Sound wave expelling method and system

Abstract

The invention provides a sound wave expelling method and system. The method relates to acquisition of millimeter wave radar point cloud data, dynamic compensation of AIS message analysis and ship threat level parameters. A ship motion model is constructed according to the data and parameters, a threat area is predicted, and the three-dimensional coverage range of sound waves is determined by combining the length-width ratio of the ship. Then, transducer array beam parameters are calculated, and a sound wave expelling waveform instruction is generated. Through millimeter wave radar, AIS message analysis and algorithm processing, the sound wave coverage range and instruction are accurately determined, the expelling precision and efficiency are remarkably improved, and the safety and smoothness of marine traffic are ensured.

Description

Technical Field

[0001] The present application relates to the field of waterway expulsion, and in particular to a sonic expulsion method and system. Background Art

[0002] In the field of maritime traffic management and security monitoring, the timely identification and effective removal of potentially threatening vessels are crucial for ensuring smooth navigation and maritime safety. Traditional removal methods often rely on visual recognition or simple radar detection, which suffer from issues such as insufficient accuracy, slow response, and susceptibility to environmental interference. With technological advancements, acoustic removal has gained increasing attention as a non-contact, safe removal method. However, most existing acoustic removal systems lack the ability to accurately predict ship motion and adapt to dynamic environments, resulting in inaccurate acoustic coverage, wasted energy, and poor removal effectiveness. Summary of the Invention

[0003] The purpose of this application is to overcome the above-mentioned defects in the prior art and provide a sound wave expulsion method and system.

[0004] The present application provides a method for acoustic wave expulsion, comprising: Obtain millimeter-wave radar point cloud data, dynamic compensation parameters obtained by AIS message analysis, and ship threat level parameters; Constructing a ship motion model based on the dynamic compensation parameters and millimeter wave radar point cloud data; generating threat area prediction data based on the ship motion model and ship characteristic parameters in the AIS message; determining a three-dimensional coverage range of the acoustic wave action based on the threat area prediction data and the ship aspect ratio parameter; Calculating transducer array beamforming parameters based on the three-dimensional coverage and a preset safety threshold; generating an acoustic wave repelling waveform instruction according to the array beamforming parameter and the ship threat level parameter; The target is driven away by sonic waves according to the sonic wave driving away waveform instruction.

[0005] Optionally, the construction of the ship motion model includes: Adopting a hybrid architecture of Kalman filter framework and particle filter correction module; When it is detected that the ship's steering angular velocity exceeds a preset threshold, the particle filter correction is triggered to generate dynamic prediction parameters including the motion state covariance matrix; The particle filter correction module adopts the Monte Carlo sampling method to generate motion state disturbance parameters through the ship's historical trajectory data.

[0006] Optionally, the method for determining the three-dimensional coverage range includes: The acoustic wave action domain is calculated based on a hyperbolic geometry model, where the long axis is aligned with the tangent direction of the ship's trajectory. The short axis length is dynamically adjusted according to the ship's aspect ratio parameters and is positively correlated with the preset safety factor; The height axis parameters are integrated with real-time ocean environment data and generated through weighted calculation of wave height and draft depth.

[0007] Optionally, the dynamic compensation parameter analysis method includes: Extract the draft compensation bit and heading differential correction bit from the AIS message extension field; The compensation bit data length is set to be a specific ratio smaller than the message check bit length; Differential coding technology is used to compress, store and transmit the compensation parameters.

[0008] Optionally, the method for generating transducer array beamforming parameters includes: Adopting a multi-layer annular array topology, the spacing between adjacent transducer units is dynamically calculated based on the acoustic wavelength and a specific proportional coefficient; The phase difference gradient is distributed along the normal direction of the target ship's trajectory; When multiple target threats are detected, the multi-beam synchronization control module is activated to generate spatially separated independent sound field focus areas.

