Marine towering object protection distance prediction analysis method based on radar technology

Abstract

The invention belongs to the technical field of maritime safety and intelligent navigation, and particularly relates to a maritime high-rise protection distance prediction analysis method based on a radar technology, which comprises the following steps of: establishing a space grid by acquiring a detection efficiency attenuation field around a maritime high-rise, and extracting a radar signal attenuation value, a space change gradient and a distance-height ratio of each grid unit; after normalization and nonlinear transformation, the radar interference risk is determined according to the range of three transformation results, the real-time ship density and the ship encounter threat value of each grid unit are calculated based on the real-time ship AIS data, and the navigation conflict risk is determined; weighting and fusing the two corresponding risks into a comprehensive risk, and dynamically delimiting the boundary of the grading protection area according to the comprehensive risk; and monitoring the ships entering the area, and generating and sending a navigation instruction according to the position risk levels of the ships. According to the method, through grid analysis, multi-feature fusion and a dynamic decision-making mechanism, the complex radar interference and navigation conflict mixed risk caused by the towering object is effectively dealt with.

Description

Technical Field

[0001] This invention belongs to the field of maritime safety and intelligent navigation technology, specifically a method for predicting and analyzing the protection distance of tall objects at sea based on radar technology. Background Technology

[0002] With the continuous development of marine resources and the increasing density of maritime traffic, the number of tall structures at sea, such as offshore wind farms, drilling platforms, and bridge towers of cross-sea bridges, is increasing. This poses a serious challenge to navigation safety and radar surveillance effectiveness in the surrounding waters. On the one hand, the tall structures themselves pose a risk of physical collisions. On the other hand, their complex metal structures can cause interference such as shielding, reflection, and scattering of shipborne and shore-based radar signals, resulting in non-uniform attenuation of radar detection performance in the surrounding space, forming radar blind spots or false targets, and significantly increasing the probability of ship misjudgment and collisions.

[0003] The main methods for protecting against the above risks include the following two categories: First, based on the recommendations of the International Maritime Organization or historical experience, setting up warning zones or no-navigation zones at fixed distances around tall objects; Second, tracking and assessing collision risks of ships by analyzing their AIS data.

[0004] However, existing technologies still have the following limitations: existing protection methods mostly adopt isolated or simply superimposed risk assessment methods, usually based on fixed rules or a single data source for analysis, failing to effectively integrate multi-dimensional information such as radar physical propagation characteristics, spatial attenuation gradient and ship dynamic encounter situation, resulting in one-sided risk judgment basis, and lacking a systematic fusion modeling and dynamic calibration mechanism for complex risk scenarios formed by the intertwining of tall structures and ship behavior. Summary of the Invention

[0005] To overcome the shortcomings in the prior art, embodiments of the present invention provide a radar-based method for predicting and analyzing the protection distance of tall objects at sea, which can effectively solve the problems mentioned in the prior art.

[0006] The objective of this invention can be achieved through the following technical solution: a radar-based method for predicting and analyzing the protection distance of tall objects at sea, comprising: acquiring the detection effectiveness attenuation field around the tall objects at sea and real-time ship AIS data.

[0007] A spatial coordinate grid is established based on the detection effectiveness attenuation field. Each grid is used as a spatial unit to extract the radar signal attenuation value, spatial variation gradient, and distance-height ratio with tall objects. Through normalization and nonlinear transformation, the range between the three transformation results is determined as the radar interference risk.

[0008] Based on real-time ship AIS data, the real-time ship density of each spatial unit is calculated, as well as the encounter threat value aggregated for all ships based on the nearest encounter time and distance, in order to determine the risk of maritime conflict.

[0009] The radar interference risk and maritime conflict risk of the same spatial unit are weighted and integrated to generate a comprehensive risk. Based on the level contour lines of this comprehensive risk value, the boundaries of graded protection zones are dynamically delineated.

[0010] The system monitors vessels entering the protected area and generates navigation instructions based on their positional risk level. If there is an immediate risk of collision, it executes an emergency avoidance instruction; otherwise, it performs route optimization control.

[0011] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention establishes a unified spatial coordinate grid, synchronously quantifies radar signal attenuation, spatial gradient change, ship density and multi-source heterogeneous risk factors of the threats encountered, realizes the integration of radar detection characteristics and traffic dynamics, overcomes the limitations of a single criterion, and effectively improves the comprehensiveness of risk assessment.

[0012] (2) This invention integrates radar interference risk and maritime conflict risk to generate a comprehensive risk value. By calculating the risk level contour lines, the graded protection boundary is dynamically delineated, so that the protection area can reflect the changes in radar detection blind zone evolution and traffic flow risk accumulation in real time. This allows the protection area to be dynamically adjusted according to real-time risk, replacing the traditional fixed warning zone setting method. Under the premise of ensuring safety, the utilization efficiency of navigation resources is optimized.

[0013] (3) The present invention dynamically generates graded protection boundaries based on the fusion risk value, and automatically generates route optimization or emergency avoidance instructions based on the real-time position and risk level of the ship, forming a perception-assessment-control closed loop, realizing intelligent protection from static warning to risk-driven and proactive intervention.

[0014] (4) By introducing spatial gridding analysis, multi-feature normalization and nonlinear transformation, as well as multi-factor weighted fusion and consistency verification mechanism, this invention can effectively handle the complex risk scenarios formed by the intertwining of non-uniform radar interference field caused by the complex structure of tall objects and the dynamic behavior of ships. Attached Figure Description

[0015] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the method flow of the present invention.

