Navigation ship motion parameter extraction method and system based on wave height time sequence data

Abstract

The application discloses a kind of based on wave height timing data's navigation ship movement parameter extraction method, wave height sensor is arranged two measuring points in the same side of ship navigation main channel;Utilize double measuring point to collect channel in ship wave time-wave height data, construct basic signal set;Utilize short-time fourier transform to combine noise threshold filtering, to basic signal set it is frequency domain conversion and purification processing, obtain effective wave system frequency spectrum matrix;For transverse wave, dynamic window peak detection method is combined linear fitting to extract the angular frequency of two measuring points, for scattered wave, pass through frequency spectrum matrix binarization and improved hough transform to extract the slope of two measuring points;Based on angular frequency, the ship speed is inverted, combined with the slope of scattered wave, the vertical distance of ship from measuring point is deduced, according to the geometric analysis of double measuring points, the heading angle is deduced, the speed, ship position, heading angle parameters are output, realize the dynamic monitoring of navigation ship without active signal dependence.The application realizes high-precision, high-reliability ship dynamic monitoring in complex scene.

Description

Technical Field

[0001] This invention relates to the field of inland waterway vessel monitoring technology, and in particular to a method for extracting motion parameters of navigable vessels based on wave height time series data. Background Technology

[0002] The collection and analysis of vessel navigation information is a crucial prerequisite for maritime traffic supervision and navigation safety assurance, and its engineering applications span the entire vessel navigation process: In port scheduling, accurately grasping the real-time position, speed, and course of vessels can prevent channel congestion, reduce the risk of vessel collisions, and improve the turnover efficiency of terminal berths. In inland waterways, monitoring vessel motion parameters can effectively control violations such as exceeding speed limits and deviating from the course, ensuring the safety of navigation infrastructure such as bridges and dams. In the ocean shipping sector, the application of these technologies can provide critical data support for vessel collision avoidance, route planning, and emergency search and rescue, reducing the risk of maritime accidents.

[0003] Currently, the positioning, speed measurement, and direction finding of vessels in navigation mainly rely on active monitoring methods or the analysis of non-water wave passive signals. For example, Automatic Identification Systems (AIS) monitor vessels by having them actively transmit information such as position and speed. However, AIS has drawbacks such as reliance on autonomous cooperation from vessels, susceptibility to signal loss or shielding, and the possibility of manually shutting down onboard devices. While shore-based radar can detect vessels through electromagnetic wave reflection, it is susceptible to interference from weather conditions (such as heavy rain and dense fog) and complex terrain (such as bridge areas, mountainous regions, or islands), and its accuracy in identifying small vessels and other surface targets is relatively low.

[0004] Among passive signal-based technologies, underwater sonar achieves positioning by capturing ship noise, but it is easily interfered with by marine environmental noise (such as water flow, biological sounds, etc.) and its applicability is limited in shallow water areas; although satellite remote sensing can infer ship trajectories from ship wake images, its spatiotemporal resolution is low and cannot meet the needs of real-time monitoring.

[0005] In existing applications of water wave signals, some technologies achieve rough positioning by recording the time difference of arrival of ship waves using a single-point wave sensor. However, they do not perform spectral analysis on the dynamic characteristics of wave height time series data, making it difficult to extract key parameters such as ship speed and heading. Furthermore, the positioning error is relatively large, which cannot meet the high-precision monitoring requirements of restricted waters (such as canals, ports, and pilot channels). Summary of the Invention

[0006] The main objective of this invention is to propose a method for extracting motion parameters of navigable vessels based on wave height time-series data. By deploying dual measuring points to collect raw wave height time-series data of ship traveling waves in the waterway, high-precision positioning of the vessel is achieved through spectrum analysis, and key motion parameters such as speed and heading are extracted simultaneously. This method overcomes the dependence on active target monitoring, the environmental interference limitations of non-water wave passive technologies, the real-time defects of satellite remote sensing, and the shortcomings of existing water wave signal technologies in parameter extraction and positioning accuracy, thereby achieving high-precision and high-reliability dynamic monitoring of vessels in complex scenarios.

