A ship anti-collision early warning method and system for a breeding water area

Abstract

The present application relates to the technical field of traffic management, and discloses a ship anti-collision early warning method and system for aquaculture waters, the method comprising: acquiring real-time position coordinate sets and sailing direction vector sets of ships in an aquaculture area, combining wave direction gradients and aquatic plant distribution density gradients to generate a dynamic environmental resistance influence coefficient, correcting an expected sailing displacement deviation according to the dynamic environmental resistance influence coefficient to obtain a target sailing path, performing space-time conflict probability matching on the target sailing path and sailing behavior characteristic parameters of adjacent ships to obtain a collision risk level, triggering a heading adaptive adjustment instruction when the collision risk level exceeds a preset threshold and feeding back the instruction to a control unit of the ship, and dynamically updating the target sailing path according to a response delay time of the control unit. The present application can solve the problems of low prediction accuracy, poor environmental adaptability, and system response lag of existing ship anti-collision early warning technologies in complex environments of aquaculture waters.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of traffic management, in particular to a ship collision prevention warning method and system for aquaculture water area. BACKGROUND

[0002] In the existing ship collision prevention warning technology, it is mainly designed for open water area or port channel, and the warning model usually judges the collision risk based on the basic dynamic parameters such as ship position, speed and heading, which lacks fine modeling of the unique environmental factors of aquaculture water area. The wave direction in aquaculture water area is changeable, and the water grass distribution is dense. These environmental factors will significantly change the actual sailing track and maneuvering performance of the ship, and the traditional method ignores the dynamic influence of wave gradient and water grass density gradient on ship sailing resistance, resulting in large prediction deviation and high false alarm rate of the warning system in complex aquaculture environment, which cannot accurately reflect the sailing state and potential collision risk of the ship in the real environment.

[0003] The existing warning method mainly uses static or semi-static track prediction model, which cannot combine with environmental resistance to correct the expected sailing displacement of the ship in real time, and also does not fully consider the influence of ship control unit response delay on path update. In the collision risk assessment link, the traditional technology usually makes a simple judgment based on geometric position overlap, lacks dynamic matching and probabilistic conflict analysis of multi-ship space-time behavior characteristics, resulting in delayed or overly conservative collision avoidance decision. After detecting the risk, only a warning prompt is given, and the closed-loop linkage with the ship control system is not realized, which cannot automatically adjust the sailing path according to the real-time environmental changes and equipment response delay, limiting the actual collision avoidance efficiency and reliability of the warning system in dynamic aquaculture water area. SUMMARY

[0004] The present application provides a ship collision prevention warning method and system for aquaculture water area, which mainly aims at the problems raised in the above background technology.

[0005] To achieve the above purpose, the present application provides a ship collision prevention warning method for aquaculture water area, which comprises:

[0006] S1, obtaining a set of real-time position coordinates and a set of sailing direction vectors of ships in the aquaculture area;

[0007] S2, generating a dynamic environmental resistance influence coefficient in combination with the wave direction gradient and the water grass distribution density gradient of the aquaculture area;

[0008] S3, correcting the expected sailing displacement deviation of the ship according to the dynamic environmental resistance influence coefficient to obtain the target sailing path of the ship;

[0009] S4, performing space-time conflict probability matching of the target sailing path with the sailing behavior characteristic parameters of adjacent ships to obtain the collision risk level of the ship.

[0010] S5, triggering the corresponding heading adaptive adjustment instruction of the ship when the collision risk level exceeds a preset threshold and feeding back to the control unit of the ship;

[0011] S6, dynamically updating the target navigation path according to the response delay time of the control unit.

[0012] Preferably, the step of obtaining the set of real-time position coordinates comprises:

[0013] The original satellite positioning signal corresponding to the ship is analyzed in space-time coordinate sequence to obtain the set of real-time position coordinates of the ship.