[0017] Figure 2 This is a schematic diagram illustrating the process of establishing a spatial coordinate grid for this invention.

[0018] Figure 3 This is a flowchart illustrating the process of generating comprehensive risk for this invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Reference Figure 1 As shown, the present invention provides a method for predicting and analyzing the protection distance of tall objects at sea based on radar technology, including: S1. acquiring the detection effectiveness attenuation field around the tall objects at sea and real-time ship AIS data.

[0021] The process of obtaining the detection effectiveness attenuation field is as follows: obtain the radar deployment parameters and a high-precision three-dimensional model of the tall object at sea. The high-precision three-dimensional model includes at least the geometric contour and material classification information of the surface of the tall object. The deployment parameters are directly read from the facility technical data of the tall object at sea or the nameplate of the radar equipment, including its geographical coordinates, antenna height, operating frequency and beamwidth.

[0022] It should be noted that if a high-precision 3D model cannot be obtained, a simplified geometric model combined with typical material parameters can be used for approximate calculations.

[0023] In this embodiment, in order to obtain the optimal surveillance field of view, the radar is preferentially deployed at the top of the towering structure itself or the highest structural point nearby, and a spatial reference system is established with the radar phase center as the origin.

[0024] Using the radar phase center as the origin, based on the high-precision three-dimensional model and the radar beamwidth, within the solid angle range corresponding to the beamwidth, a series of rays are emitted at preset azimuth and elevation angle intervals. The surface represented by the high-precision three-dimensional model is discretized into a grid representation composed of multiple triangular facets. For each ray emitted from the radar phase center, it is represented as a spatial straight line with an origin and a direction vector. All triangular facets on the model surface are traversed, and the intersection parameters of the ray and the plane containing the triangle are calculated. It is determined whether the intersection point is within the boundary range of the triangular facet. If multiple triangular facets intersect with the ray, the intersection point closest to the origin along the ray direction is selected as the valid intersection point, and its spatial three-dimensional coordinates are recorded, thereby forming the ray path set.

[0025] The elevation angle interval is determined based on the radar beamwidth and ray density requirements. Specifically, the azimuth angle interval and elevation angle interval are determined based on the required ray density requirements. Specifically, based on the spatial sampling density in the azimuth and elevation directions specified by the ray density requirements, the corresponding number of divisions N and M are determined respectively. The ratio of the beamwidth to N is used as the azimuth angle interval, and the ratio of the beamwidth to M is used as the elevation angle interval.

[0026] For each ray path, the actual propagation path length is taken as the distance from the radar phase center to the intersection of the ray and the high-precision 3D model. The free-space propagation loss at this path length is calculated based on the radar equation inversion. The calculation formula used is as follows: .

[0027] in, This represents the free-space propagation loss. This indicates the path length of the ray. Indicates the radar's operating wavelength, which is determined by the radar's operating frequency. According to the formula Calculations show that It is the speed of light.

[0028] Obtain the path length of each ray and through radar operating frequency Obtain wavelength Then, by substituting the above parameters into the formula, the signal power loss caused by the propagation of the ray path in free space can be calculated.

[0029] Based on the radar operating frequency, the electromagnetic parameter database of the surface material of the tall object is queried to obtain the complex permittivity and complex permeability of the surface material corresponding to the intersection point. Then, the reflection and diffraction at the intersection point are calculated using the physical optics method or geometric diffraction theory in the prior art. The free space loss, reflection attenuation and diffraction attenuation are superimposed in decibels to obtain the comprehensive radar signal attenuation factor of the spatial point.

[0030] It should be noted that the complex permittivity and complex permeability of common building materials vary with frequency, but in the microwave band, their values ​​are relatively stable and usually fall within a typical range. These typical values ​​can be obtained from electromagnetic handbooks or verified dedicated material databases. The material electromagnetic parameter database involved in this invention refers to a set of data known in this technical field that records the complex permittivity and complex permeability of various materials at different frequencies.

[0031] The above values ​​are illustrative examples. In practical applications, more accurate frequency-varying electromagnetic parameters can be queried from the aforementioned known data sources based on the specific material type confirmed in the as-built data of the tall building.

[0032] All spatial points within the effective detection range of the radar are considered as discrete sample points, and their radar signal comprehensive attenuation factor is the sample value. Based on the spatial coordinates of all discrete sample points and their comprehensive attenuation factor sample values, a theoretical variogram function describing the change of the attenuation factor with spatial distance is calculated and fitted.

[0033] For example, an exponential function can be used to calculate the relationship between the variance of the attenuation factor difference between any two sample points and the distance, and the sill value, range, and nugget value parameters of the theoretical variogram can be determined accordingly. For any spatial point in the radar surveillance area that needs to be interpolated for attenuation estimation, a set of Kriging equations with the minimum estimation error variance as the optimization objective is established based on the spatial variogram, and the optimal weight coefficients of each known sample point are obtained by solving the equations. The attenuation factor values ​​of the surrounding known sample points are then weighted linearly according to the optimal weights to obtain the optimal unbiased estimate of the attenuation factor of the sample point. All sample points are traversed to complete the three-dimensional spatial interpolation and generate a continuous three-dimensional detection effectiveness attenuation field.