[0007] The technical solution adopted in this invention is: A method for extracting motion parameters of navigable vessels based on wave height time series data includes the following steps: S1. Two measuring points are set up using wave height sensors in the stable area on the same side of the main navigation channel. A and B ; S2. Collect ship wave time-wave height data in the waterway using dual measuring points to construct a basic signal set; S3. Using short-time Fourier transform combined with noise threshold filtering, the basic signal set is transformed and cleaned in the spectral domain to obtain an effective wave system spectral matrix. S4. For shear waves, the dynamic window peak detection method combined with linear fitting is used to extract the angular frequency of two measuring points. and For scattered waves, the slope of two measurement points is extracted by binarizing the spectrum matrix and using an improved Hough transform. and ; S5. Based on extracted feature parameters , The system inverts the ship's speed, derives the vertical distance between the ship and the measuring point by combining the divergence slope, and derives the heading angle based on the geometric analysis of the two measuring points. It outputs the parameters of ship speed, ship position, and heading angle, thus realizing dynamic monitoring of navigable ships without active signal dependence.

[0008] In the above scheme, in S1, the line connecting the two measuring points is as parallel as possible to the main channel axis to maximize the sensitivity of the heading angle monitoring; for curved channels, measuring points are set up along the tangential direction.

[0009] In the above scheme, the distance between the two measuring points is set to 1 to 3 times the vertical distance from the measuring point to the channel axis.

[0010] In the above scheme, the time-wave height data acquisition in S2 includes the following steps: S21. Collect background wave height data of the monitored water area for one day and exclude data during the period of ship events, and calculate its statistical characteristic value; S22, The instantaneous wave height was detected to be greater than kData recording is initiated when the background wave height is doubled to its mean value to accurately distinguish changes in ship wave height from other disturbances. k Take 2-3; S23. Record the complete data segment, including the historical wave height data for the 50 seconds before the trigger time, so as to fully capture the initial wave height rise phase when the vessel enters the monitoring area, record the transition process of the wake waveform from background noise to significant change; and record the continuous wave height data after the trigger time when the wave height falls back to the background wave height of the monitoring water area, covering the complete wake attenuation process.

[0011] In the above scheme, S2 also includes preprocessing the collected ship wave time-wave height data to generate an effective signal set containing the following characteristics: The dataset includes the initial wave height rise phase when a ship enters the monitoring area and a time-wave height dataset covering the complete wake decay process. A dataset that uses noise thresholds to filter spectral data during ship passage periods; The filtered spectral data is binarized based on energy statistics to highlight the dataset with shear wave and scattering characteristics.

[0012] In the above scheme, S3 specifically includes the following steps: S31. Analyze the spectral energy distribution during periods when there is no ship passage, calculate the mean and standard deviation of the energy during these periods, and use them as the noise threshold. S32. Use short-time Fourier transform to perform spectral conversion on the time-wave height data sequence; S33. Extract the time-frequency matrix corresponding to the data after spectrum conversion, traverse the energy values ​​of each time-frequency point in the time-frequency matrix, and filter out noise components with energy values ​​lower than the noise threshold. S34. Perform hole-filling optimization on the filtered time-frequency matrix, identify isolated low-energy holes in the effective signal region of the time-frequency matrix, and use neighborhood interpolation to fill in the isolated low-energy holes to restore the integrity of the time-frequency matrix; finally, the effective wave system spectrum matrix is ​​obtained.

[0013] In the above scheme, in S4, for the transverse wave, the angular frequency is extracted using a dynamic window peak detection method combined with linear fitting based on the Python scientific computing library. and Specifically, it includes: Dynamic window initialization, sliding window length set to The time span is 1 second, covering multiple shear wave periods, with the sliding step size set to 1 / 4 of the sliding window length, and the time axis of the filtered time-frequency matrix is ​​traversed. Search for energy peaks in the 0.07-0.23Hz frequency band within each window and mark them as candidate frequencies for shear waves; Linear fitting is performed on the candidate frequencies of the shear waves for each window. ,in, Indicates the transverse wave frequency. Indicates time, and These represent the fitting coefficients; for the trend line obtained by linear fitting, the average trend value is calculated within the time window as the stable angular frequency of the shear wave. For measuring points A, B Perform these operations separately to obtain the results. and .