[0014] Preferably, the step of obtaining the set of navigation direction vectors comprises:

[0015] The ship is calibrated in navigation direction based on the set of real-time position coordinates and the attitude sensor data of the ship to obtain the navigation direction vector of the ship.

[0016] The navigation direction vector is dynamically integrated in space to obtain the set of navigation direction vectors of the ship.

[0017] Preferably, the calculation formula of the dynamic environmental resistance influence coefficient is:

[0018]

[0019] Wherein: is the dynamic environmental resistance influence coefficient, is the phase coherent intensity, is the critical entanglement coefficient, is the wave direction gradient vector, is the water grass distribution density gradient modulus, is the wave vector-heading mismatch angle.

[0020] Preferably, the step of correcting the expected navigation displacement deviation of the ship according to the dynamic environmental resistance influence coefficient to obtain the target navigation path of the ship comprises:

[0021] Generating the ideal displacement baseline of the ship based on the set of navigation direction vectors of the ship and the set of real-time position coordinates of the ship;

[0022] Adjusting the displacement component vector of the ideal displacement baseline based on the dynamic environmental resistance influence coefficient to obtain the set of corrected displacement components of the ship;

[0023] Reconstructing the navigation trajectory of the set of real-time position coordinates based on the set of corrected displacement components to obtain the target navigation path of the ship.

[0024] Preferably, the matching the target navigation path with the adjacent ship's navigation behavior characteristic parameters in time and space collision probability to obtain the collision risk level of the ship comprises:

[0025] detecting the target navigation path and the adjacent ship's navigation behavior characteristic parameters in time and space position coincidence degree to generate a set of potential conflict position points;

[0026] analyzing the set of potential conflict position points and the set of navigation direction vectors to generate a sequence of conflict occurrence probability values;

[0027] quantifying the sequence of conflict occurrence probability values to obtain the collision risk level of the ship.

[0028] Preferably, when the collision risk level exceeds a preset threshold, triggering the corresponding heading adaptive adjustment instruction of the ship and feeding back to the control unit of the ship comprises:

[0029] risk state evaluation on the collision risk level and the preset threshold to generate a risk overrun indication signal;

[0030] converting the risk overrun indication signal into the heading adjustment instruction of the ship;

[0031] converting the heading adjustment instruction into a control signal form and feeding back to the control unit of the ship.

[0032] Preferably, the dynamically updating the target navigation path according to the response delay time of the control unit comprises:

[0033] generating a set of ship's route update cycle intervals in combination with the response delay time of the control unit and the timestamp sequence of the target navigation path;

[0034] generating displacement correction components of the ship within the route update cycle interval in combination with the dynamic environmental resistance influence coefficient;

[0035] reconstructing the target navigation path through the set of displacement correction components.

[0036] Preferably, the generating displacement correction components of the ship within the route update cycle interval in combination with the dynamic environmental resistance influence coefficient comprises:

[0037] extracting time slice path points of the target navigation path within the route update cycle interval;

[0038] decomposing the resistance component influence vector of the time slice path points according to the dynamic environmental resistance influence coefficient;

[0039] calculate a displacement hysteresis compensation amount of the time slice path point in combination with the response delay time and the resistance component influence vector;

[0040] fuse the displacement hysteresis compensation amount into the real-time position coordinate set to obtain a displacement correction component of the ship.

[0041] A ship collision warning system for aquaculture waters, the system comprising:

[0042] a ship state perception module, for acquiring a real-time position coordinate set and a sailing direction vector set of a ship in an aquaculture area;

[0043] a dynamic environment modeling module, for generating a dynamic environment resistance influence coefficient in combination with a wave direction gradient and a water grass distribution density gradient of the aquaculture area;

[0044] a path planning correction module, for correcting an expected sailing displacement deviation of the ship according to the dynamic environment resistance influence coefficient to obtain a target sailing path of the ship;

[0045] a collision risk assessment module, for performing spatiotemporal conflict probability matching between the target sailing path and sailing behavior characteristic parameters of adjacent ships to obtain a collision risk level of the ship;

[0046] a warning decision and instruction generation module, for triggering a corresponding heading adaptive adjustment instruction of the ship and feeding back to a control unit of the ship when the collision risk level exceeds a preset threshold;

[0047] a path dynamic updating and compensation module, for dynamically updating the target sailing path according to a response delay time of the control unit.