[0009] The present application also provides a sonic drive system, comprising: Acquisition module, which obtains millimeter-wave radar point cloud data, dynamic compensation parameters obtained by AIS message analysis, and ship threat level parameters; A construction module, constructing a ship motion model based on the dynamic compensation parameters and millimeter wave radar point cloud data; A prediction module generates threat area prediction data based on the ship motion model and ship characteristic parameters in the AIS message; An action module determines a three-dimensional coverage range of the acoustic wave action based on the threat area prediction data and the ship aspect ratio parameter; a parameter module, calculating transducer array beamforming parameters based on the three-dimensional coverage and a preset safety threshold; an instruction module, generating an acoustic wave repelling waveform instruction according to the array beamforming parameter and the ship threat level parameter; An execution module performs acoustic wave driving away of a target according to the acoustic wave driving away waveform instruction.

[0010] Optionally, the building module builds a ship motion model, including: Adopting a hybrid architecture of Kalman filter framework and particle filter correction module; When it is detected that the ship's steering angular velocity exceeds a preset threshold, the particle filter correction is triggered to generate dynamic prediction parameters including the motion state covariance matrix; The particle filter correction module adopts the Monte Carlo sampling method to generate motion state disturbance parameters through the ship's historical trajectory data.

[0011] Optionally, the action module generates threat area prediction data, including: The acoustic wave action domain is calculated based on a hyperbolic geometry model, where the long axis is aligned with the tangent direction of the ship's trajectory. The short axis length is dynamically adjusted according to the ship's aspect ratio parameters and is positively correlated with the preset safety factor; The height axis parameters are integrated with real-time ocean environment data and generated through weighted calculation of wave height and draft depth.

[0012] Optionally, the acquiring module analyzes the dynamic compensation parameters, including: Extract the draft compensation bit and heading differential correction bit from the AIS message extension field; The compensation bit data length is set to be a specific ratio smaller than the message check bit length; Differential coding technology is used to compress, store and transmit the compensation parameters.

[0013] Optionally, the parameter module forms parameters including: Adopting a multi-layer annular array topology, the spacing between adjacent transducer units is dynamically calculated based on the acoustic wavelength and a specific proportional coefficient; The phase difference gradient is distributed along the normal direction of the target ship's trajectory; When multiple target threats are detected, the multi-beam synchronization control module is activated to generate spatially separated independent sound field focus areas.

[0014] The beneficial effects of this application are: Invention point: 1. Combining the high-precision point cloud data of millimeter-wave radar and the dynamic compensation parameters provided by AIS to more accurately build the ship motion model 2. By detecting trajectory error data and generating closed-loop correction parameters based on the error data and sound field control command parameters, real-time feedback and adjustment of the ship's motion status are achieved. 3. Ellipsoid modeling The present application provides an acoustic repelling method, comprising: obtaining millimeter-wave radar point cloud data, dynamic compensation parameters obtained from AIS message parsing, and ship threat level parameters; constructing a ship motion model based on the dynamic compensation parameters and millimeter-wave radar point cloud data; generating threat area prediction data based on the ship motion model and ship characteristic parameters in the AIS message; determining the three-dimensional coverage range of the acoustic wave action based on the threat area prediction data and the ship aspect ratio parameter; calculating transducer array beamforming parameters based on the three-dimensional coverage range and a preset safety threshold; generating acoustic repelling waveform instructions based on the array beamforming parameters and the ship threat level parameter; and performing acoustic repelling on the repelling target based on the acoustic repelling waveform instructions. The present application constructs a ship motion model using a combination of millimeter-wave radar, AIS message parsing, and advanced algorithm processing, and accurately determines the three-dimensional coverage range and waveform instructions of the acoustic wave action based on this model, significantly improving the repelling accuracy and efficiency, ensuring the safety and smooth flow of maritime traffic. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the sonic expulsion process in this application; Figure 2 Schematic diagram of the sonic drive system in this application. DETAILED DESCRIPTION