[0034] It should be noted that this invention uses a theoretical variogram based on spatial distance for Kriging interpolation. The core rationale is that in the near-field surveillance area centered on tall objects, signal attenuation caused by obstruction and multipath effects is the main source of spatial discontinuity. This discontinuity increases with the increase of the geometric distance between spatial points. Therefore, using the three-dimensional Euclidean distance as the main variable of the variogram can effectively capture the spatial autocorrelation structure of the attenuation field in the radar coordinate system. To further improve the interpolation accuracy, azimuth and elevation angles can be optionally introduced as auxiliary variables when constructing the variogram to construct anisotropic or partitioned variograms.

[0035] The specific process for acquiring real-time ship AIS data is as follows: taking the geographical coordinates of the high-rise building at sea as the center, a ring-shaped AIS data acquisition area is pre-set with the high-rise building at sea as the center and the radius value being twice the effective detection range of the radar. The shore-based AIS base station network covering the acquisition area and satellite AIS data services are accessed simultaneously to form a multi-source complementary AIS data acquisition system, ensuring continuous coverage and data acquisition of ship targets within the acquisition area.

[0036] It should be noted that the 2 times is a preferred embodiment based on the navigation density and regulatory requirements of the sea area. In practical applications, this multiple can be adjusted adaptively according to actual requirements.

[0037] After receiving multi-source AIS data streams in real time, the data is first preprocessed, including message format parsing, cyclic redundancy check, and timestamp synchronization.

[0038] Subsequently, the verified AIS messages are decoded to extract and associate key dynamic and static information of each vessel. The dynamic information includes at least the vessel's unique MMSI identifier, real-time latitude and longitude coordinates, ground speed, ground heading, and message timestamp. The static information may optionally include vessel type, length, and beam.

[0039] Finally, the decoded data undergoes deduplication, error correction, and track smoothing, and is then structured and stored according to time series and spatial location to generate a standardized real-time ship AIS data stream.

[0040] It should be noted that, in order to deal with occasional AIS signal loss or data interruption, a track inference algorithm can also be integrated. During the short period of no AIS update, the short-term position prediction can be made based on the ship's last known speed and heading until a new valid AIS message is received, thereby maintaining the continuity of the ship's track and improving the reliability of monitoring.

[0041] Reference Figure 2 As shown in Figure S2, a spatial coordinate grid is established based on the detection effectiveness attenuation field. Each grid is used as a spatial unit to extract the radar signal attenuation value, the spatial change gradient of the signal attenuation, and the distance-height ratio with the tall object. Through normalization and nonlinear transformation, the difference between the maximum and minimum values ​​of the three nonlinear transformation results is taken as the radar interference risk.

[0042] The specific process of establishing the spatial coordinate grid is as follows: First, a planar coordinate system is established with the fixed geographic coordinates of the radar as the spatial reference origin; then, the three-dimensional spatial boundary data that characterizes the radar's detection capability affected by tall objects in the detection effectiveness attenuation field is read, and its projection range on the horizontal plane is extracted.

[0043] Based on this projection range, the maximum and minimum coordinate values ​​of the grid in the east-west and north-south directions are determined, thereby defining a rectangular horizontal region that can completely contain the projection range.

[0044] The geometric center of the rectangular horizontal region is aligned with the radar geographic coordinate reference point, and its boundary range is determined by the outer extent of the attenuation field spatial boundary on the horizontal plane.

[0045] It should be noted that the choice of using the radar's geographical coordinates as the reference is based on the spatial consistency requirement that the radar detection effectiveness attenuation field is calculated with the radar phase center as the ray emission origin. Therefore, establishing a spatial coordinate grid based on these coordinates can ensure that the grid cells and the attenuation field data are strictly aligned in space, providing a direct coordinate correspondence for the subsequent extraction of the radar signal comprehensive attenuation factor of each spatial coordinate grid.

[0046] Determining the horizontal coverage range by combining the spatial boundary of the detection effectiveness attenuation field enables the grid to completely cover all sea areas that may be at risk of radar interference, avoiding omissions in the analysis and thus ensuring the comprehensiveness and reliability of subsequent risk assessment and protection zone delineation.

[0047] This invention establishes a unified spatial coordinate grid and synchronously quantifies multi-source heterogeneous risk factors such as radar signal attenuation, spatial gradient changes, ship density, and encountered threats. This achieves the integrated fusion of radar detection characteristics and traffic dynamics, overcomes the limitations of a single criterion, and effectively improves the comprehensiveness of risk assessment.

[0048] The horizontal resolution is set based on the azimuth beamwidth of the radar. To ensure that the grid can effectively distinguish the main lobe structure of the radar azimuth beam and its spatial variation after obstruction, the horizontal resolution should meet the following requirements: The constraints, among which For the typical analysis distance of interest, in practice, depending on the required level of precision, the arc length corresponding to the azimuth beamwidth at the specified distance can be divided equally or a specific ratio can be taken to determine a fixed value. For azimuth beamwidth, This refers to the horizontal resolution.

[0049] For example, the arc length corresponding to the beamwidth can be divided into ten equal parts, that is, the horizontal resolution can be... This enables effective sampling of the beam structure.

[0050] The specific process for determining the number of vertical layers and the layer thickness is as follows: First, determine the total vertical height range that needs to be covered. Its lower limit is sea level, and its upper limit is the greater of the top height of the towering object at sea and the maximum pitch coverage height of the radar beam.

[0051] Secondly, based on the radar vertical beam To characterize the vertical shading effect of structures and tall buildings with sufficient precision, a basic vertical layer thickness is defined. The vertical layer thickness is typically associated with the height range covered by the radar's vertical beamwidth over a certain distance; for example, it can be set to... ,in It is an integer greater than 1, and its specific value is set according to actual requirements to ensure that there are enough sampling points in the vertical direction.