[0014] In the above scheme, in S4, the slope of the two measurement points is extracted for the scattered wave by binarizing the spectrum matrix and using an improved Hough transform. and Specifically, it includes: The filtered time-frequency matrix is ​​binarized, and the mean energy is calculated. and standard deviation Set threshold Points with energy above the threshold are marked as 1, and those below are marked as 0. Using the properties of the Hough transform, the equation of the slant line of the scattering wave is derived. Transform into the general form of a straight line Corresponding to polar coordinates, the problem of finding the parameters of the oblique line in the time domain is transformed into the problem of finding the intersection point in polar coordinates; among which, Indicates the scattering frequency, The initial frequency of the dispersion is represented by S, and the dispersion slope is represented by S. d , e , g The coefficients represent the coefficients when the equation of a slanted line is transformed into the general form of a straight line. Considering the physical constraints of scattering waves, the slope ,angle Filter out invalid solutions, including transverse waves and noise; Create a polar coordinate accumulator with the horizontal axis representing angles. The vertical axis represents distance. , to the spectrum Figure 2 Substituting the value point into the calculation of possible values Then vote and find the one with the most votes in the accumulator. ; The slope is derived from the angle of the highest vote. For each measuring point A, B The scattering slope is obtained by calculating the data. and .

[0015] In the above scheme, in S5, the method for calculating the ship's speed is as follows: the ship at the measuring point... A, B The speeds are respectively , The average ship speed is taken. ; Ship leaving the measurement point A, B The vertical distances are respectively ; Heading angle ; in, The transverse wave angular frequency; The angular frequency of the dispersion wave; It is the acceleration due to gravity; The time difference between the two measuring points; The distance between the two measuring points; It is the Kelvin angle.

[0016] Accordingly, the present invention also proposes a navigation vessel motion parameter extraction system based on wave height time series data, including a ship wave signal acquisition module, a spectrum feature extraction module, and a ship motion parameter inversion module; The ship wave signal acquisition module uses two measuring points deployed in the stable area on the same side of the main navigation channel to collect ship wave time-wave height data in the channel and construct a basic signal set. The spectral feature extraction module utilizes short-time Fourier transform combined with noise threshold filtering to perform spectral domain transformation and purification on the basic signal set, obtaining an effective wave system spectral matrix. For transverse waves, a dynamic window peak detection method combined with linear fitting is used to extract the angular frequencies of two measurement points. and For scattered waves, the slope of two measurement points is extracted by binarizing the spectrum matrix and using an improved Hough transform. and ; The ship motion parameter inversion module is based on the extracted feature parameters. , The system inverts the ship's speed, derives the vertical distance between the ship and the measuring point by combining the divergence slope, and derives the heading angle based on the geometric analysis of the two measuring points. It outputs the parameters of ship speed, ship position, and heading angle, thus realizing dynamic monitoring of navigable ships without active signal dependence.

[0017] The beneficial effects of this invention are: This invention extracts multi-dimensional motion parameters of navigating vessels by performing spectral analysis and calculating the dispersion curve of ship-borne wave height time-series data, enabling the inversion of motion parameters such as vessel speed, distance from shore, and course. This method eliminates the need for multi-device collaboration, avoiding the time-consuming data fusion and systemic errors associated with coordinating multiple types of monitoring equipment. Based on ship-borne wave height time-series data acquired from dual measuring points, this method requires no active cooperation from the vessel; it only needs to monitor the transverse wave and scattered wave time-series signals during vessel navigation. The wave height time-series data is unaffected by external environmental factors such as rain, fog, and nighttime, thus solving the blind zone problem faced by active signal-dependent technologies in practical applications. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of the method for extracting motion parameters of navigable ships based on wave height time series data according to the present invention; Figure 2 This is a flowchart of the short-time Fourier algorithm time-frequency conversion filtering in the method of this invention; Figure 3 This is a flowchart of the extraction of shear wave dispersion features and ship motion parameters in the method of this invention; Figure 4 This is a schematic diagram illustrating the solution of ship navigation geometry in the method of this invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0021] like Figure 1 As shown, this invention proposes a method for extracting navigational motion parameters based on wave height time-series data. By deploying dual measuring points to collect raw wave height time-series data of ship traveling waves in the waterway, the dispersion curve relationship between shear waves and scattered waves in the ship traveling waves is analyzed. This addresses problems in inland waterway vessel monitoring such as over-reliance on active ship signals, insufficient accuracy of parameter inversion in complex waterways, and the lack of a non-cooperative, high-precision, multi-dimensional parameter monitoring scheme. The method specifically includes the following steps: S1. Two measuring points are set up using wave height sensors in the stable area on the same side of the main navigation channel. A and B.