[0016] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that various forms of implementation of the present disclosure are not limited to the embodiments set forth herein. Rather, the embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0017] S101, obtaining millimeter wave radar point cloud data, dynamic compensation parameters obtained by AIS message analysis, and ship threat level parameters; The system uses millimeter-wave radar to obtain real-time point cloud data of the target ship (distance r, azimuth angle θ, elevation angle ϕ in the polar coordinate system):

[0018] And parse the dynamic compensation parameters in the AIS message extension field: Draft depth compensation value: Δd = B13 − 16 × 0.1m (B13 − 16 is a 4-bit binary value); Heading differential correction value: Δψ = B20 × 0.1° / s (B20 is an 8-bit binary value, ranging from −12.8 to +12.7° / s); Differential coding compression: The difference between adjacent data is stored as 4 bits, and the compression rate is increased by 60%.

[0019] The draft compensation bits (4 bits) and heading differential correction bits (8 bits) in AIS messages are compressed and stored using differential encoding technology. The compensation bit data length is 1 / 4 of the check bit. For example, when the check bit is 16 bits, the compensation bit only occupies 4 bits and is restored to the actual physical value by the protocol analysis module.

[0020] S102, constructing a ship motion model according to the dynamic compensation parameters and millimeter wave radar point cloud data; A hybrid architecture of Kalman filtering and particle filtering is used to construct a six-degree-of-freedom motion model of a ship.

[0021] Kalman filter state equation: State vector definition:

[0022] Among them, position (x, y, z), velocity (vx, vy, vz), Euler angle (ψ, θ, ϕ).

[0023] State transition equation:

[0024] Where, F: state transfer matrix (including ship hydrodynamic damping coefficient); B: control input matrix (wind and wave interference model); : process noise, k is the time step.

[0025] When the ship's steering angular velocity exceeds 3° / s or the acceleration exceeds 3m / s², the particle filter correction module is triggered.

[0026] Particle filter correction: Trigger condition: ∣ψ˙∣>3° / s or ∣a∣>3m / s2 Perturbation generation: position perturbation: Δx∼N(0,0.52)m; velocity perturbation: Δv∼U(−2,+2)m / s.

[0027] Covariance matrix update: = +ThreatLevel×diag[0.05,0.05,0.03] Furthermore, 1,000 disturbance particles were generated through Monte Carlo sampling to address prediction inaccuracies in sharp turns. The Kalman filter's base state covariance matrix was dynamically adjusted based on the threat level.

[0028] S103, generating threat area prediction data based on the ship motion model and ship characteristic parameters in the AIS message; Predict the trajectory of the ship within the next 5 seconds based on the ship motion model: Trajectory prediction equation:

[0029] Where, Δt=5s: prediction time window; : The plural form indicates the heading angle direction, is the state vector at the future moment, is the state vector at the current moment.

[0030] This application integrates the current speed (v) and acceleration (a) of the ship in an integral form to accurately predict the motion trajectory within the next 5 seconds, solving the error problem of traditional linear extrapolation in speed change or turning scenarios. Directly embed the heading angle change into the motion direction to accurately reflect the ship's steering action and improve the geometric fit of the trajectory prediction. The introduction of can effectively capture the variable speed motion of the ship and avoid the prediction deviation caused by the uniform speed model.

[0031] AIS messages combine vessel size (length, width) and type (freighter / speedboat) to generate a probability distribution map of the threat area. Threat level parameters are calculated based on vessel speed, course deviation angle, and historical behavior patterns.

[0032] Threat Level Calculation:

[0033] in, : Maximum speed corresponding to the ship type (25m / s for cargo ships and 40m / s for speedboats); :captain.

[0034] This application uses the tanh function to normalize velocity, suppressing sudden changes in the threat value of high-speed targets and smoothing the response curve. The ratio of the heading deviation angle (Δψ) to 30° quantifies the degree of deviation of the ship's heading from the safe route and promptly identifies abnormal steering behavior.

[0035] Furthermore, the scaling factor between ship length (Lship) and 200 meters reflects the potential threat of large ships, enhancing sensitivity to high-risk targets such as cargo ships. The tanh function also maps speed to the [0, 1] interval, avoiding oversensitivity to extreme speeds in linear scaling and balancing threat assessments for different ship types.