[0052] Finally, the number of vertical layers Through calculation N is obtained, where The function is rounded up. This results in a structure with uniform thickness extending upwards from sea level. of A vertical layer.

[0053] Within the defined horizontal coverage area, using the radar's geographical coordinates as the reference origin, a projection plane coordinate system along the latitude and longitude directions is established according to a set horizontal resolution. This generates a grid array with equal spacing in both row and column directions. Each grid point corresponds to a horizontal position, and all grid points together form a two-dimensional planar grid covering the target sea area.

[0054] The two-dimensional planar grid is expanded in layers along the vertical direction to form multiple layers of three-dimensional spatial units, each of which is uniquely identified by its horizontal position index and vertical layer index.

[0055] It should be noted that the attenuation of radar detection effectiveness is not uniformly distributed in the vertical direction. It is affected by tall objects blocking the beam and the vertical directionality. In addition, the collision risk and radar interference faced by ships at different navigation altitudes are also different. By vertical layering, a three-dimensional spatial analysis framework can be established to finely characterize the distribution characteristics of risk in the height dimension.

[0056] Each three-dimensional spatial unit is uniquely identified by its horizontal grid row and column number and its vertical layer number.

[0057] For each spatial cell in the three-dimensional spatial coordinate grid, based on the three-dimensional coordinates of its center point, the radar signal comprehensive attenuation factor at the center point of the cell is calculated from the discrete sample points of the attenuation field using the interpolation method of the Kriging algorithm described above in the continuous three-dimensional detection effectiveness attenuation field.

[0058] The attenuation factor calculated by the interpolation above is stored and associated as the attribute value of the spatial cell. After traversing all spatial cells and assigning values, a three-dimensional spatial coordinate mesh is generated.

[0059] It should also be noted that the volume of the spatial unit of the spatial coordinate grid is determined based on the typical dimensions of ships when sailing in water. Specifically, the volume is determined by statistically analyzing the mode of the height above water and draft of ships in the target sea area, combined with the statistical characteristics of their length and width above water, to determine the physical scale of the spatial unit in the horizontal and vertical directions.

[0060] In a preferred embodiment of the present invention, the specific steps for determining the radar interference risk are as follows: for each spatial cell in the spatial coordinate grid, extract the radar signal comprehensive attenuation factor corresponding to the spatial cell, and calculate the signal attenuation spatial variation gradient of the spatial cell in three-dimensional space by combining the radar signal comprehensive attenuation factors of its adjacent spatial cells.

[0061] The calculation process of the spatial variation gradient of signal attenuation is as follows: based on the index position of the spatial unit in the three-dimensional grid, obtain the radar signal comprehensive attenuation factor corresponding to its adjacent spatial units in the six directions of front, back, left, right, up, and down.

[0062] By calculating the difference in attenuation factor between the spatial cell and its adjacent cells, and dividing it by the grid spacing in the corresponding direction, the partial derivative components in the three coordinate axes are obtained.

[0063] Finally, the three partial derivative components are combined into a three-dimensional gradient vector at the spatial unit, and the magnitude of this vector represents the strength of the spatial gradient of signal attenuation.

[0064] Using the base coordinates of the towering object at sea as the origin, calculate the horizontal projection distance between the three-dimensional coordinates of the center point of the spatial unit and the origin.

[0065] Calculate the relative height difference between the altitude of the center point of the space unit and the altitude of the radar antenna.

[0066] Divide the horizontal projection distance by the relative height difference to obtain the distance-height ratio of the spatial unit. The horizontal projection distance is calculated in the horizontal plane, and the relative height difference is taken as the absolute value.

[0067] In this embodiment, the base point coordinates of the towering object at sea are selected as the calculation origin in order to establish a unified spatial geometric benchmark with the towering object itself as a reference. The distance-height ratio is a dimensionless parameter. The smaller the value, the closer the spatial unit is to the towering object in terms of horizontal distance, and the lower it is in terms of vertical height relative to the radar antenna.

[0068] By introducing the range-to-height ratio, the three-dimensional spatial geometric relationship between spatial units and tall objects is incorporated into the quantification system of radar interference risk. This allows the risk assessment to be based not only on the absolute value and local changes of signal attenuation, but also on the fundamental geometric structural factors that cause the attenuation.

[0069] By traversing all spatial cells in the spatial coordinate grid, the minimum and maximum values ​​of the three characteristics—the radar signal comprehensive attenuation factor, the spatial variation gradient of signal attenuation, and the range-altitude ratio—are determined within the entire spatial range.

[0070] Calculate the difference between the original value and the global minimum value, then divide this difference by the difference between the global maximum value and the global minimum value to convert it to a standard interval.

[0071] The normalized feature values ​​are input into a preset nonlinear transformation function, and the range of the three nonlinear transformation results is calculated and determined as the radar interference risk.

[0072] It should be noted that the nonlinear transformation and range calculation process specifically involves: transforming each feature value to the standard interval by inputting it into a preset monotonically increasing nonlinear function for transformation. This function can be a sigmoid function, an exponential function, or a power function.