[0022] Two measuring points A and B Measurement points should be placed in stable areas (such as rigid embankments or fixed pile foundations) on the same side of the main navigation channel, avoiding turbulent water areas and obstructions to ensure unobstructed propagation of ship wave timing signals. The line connecting the two points should be as parallel as possible to the main channel axis to maximize the sensitivity of heading angle monitoring; for curved channels, measurement points can be placed along the tangent direction. The spacing between the two measurement points needs to balance the requirements of signal resolution and parameter extraction accuracy. The spacing setting must ensure sufficient time difference for accurate identification of water wave information while also ensuring the accuracy of ship motion parameter calculation. The measurement point spacing is generally set to 1 to 3 times the vertical distance from the measurement point to the channel axis.

[0023] S2. Collect ship wave time-wave height data in the channel using dual measuring points to construct a basic signal set.

[0024] Time-wave height data acquisition includes the following steps: S21. Collect background wave height data of the monitored water area for one day and exclude data during the period of ship events, and calculate its statistical characteristic value; S22, The instantaneous wave height was detected to be greater than k Data recording is initiated when the background wave height is doubled to its mean value to accurately distinguish changes in ship wave height from other disturbances. k Take 2-3; S23. Record the complete data segment, including the historical wave height data for the 50 seconds before the trigger time, so as to fully capture the initial wave height rise phase when the vessel enters the monitoring area, record the transition process of the wake waveform from background noise to significant change; and record the continuous wave height data after the trigger time when the wave height falls back to the background wave height of the monitoring water area, covering the complete wake attenuation process.

[0025] Then, the collected ship wave time-wave height data is preprocessed to generate an effective signal set containing the following characteristics: The dataset includes the initial wave height rise phase when a ship enters the monitoring area and a time-wave height dataset covering the complete wake decay process. A dataset that uses noise thresholds to filter spectral data during ship passage periods; The filtered spectral data is binarized based on energy statistics to highlight the dataset with shear wave and scattering characteristics.

[0026] S3. Using the Short-time Fourier Transform (STFT) combined with noise threshold filtering, the basic signal set is transformed and cleaned in the spectral domain to obtain an effective wave system spectrum matrix.

[0027] To ensure the quality of the raw wave height data of the ship's sailing waves, noise filtering preprocessing is required on the time-wave height data obtained in S2. See the flowchart for S3. Figure 2 Specifically, it includes the following steps: S31. Analyze the spectral energy distribution during periods when there is no ship passage, calculate the mean and standard deviation of the energy during this period, and use them as the noise threshold.

[0028] S32. Considering the non-stationary time-varying characteristics of ship waves, the short-time Fourier transform is used to perform spectral conversion on the time-wave height data sequence; the short-time Fourier transform formula is as follows:

[0029] In the formula, It is a continuous-time signal to be analyzed. It is a window function. Indicates time, This indicates the position of the window function on the time axis; This is the kernel function for the Fourier transform.

[0030] S33. Extract the time-frequency matrix corresponding to the data after spectrum conversion, traverse the energy values ​​of each time-frequency point in the time-frequency matrix, and filter out noise components with energy values ​​lower than the noise threshold.

[0031] S34. Perform hole-filling optimization on the filtered time-frequency matrix, identify isolated low-energy holes in the effective signal region of the time-frequency matrix, and use neighborhood interpolation to fill in the isolated low-energy holes to restore the integrity of the time-frequency matrix; finally, the effective wave system spectrum matrix is ​​obtained.

[0032] S4. For shear waves, the dynamic window peak detection method combined with linear fitting is used to extract the angular frequency of two measuring points. and For scattered waves, the slope of two measurement points is extracted by binarizing the spectrum matrix and using an improved Hough transform. and .

[0033] Based on the characteristics of ship wave signals, the time-wave height data processing method uses short-time Fourier transform combined with the Blackman-Harris 92 dB window function. Since the transverse waves and scattered waves in ship waves belong to the low-frequency range (less than 1 Hz), in order to accurately distinguish similar low-frequency components, the frequency resolution should be less than the lowest significant frequency of the ship wave. The frequency resolution is set to 0.01 Hz, corresponding to a window length of 100 seconds. To ensure the continuity of the spectrum and improve the accuracy of dynamic feature tracking, and to adapt to the continuous changing characteristics of ship waves, the overlap rate is set to 75%.