[0036] S104, determining a three-dimensional coverage range of the acoustic wave action based on the threat area prediction data and the ship aspect ratio parameter; The three-dimensional coverage of the acoustic wave is calculated using a hyperbolic geometry model.

[0037] Hyperbolic model equation:

[0038] Where, α: heading angle; L=1.2 (major axis); (minor axis); (Height axis).

[0039] The hyperbolic model more accurately matches the dynamic motion trajectory of a vessel, with its major axis aligned with the tangent of the vessel's motion, ensuring that the acoustic coverage area closely matches the vessel's actual motion path. Furthermore, the minor axis (S) dynamically adjusts based on the vessel's aspect ratio and wave height, while the height axis (H) integrates draft depth and real-time oceanographic data to enhance coverage accuracy in complex sea conditions.

[0040] When the threat level is ≥ 2:

[0041] The long axis is aligned with the tangent of the ship's trajectory, the short axis length is dynamically adjusted based on the ship's aspect ratio, and the elevation axis incorporates real-time wave height and draft data. When the threat level is ≥ 2, the coverage area automatically expands by 20%.

[0042] When the threat level is ≥ 2, the coverage area will be automatically expanded (20%) to enhance the ability to repel high-risk targets.

[0043] S105: calculating transducer array beamforming parameters based on the three-dimensional coverage and a preset safety threshold; The transducer adopts a three-layer ring array topology, with the inner ring unit spacing being half a wavelength (λ / 2) and the outer ring spacing being dynamically adjusted according to the golden section coefficient (0.618λ).

[0044] Ring array design: Cell spacing calculation:

[0045] Phase difference control equation:

[0046] Where, R: ring radius; N: number of single ring units; θ: target azimuth, is the phase difference of the nth transducer unit.

[0047] The phase difference gradient is distributed along the normal direction of the target motion trajectory, supporting multi-beam synchronous control.

[0048] The golden section coefficient (0.618λ) reduces interference between adjacent units and improves the energy concentration of the main lobe of the beam.

[0049] The phase difference gradient is distributed along the target normal direction, which enhances the beam directivity and reduces sidelobe leakage.

[0050] Dynamic adjustment of the spacing (λ is the wavelength) supports efficient generation of sound waves of different frequencies.

[0051] Multi-beam synchronous control: Number of beams:

[0052] Energy distribution rules:

[0053] in, and are the acoustic wave energy allocated to the i-th target and the total acoustic wave energy available to the system, respectively.

[0054] It supports up to 12 independent beams (θ3dB=15°), which can drive away multiple threatening ships at the same time.

[0055] Allocate total energy according to the threat level ratio, optimize resource utilization, and give priority to suppressing high-risk targets.

[0056] S106, generating an acoustic wave repelling waveform instruction according to the array beamforming parameter and the ship threat level parameter; Generates graded acoustic signals based on threat level: Level 1 alert: 10kHz continuous wave, sound pressure level 140dB; Level 2 drive: 20kHz swept frequency pulse (±5kHz), duty cycle 30%, sound pressure level 150dB; Level 3 Strong: 40kHz shock wave, 10% duty cycle, 160dB SPL.

[0057] Dynamic adjustment of sound pressure level:

[0058] Here, SPL is the sound pressure level.

[0059] The higher the threat level, the greater the sound pressure level, achieving a balance between deterrence and safety, avoiding excessive use of high energy, and reducing the impact on non-target areas.

[0060] Frequency modulation rules:

[0061] As the threat level increases, the center frequency doubles, making high-frequency shock waves more effective against high-threat targets. High-frequency sound waves (such as 40kHz) have less impact on humans and marine life, meeting safe repellent requirements.

[0062] S107 , performing sonic expulsion on the target according to the sonic expulsion waveform instruction.