[0073] It should also be noted that this invention uses the range as a measure of radar interference risk. The purpose is to comprehensively reflect the internal inconsistency and overall fluctuation level of radar interference risk within a spatial unit by quantifying the dispersion of three key characteristics after nonlinear standardization and transformation. A larger range indicates a more significant synergistic difference among the attenuation factor, spatial gradient, and range-altitude ratio, suggesting a more complex and unstable radar detection environment, thus corresponding to a higher overall interference risk. Conversely, a smaller range indicates relatively consistent values ​​for the three characteristics, a relatively uniform and stable radar detection environment, and a lower overall interference risk. This method overcomes the limitations of single-feature evaluation, achieving a comprehensive quantification of the nonlinear synergistic effects of multi-dimensional interference factors, enabling the risk assessment results to more comprehensively and sensitively reflect the complexity and uncertainty of the actual electromagnetic environment.

[0074] S3. Based on real-time ship AIS data, calculate the real-time ship density of each spatial unit, and the encounter threat value for all ships based on the aggregation of the nearest encounter time and distance, thereby determining the risk of maritime conflict.

[0075] The calculation process for the real-time ship density is as follows: within a preset time window, the real-time ship AIS data stream is traversed to obtain the real-time latitude and longitude coordinates and heading information of each ship.

[0076] The preset time window is set based on the characteristics of the typical speed and the duration of stable course speed of ships in the target sea area based on historical navigation data analysis. For example, in open water, ships usually maintain course speed for several minutes to tens of minutes, so the preset time window can be set in the range of 5 to 15 minutes.

[0077] Based on the geographical coordinate system of the location of the tall objects at sea, the real-time latitude and longitude coordinates of each ship are converted into horizontal projected coordinates consistent with the spatial coordinate grid, and then mapped to the corresponding horizontal spatial cells in the spatial coordinate grid.

[0078] Since the spatial coordinate grid is constructed on a specific projection plane based on radar geographic coordinates, the planar coordinates of its grid cells and the latitude and longitude coordinates belong to different coordinate systems. Therefore, the real-time latitude and longitude coordinates of each ship must be converted into horizontal projected coordinates under the same projection plane and the same unit of measurement as the spatial coordinate grid through geographic information conversion algorithms or function libraries.

[0079] After obtaining the horizontal projected coordinates of the ship, the row offset and column offset of the coordinate point relative to the grid origin are calculated based on the horizontal coverage origin coordinates and horizontal resolution of the spatial coordinate grid. These two offsets are then divided by the horizontal resolution and rounded to obtain the row index and column index of the horizontal spatial unit to which the ship belongs.

[0080] Within the preset time window, the total number of ships mapped to that specific horizontal spatial unit is calculated after deduplication. The horizontal area of ​​the horizontal spatial unit is directly determined by the preset horizontal resolution of the spatial coordinate grid. In the projected plane coordinate system, this area is usually a fixed value, for example, when the horizontal resolution is... and At that time, its horizontal area is Multiply .

[0081] Divide the total number of ships obtained from the statistics by the horizontal area of ​​the spatial unit to get the number of ships per unit area, i.e., the real-time ship density.

[0082] In a preferred embodiment of the present invention, the process of calculating the encounter threat value is as follows: traverse all ships located in the real-time ship AIS data acquisition area, and determine the nearest encounter distance and nearest encounter time of any two ships within a preset time period based on their real-time position coordinates, ground speed and ground heading, thereby calculating the potential collision threat value of each ship pair.

[0083] The preset duration is a forward-looking time interval, such as the next 6 minutes. Based on the real-time motion status of the two ships, assuming that they maintain their current ground speed and course at a constant speed within the preset duration, the relative motion vectors of the two ships are calculated through vector analysis based on their real-time positions, speeds and course vectors. This determines the nearest encounter distance between the predicted tracks of the two ships and the nearest encounter time required to reach that nearest encounter distance point.

[0084] The potential collision threat value is obtained by multiplying the reciprocal of the nearest encounter distance by the reciprocal of the nearest encounter time. The closer the predicted nearest encounter distance between the two ships and the shorter the time to reach that nearest point, the greater the calculated potential collision threat value, thus directly and quantitatively characterizing the urgency of the collision.

[0085] Considering that collision risk is not limited to the precise meeting point but gradually decreases with increasing distance from the meeting point, a distance attenuation rule is introduced to correct the original threat value. Specifically, for each affected horizontal spatial unit, the Euclidean distance between its center point and the predicted meeting point is calculated. Based on the Euclidean distance, an attenuation coefficient is calculated using a monotonically decreasing function, such as an inverse distance weighting function or an exponential attenuation function. The original potential collision threat value of the ship pair is multiplied by this attenuation coefficient to obtain the corrected threat contribution value assigned to that specific spatial unit; the closer the distance, the larger the attenuation coefficient and the higher the assigned contribution value; conversely, the farther the distance, the lower the contribution value.

[0086] It should be noted that using the exponential decay function can more sharply concentrate the threat near the meeting point, which is suitable for emphasizing the core risk area; while using the inverse distance weighting function makes the threat distribution smoother, which is suitable for describing the broad impact of the risk.

[0087] By iterating through all horizontal spatial cells that may be affected by the encounter event, the corrected threat contribution value calculated according to the above rules is added to the cumulative threat value of the corresponding spatial cell. By repeating this process for all ship pairs, each horizontal spatial cell will eventually obtain an encounter threat value.

[0088] In a preferred embodiment of the present invention, the specific steps for determining the maritime conflict risk are as follows: receiving the real-time ship density value and the comprehensive encounter threat value of each spatial unit, and standardizing the two values ​​using the same extreme value normalization method to obtain the corresponding standardized density factor and threat factor.