[0034] To reliably identify the peak energy of shear waves, a dynamic window peak detection method combined with linear fitting was used based on the Python scientific computing library to extract the angular frequency. and Specifically, it includes: (1) Initialize the dynamic window and set the sliding window length to 0.5. The time is measured in seconds, covering multiple shear wave cycles. The sliding step size is set to 1 / 4 of the sliding window length. By traversing the time axis of the filtered time-frequency matrix, it can be ensured that the shear wave frequency can be captured by the continuous window, avoiding missed detection of changing trends. (2) Search for the energy peak (i.e. the main distribution range of shear waves) in the 0.07-0.23Hz frequency band within each window and mark it as a candidate frequency for shear waves; (3) Perform linear fitting on the candidate frequencies of the transverse waves for each window. ,in, Indicates the transverse wave frequency. Indicates time, and These represent the fitting coefficients; for the trend line obtained by linear fitting, the average trend value is calculated within the time window as the stable angular frequency of the shear wave. For measuring points A, B Perform these operations separately to obtain the results. and In reality, candidate frequencies may exhibit slow, trend-like fluctuations due to minute changes in ship motion and environmental disturbances. Linear fitting can first capture this trend, and then take the mean value based on the trend line, resulting in a more accurate representation of the true and stable frequency characteristics.

[0035] The scattered wave in the spectrum is a tilted energy band whose frequency increases linearly with time, satisfying the following condition: ,in, Indicates the scattering frequency, Let S represent the initial frequency of the dispersion and S represent the dispersion slope. For dispersion analysis, also based on Python scientific computing libraries, the slopes at two measurement points are extracted through spectrum matrix binarization and an improved Hough transform. and Specifically, it includes: (1) Binarize the filtered time-frequency matrix and calculate the mean energy. and standard deviation Set threshold Points with energy above the threshold are marked as 1 (to retain candidate points for scattering) and those below the threshold are marked as 0 (to filter background noise). (2) Using the properties of the Hough transform, the equation of the scattering wave is transformed into the equation of the scattering wave. Transform into the general form of a straight line ,in, d , e ,g The coefficients represent the coefficients when the equation of the oblique line is transformed into the general form of the straight line, corresponding to the polar coordinate form. This transforms the problem of finding the oblique line parameters in the time domain into the problem of finding the intersection point in polar coordinates. (3) Considering the physical constraints of the scattering wave, the slope ,angle Filtering includes transverse waves (horizontal, ) and noise ( Invalid solutions, including those not included in the above. (4) Create a polar coordinate accumulator with the horizontal axis representing angles. The vertical axis represents distance. , to the spectrum Figure 2 Substituting the value point into the calculation of possible values Then vote and find the one with the most votes in the accumulator. ; (5) Derive the slope from the angle of the highest vote. For each measuring point A, B The scattering slope is obtained by calculating the data. and .

[0036] S5. Based on extracted feature parameters , The ship's speed is inverted, and the vertical distance between the ship and the measuring point is derived by combining the dispersion slope. The heading angle is then calculated based on the geometric analysis of the two measuring points. The ship's speed, position, and heading angle parameters are output, enabling dynamic monitoring of navigable vessels without active signal dependence. (See flowchart.) Figure 3 .

[0037] The formulas for calculating the frequencies of transverse waves and scattered waves are as follows:

[0038]

[0039] in, The transverse wave angular frequency; The angular frequency of the dispersion wave; For ship speed; The vertical distance from the ship to the measuring point; For time; This is the acceleration due to gravity.

[0040] The method for calculating ship speed is as follows: the ship is at the measuring point A, B The speeds are respectively , The average ship speed is taken. .

[0041] Ship leaving the measurement point A, B The vertical distances are respectively .

[0042] The course angle can be calculated based on the geometric relationship between the measuring point and the ship. (Note:) A, B The time of intersection between the scattered wave and the shear wave at the measuring point is Time difference between two measuring points The distance between the two measuring points is The projection of the navigation distance of the vessel during the aforementioned period onto the line connecting the two points is equal to the distance between the two measuring points, taking into account the Kelvin angle. The sum of the components under influence, and their geometric relationships are shown in the appendix. Figure 4 ,in O It is a fixed reference point, used as the origin for determining the ship's navigation direction and related geometric relationships. P, Q Observation points A, B Projection on the shipping route line M, N The position of the ship at different times is obtained through geometric calculations. heading angle .