[0063] The system transmits acoustic signals through a transducer array, monitoring the target's response in real time. If the target's heading change rate exceeds 2° / s or its range continues to decrease, the system dynamically adjusts the waveform parameters and triggers an AIS alarm. The system updates control commands every 200ms, creating a closed-loop control system.

[0064] Closed-loop correction equation

[0065] in, is the proportional coefficient; E is the error energy of the target deviating from the predicted trajectory, and are the phase difference after correction and the phase difference before correction respectively.

[0066] This application dynamically corrects the phase difference through the error energy (E) gradient to improve beam tracking accuracy. The proportional coefficient (kp=0.1) balances response speed and stability and suppresses environmental noise interference.

[0067] AIS alarm message generation: message format (compliant with ITU-R M.1371 standard extension) The present application also provides a sonic drive system, comprising: Acquisition module, which obtains millimeter-wave radar point cloud data, dynamic compensation parameters obtained by AIS message analysis, and ship threat level parameters; A construction module, constructing a ship motion model based on the dynamic compensation parameters and millimeter wave radar point cloud data; A prediction module generates threat area prediction data based on the ship motion model and ship characteristic parameters in the AIS message; An action module determines a three-dimensional coverage range of the acoustic wave action based on the threat area prediction data and the ship aspect ratio parameter; a parameter module, calculating transducer array beamforming parameters based on the three-dimensional coverage and a preset safety threshold; an instruction module, generating an acoustic wave repelling waveform instruction according to the array beamforming parameter and the ship threat level parameter; An execution module performs acoustic wave driving away of a target according to the acoustic wave driving away waveform instruction.

[0068] Furthermore, the construction module constructs a ship motion model, including: Adopting a hybrid architecture of Kalman filter framework and particle filter correction module; When it is detected that the ship's steering angular velocity exceeds a preset threshold, the particle filter correction is triggered to generate dynamic prediction parameters including the motion state covariance matrix; The particle filter correction module adopts the Monte Carlo sampling method to generate motion state disturbance parameters through the ship's historical trajectory data.

[0069] Furthermore, the action module generates threat area prediction data, including: The acoustic wave action domain is calculated based on a hyperbolic geometry model, where the long axis is aligned with the tangent direction of the ship's trajectory. The short axis length is dynamically adjusted according to the ship's aspect ratio parameters and is positively correlated with the preset safety factor; The height axis parameters are integrated with real-time ocean environment data and generated through weighted calculation of wave height and draft depth.

[0070] Furthermore, the acquisition module analyzes the dynamic compensation parameters, including: Extract the draft compensation bit and heading differential correction bit from the AIS message extension field; The compensation bit data length is set to be a specific ratio smaller than the message check bit length; Differential coding technology is used to compress, store and transmit the compensation parameters.

[0071] Furthermore, the parameter module forms parameters including: Adopting a multi-layer annular array topology, the spacing between adjacent transducer units is dynamically calculated based on the acoustic wavelength and a specific proportional coefficient; The phase difference gradient is distributed along the normal direction of the target ship's trajectory; When multiple target threats are detected, the multi-beam synchronization control module is activated to generate spatially separated independent sound field focus areas.

Claims

1. A sonic drive method, characterized in that: include: Obtain millimeter-wave radar point cloud data, dynamic compensation parameters obtained by AIS message analysis, and ship threat level parameters; Constructing a ship motion model based on the dynamic compensation parameters and millimeter wave radar point cloud data; generating threat area prediction data based on the ship motion model and ship characteristic parameters in the AIS message; determining a three-dimensional coverage range of the acoustic wave action based on the threat area prediction data and the ship aspect ratio parameter; Calculating transducer array beamforming parameters based on the three-dimensional coverage and a preset safety threshold; generating an acoustic wave repelling waveform instruction according to the array beamforming parameter and the ship threat level parameter; The target is driven away by sonic waves according to the sonic wave driving away waveform instruction.