[0089] A two-dimensional risk space is constructed using the standardized density factor and threat factor as two orthogonal dimensions. A theoretical minimum risk point is defined in this space as an evaluation benchmark. This theoretical minimum risk point corresponds to the minimum risk state that can be theoretically achieved in the two dimensions. After normalization, the coordinates of the benchmark point are set to (0, 0), which corresponds to the theoretical ideal state in which there is no ship activity in the area and no ship is threatened.

[0090] For each spatial unit, the Euclidean distance between its corresponding coordinate point in the two-dimensional risk space and the theoretical minimum risk point is used as a comprehensive distance index. This comprehensive distance index comprehensively characterizes the extent to which the unit deviates from the theoretical safest state in terms of both ship density and encountered threats.

[0091] The comprehensive distance index is linearly scaled to a range of risk values ​​that are continuously distributed from the theoretical minimum to the theoretical maximum, and this range is used as the maritime conflict risk for that spatial unit.

[0092] The theoretical minimum value is 0, corresponding to the theoretical lowest risk point itself; the theoretical maximum value is determined based on the extreme case of the normalization interval upper limit of 1 corresponding to the two standardization factors, by calculating the Euclidean distance from the two-dimensional coordinate point (1,1) to the origin (0,0), and its value is... Therefore, the theoretical range of variation for the comprehensive distance index is [0, ...]. ].

[0093] The comprehensive distance index of each spatial unit is mapped to a preset continuous risk value range, such as [0, 100], through a linear transformation formula.

[0094] This calculation applies the theoretical range [0, ...]. Linearly and proportionally mapped to the target range [0, 100]. When the comprehensive distance index is 0, the risk value is 0; when the comprehensive distance index is... At that time, the risk value was 100.

[0095] S4. The radar interference risk and maritime conflict risk of the same spatial unit are weighted and integrated to generate a comprehensive risk. Based on the level contour lines of the comprehensive risk value, the boundaries of the graded protection area are dynamically delineated.

[0096] Reference Figure 3 As shown, the specific process of generating comprehensive risk is as follows: for each spatial unit, obtain its corresponding radar interference risk value and maritime conflict risk value.

[0097] Configure fusion weighting coefficients for the radar interference risk value and the maritime conflict risk value respectively.

[0098] Based on the aforementioned fusion weighting coefficient, the two standardized risk values ​​corresponding to the same spatial unit are linearly weighted and fused to obtain a comprehensive risk value that characterizes the overall risk level of the spatial unit.

[0099] It should be noted that the fusion weight coefficient can be set differently according to the focus of the actual application scenario. For example, the fusion weight coefficient is determined by the analytic hierarchy process, where the weight of radar interference risk is set to 0.6 and the weight of maritime conflict risk is set to 0.4. The specific weight values ​​can be dynamically adjusted according to the historical risk data of the actual sea area.

[0100] The specific steps for dynamically delineating the boundaries of graded protection zones are as follows: extract the comprehensive risk value of each spatial unit and calculate the statistical distribution of the comprehensive risk values ​​of all spatial units.

[0101] Based on the statistical distribution of the comprehensive risk value, the corresponding quantiles are selected as risk thresholds to divide the comprehensive risk value into several continuous risk value intervals.

[0102] Traverse all spatial units, compare their comprehensive risk value with the risk value range, and assign a specific risk level to each spatial unit.

[0103] Adjacent spatial units with the same risk level are aggregated to form independent regions of each risk level.

[0104] Extract the outer contour of each independent region to generate the graded protection zone boundaries corresponding to each risk level.

[0105] It should be noted that the specific implementation method of dividing risk value intervals based on quantiles is as follows: according to the preset number of protection levels, the required quantile points are determined. For example, for a three-level division, the tertiles are used for division, that is, the quantiles with cumulative probabilities of 33% and 67% in the corresponding statistical distribution. Based on the calculated comprehensive risk value statistical distribution, the specific risk threshold corresponding to the quantile points is determined.

[0106] Therefore, the global range of the comprehensive risk value is divided into three consecutive risk value intervals: the lower limit of the first risk value interval is the global minimum value among all spatial units' comprehensive risk values, and the upper limit is the risk value corresponding to the 33rd percentile of the first quantile; the lower limit of the second risk value interval is the risk value corresponding to the 33rd percentile of the first quantile, and the upper limit is the risk value corresponding to the 67th percentile of the second quantile; the lower limit of the third risk value interval is the risk value corresponding to the 67th percentile of the second quantile, and the upper limit is the global maximum value among all spatial units' comprehensive risk values.

[0107] This invention integrates radar interference risk and maritime conflict risk to generate a comprehensive risk value. By calculating risk level contour lines, it dynamically delineates graded protection boundaries, enabling the protection area to reflect the evolution of radar detection blind spots and changes in traffic flow risk accumulation in real time. This allows the protection area to be dynamically adjusted according to real-time risks, replacing the traditional fixed warning zone setting method. Under the premise of ensuring safety, it optimizes the utilization efficiency of navigation resources.

[0108] S5. Monitor vessels entering the protected area, generate navigation instructions based on their position risk level, and execute emergency avoidance instructions if there is an immediate risk of collision; otherwise, execute route optimization control.

[0109] The emergency avoidance command includes the turning angle, deceleration magnitude, and conditions for resuming course; the system monitors the ship's response, and if it fails to execute the command within the set time, it escalates the alarm level and notifies the shore-based control center.

[0110] The route optimization control specifically involves: acquiring in real time the precise position, heading to ground, and speed to ground of the vessel entering the graded protection zone, and matching the vessel's real-time position with the graded protection zone to determine the current risk level of the vessel.