[0043] Accordingly, the present invention also proposes a navigation vessel motion parameter extraction system based on wave height time series data, including a ship wave signal acquisition module, a spectrum feature extraction module, and a ship motion parameter inversion module; The ship wave signal acquisition module uses two measuring points deployed in the stable area on the same side of the main navigation channel to collect ship wave time-wave height data in the channel and construct a basic signal set. The spectral feature extraction module utilizes short-time Fourier transform combined with noise threshold filtering to perform spectral domain transformation and purification on the basic signal set, obtaining an effective wave system spectral matrix. For transverse waves, a dynamic window peak detection method combined with linear fitting is used to extract the angular frequencies of two measurement points. and For scattered waves, the slope of two measurement points is extracted by binarizing the spectrum matrix and using an improved Hough transform. and ; The ship motion parameter inversion module is based on the extracted feature parameters. , The system inverts the ship's speed, derives the vertical distance between the ship and the measuring point by combining the divergence slope, and derives the heading angle based on the geometric analysis of the two measuring points. It outputs the parameters of ship speed, ship position, and heading angle, thus realizing dynamic monitoring of navigable ships without active signal dependence.

[0044] It should be noted that, depending on the implementation needs, the various steps / components described in this application can be broken down into more steps / components, or two or more steps / components or parts of the operation of steps / components can be combined into new steps / components to achieve the purpose of this invention.

[0045] The order of the steps in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0046] It should be understood that those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A method for extracting motion parameters of navigable vessels based on wave height time-series data, characterized in that, Includes the following steps: S1. Two measuring points are set up using wave height sensors in the stable area on the same side of the main navigation channel. A and B ; S2. Collect ship wave time-wave height data in the waterway using dual measuring points to construct a basic signal set; S3. Using short-time Fourier transform combined with noise threshold filtering, the basic signal set is transformed and cleaned in the spectral domain to obtain an effective wave system spectral matrix. S4. For shear waves, the dynamic window peak detection method combined with linear fitting is used to extract the angular frequency of two measuring points. and ; For scattered waves, the slope of two measurement points is extracted by binarizing the spectrum matrix and using an improved Hough transform. and Specifically, it includes: The filtered time-frequency matrix is ​​binarized, and the mean energy is calculated. and standard deviation Set threshold Points with energy above the threshold are marked as 1, and those below are marked as 0. Using the properties of the Hough transform, the equation of the slant line of the scattering wave is derived. Transform into the general form of a straight line Corresponding to polar coordinates, the problem of finding the parameters of the oblique line in the time domain is transformed into the problem of finding the intersection point in polar coordinates; among which, Indicates the scattering frequency, Indicates the initial frequency of the scattering wave. S Indicates the slope of the dispersion wave. d , e , g The coefficients represent the coefficients when the equation of a slanted line is transformed into the general form of a straight line. Considering the physical constraints of scattering waves, the slope ,angle Filter out invalid solutions, including transverse waves and noise; Create a polar coordinate accumulator with the horizontal axis representing angles. The vertical axis represents distance. Substituting the binarized points of the spectrum into the calculation of possible... Then vote and find the one with the most votes in the accumulator. ; The slope is derived from the angle of the highest vote. For each measuring point A, B The scattering slope is obtained by calculating the data. and ; S5. Based on extracted feature parameters , The system inverts the ship's speed, derives the vertical distance between the ship and the measuring point by combining the divergence slope, and derives the heading angle based on the geometric analysis of the two measuring points. It outputs the parameters of ship speed, ship position, and heading angle, thus realizing dynamic monitoring of navigable ships without active signal dependence.

2. The method for extracting navigational vessel motion parameters based on wave height time series data according to claim 1, characterized in that, In S1, the line connecting the two measuring points is as parallel as possible to the main channel axis to maximize the sensitivity of the heading angle monitoring; for curved channels, measuring points are set up along the tangential direction.

3. The method for extracting navigational vessel motion parameters based on wave height time series data according to claim 2, characterized in that, The distance between two measuring points is set to 1 to 3 times the vertical distance from the measuring point to the channel axis.

4. The method for extracting navigational vessel motion parameters based on wave height time series data according to claim 1, characterized in that, In S2, time-wave height data acquisition includes the following steps: S21. Collect background wave height data of the monitored water area for one day and exclude data during the period of ship events, and calculate its statistical characteristic value; S22, The instantaneous wave height was detected to be greater than k Data recording is initiated when the background wave height is doubled to its mean value to accurately distinguish changes in ship wave height from other disturbances. k Take 2-3; S23. Record the complete data segment, including the historical wave height data for the 50 seconds before the trigger time, so as to fully capture the initial wave height rise phase when the vessel enters the monitoring area, record the transition process of the wake waveform from background noise to significant change; and record the continuous wave height data after the trigger time when the wave height falls back to the background wave height of the monitoring water area, covering the complete wake attenuation process.