2. The sonic drive method according to claim 1, characterized in that: The construction of the ship motion model includes: Adopting a hybrid architecture of Kalman filter framework and particle filter correction module; When it is detected that the ship's steering angular velocity exceeds a preset threshold, the particle filter correction is triggered to generate dynamic prediction parameters including the motion state covariance matrix; The particle filter correction module adopts the Monte Carlo sampling method to generate motion state disturbance parameters through the ship's historical trajectory data.

3. The sonic drive method according to claim 1, characterized in that: The method for determining the three-dimensional coverage range includes: The acoustic wave action domain is calculated based on a hyperbolic geometry model, where the long axis is aligned with the tangent direction of the ship's trajectory. The short axis length is dynamically adjusted according to the ship's aspect ratio parameters and is positively correlated with the preset safety factor; The height axis parameters are integrated with real-time ocean environment data and generated through weighted calculation of wave height and draft depth.

4. The sonic drive method according to claim 1, wherein: The analysis method of the dynamic compensation parameters includes: Extract the draft compensation bit and heading differential correction bit from the AIS message extension field; The compensation bit data length is set to be a specific ratio smaller than the message check bit length; Differential coding technology is used to compress, store and transmit the compensation parameters.

5. The sonic drive method according to claim 1, characterized in that: The method for generating the transducer array beamforming parameters includes: Adopting a multi-layer annular array topology, the spacing between adjacent transducer units is dynamically calculated based on the acoustic wavelength and a specific proportional coefficient; The phase difference gradient is distributed along the normal direction of the target ship's trajectory; When multiple target threats are detected, the multi-beam synchronization control module is activated to generate spatially separated independent sound field focus areas.

6. A sonic drive-away system, characterized in that: include: Acquisition module, which obtains millimeter-wave radar point cloud data, dynamic compensation parameters obtained by AIS message analysis, and ship threat level parameters; A construction module, constructing a ship motion model based on the dynamic compensation parameters and millimeter wave radar point cloud data; A prediction module generates threat area prediction data based on the ship motion model and ship characteristic parameters in the AIS message; An action module determines a three-dimensional coverage range of the acoustic wave action based on the threat area prediction data and the ship aspect ratio parameter; a parameter module, calculating transducer array beamforming parameters based on the three-dimensional coverage and a preset safety threshold; an instruction module, generating an acoustic wave repelling waveform instruction according to the array beamforming parameter and the ship threat level parameter; An execution module performs acoustic wave driving away of a target according to the acoustic wave driving away waveform instruction.

7. The sonic repelling system according to claim 1, characterized in that The building module builds a ship motion model, including: Adopting a hybrid architecture of Kalman filter framework and particle filter correction module; When it is detected that the ship's steering angular velocity exceeds a preset threshold, the particle filter correction is triggered to generate dynamic prediction parameters including the motion state covariance matrix; The particle filter correction module adopts the Monte Carlo sampling method to generate motion state disturbance parameters through the ship's historical trajectory data.

8. The sonic drive-away system according to claim 1, wherein: The action module generates threat area prediction data, including: The acoustic wave action domain is calculated based on a hyperbolic geometry model, where the long axis is aligned with the tangent direction of the ship's trajectory. The short axis length is dynamically adjusted according to the ship's aspect ratio parameters and is positively correlated with the preset safety factor; The height axis parameters are integrated with real-time ocean environment data and generated through weighted calculation of wave height and draft depth.

9. The sonic drive-away system according to claim 1, characterized in that: The acquisition module analyzes the dynamic compensation parameters, including: Extract the draft compensation bit and heading differential correction bit from the AIS message extension field; The compensation bit data length is set to be a specific ratio smaller than the message check bit length; Differential coding technology is used to compress, store and transmit the compensation parameters.

10. The sonic repelling system according to claim 1, characterized in that The parameter module forms parameters including: Adopting a multi-layer annular array topology, the spacing between adjacent transducer units is dynamically calculated based on the acoustic wavelength and a specific proportional coefficient; The phase difference gradient is distributed along the normal direction of the target ship's trajectory; When multiple target threats are detected, the multi-beam synchronization control module is activated to generate spatially separated independent sound field focus areas.

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