[0111] Based on the vessel's preset destination, navigation mission requirements, international maritime collision avoidance rules, and specific navigation regulations of the sea area, and combined with the spatial distribution data of the generated graded protection zone boundaries, the core optimization objective is to guide the vessel to avoid higher-risk areas and prioritize passage through lower-risk protection zones. In the electronic chart environment, starting from the vessel's current position and ending at the destination or preset waypoint, multiple feasible future routes that comply with navigation rules and meet the above-mentioned risk avoidance objectives are generated through a step-by-step exploration and path construction method.

[0112] This invention dynamically generates graded protection boundaries based on fused risk values, and automatically generates route optimization or emergency avoidance commands based on the real-time position and risk level of the vessel, forming a perception-assessment-control closed loop, realizing intelligent protection from static warning to risk-driven and proactive intervention.

[0113] Each generated feasible route is evaluated using multiple indicators to select a recommended route. The evaluation indicators include at least the total distance of the route, and the turning complexity represented by the number of turning points and the cumulative turning angle. Specifically, a sequential evaluation method can be used for comprehensive comparison. In the sequential evaluation, priority should be given to ensuring that the route does not cross the highest risk restricted area. Then, among the set of routes that meet this condition, the route with the shortest total distance is selected as the recommended route. If there are multiple routes with similar distances, the route with the lowest turning complexity is further selected as the recommended route.

[0114] Based on the recommended route and combined with the ship's real-time motion status, a specific and executable sequence of course adjustment instructions and recommended speed values ​​are calculated. These instructions and recommendations are intended to guide the ship to sail along the recommended route, thereby safely and orderly gradually leaving the current high-risk area or passing through the protection zone.

[0115] Finally, the navigation instructions are sent to the target vessel via a ship AIS message.

[0116] It should be noted that if a vessel fails to leave a high-risk area within the preset time, the surrounding risks will be recalculated, and a new optimized route will be generated to avoid sending the same instructions repeatedly.

[0117] This invention effectively addresses complex risk scenarios arising from the interplay between non-uniform radar interference fields caused by the complex structure of tall buildings and the dynamic behavior of ships by introducing spatial gridding analysis, multi-feature normalization and nonlinear transformation, as well as multi-factor weighted fusion and consistency verification mechanisms.

[0118] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A radar-based method for predicting and analyzing the protection distance of tall objects at sea, characterized in that, include: Acquire detection performance attenuation field and real-time ship AIS data around tall objects at sea; Based on the detection effectiveness attenuation field, a spatial coordinate grid is established. Each grid is used as a spatial unit to extract the radar signal attenuation value, the spatial variation gradient of signal attenuation, and the distance-height ratio with tall objects. Through normalization and nonlinear transformation, the range between the three transformation results is determined as the radar interference risk. Based on real-time ship AIS data, the real-time ship density of each spatial unit is calculated, as well as the encounter threat value for all ships based on the aggregation of the nearest encounter time and distance, in order to determine the risk of maritime conflict. The radar interference risk and maritime conflict risk of the same spatial unit are weighted and integrated to generate a comprehensive risk. Based on the level contour lines of this comprehensive risk value, the boundaries of graded protection zones are dynamically delineated. The system monitors vessels entering the protected area and generates navigation instructions based on their positional risk level. If there is an immediate risk of collision, it executes an emergency avoidance instruction; otherwise, it performs route optimization control.

2. The method for predicting and analyzing the protection distance of tall marine structures based on radar technology according to claim 1, characterized in that: The specific process for obtaining the detection effectiveness attenuation field and real-time ship AIS data around tall objects at sea is as follows: The deployment parameters of the radar and a high-precision three-dimensional model of a tall object at sea are obtained. The deployment parameters include geographic coordinates, antenna height, operating frequency and beamwidth. Based on the high-precision three-dimensional model and radar beamwidth, a set of ray paths centered on the radar and intersecting with the surface of the tall object is simulated; For each ray path, the path propagation length difference is calculated by taking into account the blocking effect of the tower's geometry on the radar signal, and the radar signal comprehensive attenuation factor at the spatial point at the end of the ray path is determined based on the radar operating frequency and the reflection characteristics of the tower's surface material. Within the effective detection range of the radar, spatial interpolation is performed on all spatial points and their corresponding comprehensive attenuation factors to generate a continuous three-dimensional detection performance attenuation field. A ring-shaped AIS data collection area is defined with the tall objects at sea as the center, and the area is connected to the regional AIS base station network and satellite AIS data source to receive and parse AIS messages broadcast by ships in the area in real time. The AIS messages are decoded and verified to extract dynamic information including at least the ship's unique MMSI identifier, real-time position coordinates, ground speed, ground heading, and message timestamp, and then stored in a structured manner to form a real-time ship AIS data stream.

3. The radar-based method for predicting and analyzing the protection distance of tall marine structures according to claim 2, characterized in that: The specific process for establishing the spatial coordinate grid is as follows: Based on the geographic coordinates of the radar, and combined with the spatial boundary of the detection effectiveness attenuation field, the horizontal coverage range of the spatial coordinate grid is determined; Set the horizontal resolution and vertical number of layers of the grid, and construct a two-dimensional planar grid consisting of multiple equally spaced horizontal grid points within the horizontal coverage area; The two-dimensional planar grid is expanded in layers along the vertical direction to form multiple three-dimensional spatial units, wherein each spatial unit is uniquely identified by its horizontal position index and vertical layer index. The three-dimensional detection performance attenuation field is mapped to the three-dimensional spatial coordinate grid, and a corresponding radar signal comprehensive attenuation factor is assigned to each spatial unit to generate the spatial coordinate grid.