[0048] Compared with the prior art, the present application has the following beneficial effects:

[0049] The present application significantly improves the precision of ship path prediction and the reliability of warning in complex aquaculture environments. By introducing the wave direction gradient and the water grass distribution density gradient, the dynamic environment resistance influence coefficient is constructed, realizing the quantitative modeling of the unique fluid dynamics and vegetation obstruction effect of aquaculture waters. The expected sailing displacement deviation of the ship can be corrected in real time and accurately, and a target sailing path closer to the actual motion state is generated. Compared with the traditional warning model relying only on position and heading, the problem of trajectory prediction distortion and high false alarm rate caused by ignoring environmental resistance is effectively overcome, providing a real and reliable trajectory input for collision risk assessment.

[0050] The intelligent, self-adaptive and high-response closed-loop collision avoidance control is realized. The time-space conflict probability matching mechanism is adopted for collision risk quantitative evaluation, which can finely identify the potential time-space conflict points among multiple ships and generate risk levels. Once the limit is exceeded, the heading self-adaptive adjustment instruction is automatically triggered and issued, forming a closed loop of perception-evaluation-decision-control. The response delay time of the ship control unit is innovatively considered, and the target navigation path is dynamically updated and compensated accordingly, effectively offsetting the safety margin loss caused by the instruction execution lag, ensuring the timeliness, adaptability and overall reliability of the whole early warning and collision avoidance control loop in the dynamic environment, and greatly improving the safety and collaborative efficiency of multi-ship operation in the aquaculture water area. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 A flowchart of a ship anti-collision early warning method in an aquaculture water area provided by an embodiment of the present application is shown in the figure.

[0052] Figure 2 A functional module diagram of a ship anti-collision early warning system in an aquaculture water area provided by an embodiment of the present application is shown in the figure.

[0053] The object implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0054] It should be understood that the specific embodiments described herein are only used to explain the present application and not to limit the present application.

[0055] The present application embodiment provides a ship anti-collision early warning method in an aquaculture water area. The execution subject of the ship anti-collision early warning method in the aquaculture water area includes but is not limited to at least one of electronic devices such as a server, a terminal, etc. which can be configured to execute the method provided by the present application. In other words, the ship anti-collision early warning method in the aquaculture water area can be executed by software or hardware installed in a terminal device or a server device. The server includes but is not limited to a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be a stand-alone server, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content distribution networks, and big data and artificial intelligence platforms, etc. basic cloud computing services.

[0056] Referring to Figure 1 A flowchart of a ship anti-collision early warning method in an aquaculture water area provided by an embodiment of the present application is shown in the figure. In this embodiment, the ship anti-collision early warning method in the aquaculture water area includes:

[0057] S1, obtaining a real-time position coordinate set and a navigation direction vector set of a ship in an aquaculture area;

[0058] The obtaining of the real-time position coordinate set comprises:

[0059] The original satellite positioning signal corresponding to the ship is analyzed in time and space coordinate sequence to obtain the real-time position coordinate set of the ship.

[0060] The obtaining of the set of sailing direction vectors comprises:

[0061] The sailing direction of the ship is calibrated based on the real-time position coordinate set and the attitude sensor data of the ship to obtain the sailing direction vector of the ship.

[0062] The sailing direction vector is dynamically integrated in space to obtain the set of sailing direction vectors of the ship.

[0063] Specifically, the aquaculture area refers to a specific water area where aquaculture activities are carried out. The area environment is complex, usually with fixed aquaculture facilities, relatively narrow and irregular waterways, and high requirements for the accuracy of the ship's sailing trajectory.