5. The method for extracting navigational vessel motion parameters based on wave height time series data according to claim 1, characterized in that, S2 also includes preprocessing the acquired ship wave time-wave height data to generate an effective signal set containing the following characteristics: The dataset includes the initial wave height rise phase when a ship enters the monitoring area and a time-wave height dataset covering the complete wake decay process. A dataset that uses noise thresholds to filter spectral data during ship passage periods; The filtered spectral data is binarized based on energy statistics to highlight the dataset with shear wave and scattering characteristics.

6. The method for extracting navigational vessel motion parameters based on wave height time series data according to claim 1, characterized in that, S3 specifically includes the following steps: S31. Analyze the spectral energy distribution during periods when there is no ship passage, calculate the mean and standard deviation of the energy during these periods, and use them as the noise threshold. S32. Use short-time Fourier transform to perform spectral conversion on the time-wave height data sequence; S33. Extract the time-frequency matrix corresponding to the data after spectrum conversion, traverse the energy values ​​of each time-frequency point in the time-frequency matrix, and filter out noise components with energy values ​​lower than the noise threshold. S34. Perform hole-filling optimization on the filtered time-frequency matrix, identify isolated low-energy holes in the effective signal region of the time-frequency matrix, and use neighborhood interpolation to fill in the isolated low-energy holes to restore the integrity of the time-frequency matrix; finally, the effective wave system spectrum matrix is ​​obtained.

7. The method for extracting navigational vessel motion parameters based on wave height time series data according to claim 1, characterized in that, In S4, for shear waves, the angular frequency is extracted using a dynamic window peak detection method combined with linear fitting based on a Python scientific computing library. and Specifically, it includes: Dynamic window initialization, sliding window length set to The time span is 1 second, covering multiple shear wave periods, with the sliding step size set to 1 / 4 of the sliding window length, and the time axis of the filtered time-frequency matrix is ​​traversed. Search for energy peaks in the 0.07-0.23Hz frequency band within each window and mark them as candidate frequencies for shear waves; Linear fitting is performed on the candidate frequencies of the shear waves for each window. ,in, Indicates the transverse wave frequency. Indicates time, and These represent the fitting coefficients; for the trend line obtained by linear fitting, the average trend value is calculated within the time window as the stable angular frequency of the shear wave. For measuring points A, B Perform these operations separately to obtain the results. and .

8. The method for extracting navigational vessel motion parameters based on wave height time series data according to claim 1, characterized in that, In S5, the method for calculating ship speed is as follows: the ship at the measuring point... A, B The speeds are respectively , The average ship speed is taken. ; Ship leaving the measurement point A, B The vertical distances are respectively ; Heading angle ; in, It is the acceleration due to gravity; The time difference between the two measuring points; The distance between the two measuring points; It is the Kelvin angle.

9. A system for extracting motion parameters of navigable vessels based on wave height time-series data, characterized in that, The system is used to implement the method according to any one of claims 1-8, and the system includes a ship traveling wave signal acquisition module, a spectrum feature extraction module, and a ship motion parameter inversion module; The ship wave signal acquisition module uses two measuring points deployed in the stable area on the same side of the main navigation channel to collect ship wave time-wave height data in the channel and construct a basic signal set. The spectral feature extraction module utilizes short-time Fourier transform combined with noise threshold filtering to perform spectral domain transformation and purification on the basic signal set, obtaining an effective wave system spectral matrix. For transverse waves, a dynamic window peak detection method combined with linear fitting is used to extract the angular frequencies of two measurement points. and For scattered waves, the slope of two measurement points is extracted by binarizing the spectrum matrix and using an improved Hough transform. and ; The ship motion parameter inversion module is based on the extracted feature parameters. , The system inverts the ship's speed, derives the vertical distance between the ship and the measuring point by combining the divergence slope, and derives the heading angle based on the geometric analysis of the two measuring points. It outputs the parameters of ship speed, ship position, and heading angle, thus realizing dynamic monitoring of navigable ships without active signal dependence.

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