4. The radar-based method for predicting and analyzing the protection distance of tall marine structures according to claim 3, characterized in that: The specific steps for determining radar interference risk are as follows: For each spatial cell in the spatial coordinate grid, the radar signal attenuation factor corresponding to the spatial cell is extracted, and combined with the radar signal attenuation factor of its neighboring spatial cells, the spatial gradient of signal attenuation in three-dimensional space is calculated. Using the base point coordinates of the aforementioned tall sea structure as the origin, calculate the horizontal projection distance between the three-dimensional coordinates of the center point of the spatial unit and the origin. Calculate the relative height difference between the altitude of the center point of the spatial unit and the altitude of the radar antenna; Divide the horizontal projected distance by the relative height difference to obtain the distance-height ratio of the spatial unit; The extreme value normalization method is used to normalize the three features of radar signal integrated attenuation factor, signal attenuation spatial variation gradient and range-altitude ratio, so that the values ​​of each feature are mapped to a unified value range. The normalized feature values ​​are input into a preset nonlinear transformation function, and the range of the three nonlinear transformation results is calculated and determined as the radar interference risk.

5. The method for predicting and analyzing the protection distance of tall marine structures based on radar technology according to claim 1, characterized in that: The calculation process for the real-time ship density is as follows: Within a preset time window, the real-time ship AIS data stream is traversed to obtain the real-time latitude and longitude coordinates and heading information of each ship. Based on the geographical coordinate system of the location of the towering objects at sea, the real-time latitude and longitude coordinates of each ship are converted into horizontal projected coordinates consistent with the spatial coordinate grid, and mapped to the corresponding horizontal spatial unit in the spatial coordinate grid. Based on the total number of ships counted within the preset time window and the horizontal area of ​​the horizontal spatial unit, the real-time ship density of the horizontal spatial unit is obtained by calculating the ratio of the two.

6. The method for predicting and analyzing the protection distance of tall marine structures based on radar technology according to claim 2, characterized in that: The calculation process for the encounter threat value is as follows: Iterate through all ships located in the real-time ship AIS data acquisition area, and determine the nearest encounter distance and nearest encounter time of any two ships within a preset time period based on their real-time position coordinates, speed to ground and heading to ground, and calculate the potential collision threat value of each ship pair. Centered on the predicted meeting point of each pair of ships, the potential collision threat value is corrected according to the distance attenuation rule and allocated to the corresponding horizontal spatial unit; The combined encounter threat value for that horizontal spatial cell is obtained by summing up all threat values ​​of all ships assigned to the same horizontal spatial cell.

7. The method for predicting and analyzing the protection distance of tall marine structures based on radar technology according to claim 1, characterized in that: The specific steps for determining the risk of maritime conflict are as follows: The system receives real-time ship density and comprehensive encounter threat value from each space unit, and performs extreme value normalization processing to obtain the corresponding standardized density factor and threat factor. Using the density factor and threat factor of the same spatial unit as two-dimensional coordinate points, the theoretically lowest risk point is selected as the reference benchmark point; Calculate the Euclidean distance between the two-dimensional coordinate point and the theoretical lowest risk point as a comprehensive distance index characterizing the synergistic effect of the two factors; The comprehensive distance index is linearly scaled to a range of risk values ​​that are continuously distributed from the theoretical minimum to the theoretical maximum, and this range is taken as the comprehensive maritime conflict risk of the spatial unit.

8. The method for predicting and analyzing the protection distance of tall marine structures based on radar technology according to claim 1, characterized in that: The specific process for generating comprehensive risk is as follows: For each spatial unit, obtain its corresponding radar interference risk and maritime conflict risk; Configure fusion weighting coefficients for the radar interference risk value and the maritime conflict risk respectively; Based on the aforementioned fusion weighting coefficient, the two standardized risk values ​​corresponding to the same spatial unit are weighted and fused to obtain a comprehensive risk value that characterizes the overall risk level of the spatial unit.

9. The method for predicting and analyzing the protection distance of tall marine structures based on radar technology according to claim 1, characterized in that: The specific steps for dynamically delineating the boundaries of graded protection zones are as follows: Extract the comprehensive risk value of each spatial unit and calculate the statistical distribution of the comprehensive risk values ​​of all spatial units; Based on the quantiles of the statistical distribution, the range of comprehensive risk values ​​is divided into several risk value intervals corresponding to the number of preset protection levels; Traverse all spatial units, compare their comprehensive risk values ​​with the risk value range, and assign a specific risk level to each spatial unit; Adjacent spatial units with the same risk level are aggregated to form independent regions of each risk level. Extract the outer contour of each independent region to generate the graded protection zone boundaries corresponding to each risk level.

10. The radar-based method for predicting and analyzing the protection distance of tall marine structures according to claim 9, characterized in that: The route optimization control specifically refers to: The system acquires the real-time position, heading, and speed information of ships entering the graded protection zone and determines the risk level corresponding to their location. Based on the ship's preset destination and navigation rules, and combined with the spatial distribution of the boundaries of the graded protection zones, multiple feasible future routes are generated with the optimization goal of avoiding higher-risk areas and prioritizing lower-risk graded protection zones. The total distance and turning complexity of each feasible route are evaluated, and the route with the best overall evaluation is selected as the recommended route. Based on the recommended route, course adjustment instructions and speed suggestions are calculated to guide the vessel to gradually leave the high-risk area, and then sent to the vessel.

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