are... n equal parts, The width of each frequency band; The wave spectrum in the shallow water area Calculated using the following formula In the formula, The average wave height. The average period of the ocean waves, The wavelength corresponding to the average period and sea depth, Because of the water depth, Pi is the coefficient of π corresponding to the dominant period of the surface spectrum. ω The frequency of ocean wave undulations S p For the soundtrack of ocean waves; The width of each frequency band is expressed as In the formula, Pi is the coefficient of π corresponding to the dominant period of the surface spectrum. n The number of equal parts of the frequency band covered by the wave spectrum. The width of each frequency band; Step 2: Establish a magnetic field model related to buoy swaying; In the formula, , , The buoy attitude model in step 1 corresponds sequentially to the yaw angle model, roll angle model, and pitch angle model. R α,β,γ This is the magnetic field transformation matrix related to the swaying motion.

2. The method for modeling the swaying noise of a magnetic buoy platform according to claim 1, characterized in that: In step 2, R α,β,γ The sway-related magnetic field transformation matrix is ​​the transformation matrix L from the buoy platform coordinate system to the geodetic coordinate system.

3. The method for modeling the swaying noise of a magnetic buoy platform according to claim 2, characterized in that: Assume the magnetic field value of a stationary target in the Earth coordinate system is The measured value in the buoy platform coordinate system is The conversion relationship is as follows: 。

Images