[0064] Specifically, the ship refers to various water vehicles that carry out activities such as operation, inspection, transportation, etc. in the aquaculture area.

[0065] Specifically, the real-time position coordinate set is a data set, each element of which represents the accurate spatial position of the ship in the earth coordinate system at a certain specific time, usually in the form of latitude and longitude. The set is a sequence arranged in chronological order, dynamically reflecting the trajectory of the ship moving over time.

[0066] Further, the specific steps for obtaining the real-time position coordinate set of the ship by analyzing the original satellite positioning signal corresponding to the ship in time and space coordinate sequence are as follows:

[0067] First, signal reception is performed. The positioning receiving unit installed on the ship continuously captures the original satellite positioning signal transmitted from the global navigation satellite system. These signals are unprocessed radio waves containing satellite ephemeris, time stamps, and ranging codes, etc.

[0068] Subsequently, signal decoding and measurement are performed. The internal circuit and processing unit of the receiver demodulate and decode the original satellite positioning signal to extract the available ranging information and satellite orbit and clock parameters.

[0069] Then, position calculation is performed. The processing unit uses navigation algorithms to calculate the spatial three-dimensional coordinates of the phase center of the receiver antenna at a certain time using the ranging information of multiple satellites. This process is the core of time and space coordinate analysis, which binds a high-precision time tag to each coordinate point, and the latitude and longitude coordinates calculated.

[0070] Finally, sequence generation and output, the continuously calculated, with timestamped coordinate points, in chronological order to arrange, cache and format, form a standardized data stream for subsequent software modules directly read and process. This ordered data stream is the real-time position coordinate set. In the context of aquaculture waters, this process needs to have high update rate and anti-multipath interference ability to deal with complex water surface reflection environment, to ensure the continuity and reliability of the position data.

[0071] Overall, the action of obtaining real-time position coordinate set, in essence, is to convert the physical signals transmitted by satellites into structured data describing the accurate and time-sequenced position information of the ship in the aquaculture waters through a series of electronic and digital signal processing steps. It is the cornerstone of the entire early warning system to perceive the physical existence of the ship, providing the most fundamental input for judging whether the ship deviates from the safety area, calculating the relative distance and predicting the future position.

[0072] Specifically, the sailing direction vector is a vector that indicates the direction of the ship's bow. Its magnitude can also represent the speed or be used for standardization. It describes the instantaneous motion direction of the ship in the horizontal plane.

[0073] Specifically, attitude sensor data refers to the raw physical quantity data collected directly by sensors such as inertial measurement units, electronic compasses, and gyroscopes carried by the ship. These data may include three-axis acceleration, three-axis angular velocity, and three-axis magnetic field strength, reflecting the attitude changes and rotation rates of the ship body.

[0074] Specifically, the sailing direction vector set is a data collection composed of multiple sailing direction vectors in chronological order. It records the continuous changes in the ship's heading over a period of time, reflecting the ship's maneuvering dynamics and trends better than a single direction value.

[0075] Further, the sailing direction calibration of the ship based on the real-time position coordinate set and the attitude sensor data of the ship to obtain the sailing direction vector of the ship includes the following specific steps:

[0076] First, multi-source data synchronization, align the real-time position coordinate set and attitude sensor data of the same time period in time, to ensure that both describe the state of the ship at the same time.

[0077] Then, preliminary heading generation, from the attitude sensor data, through electronic compass data directly or combined with gyro data for data fusion, to obtain a preliminary ship heading angle.

[0078] Next, from the real-time position coordinate set, by calculating the direction of the line between two or more consecutive position coordinate points, another displacement-based heading reference can be obtained.

[0079] Finally, calibration and fusion. In aquaculture waters, the ship may be pushed by waves and currents, causing the ship to slide sideways, and the bow direction may not be consistent with the actual moving direction. The core of the navigation direction calibration action is to compare and fuse the two kinds of heading information.

[0080] For example, when the ship sails at a constant speed in a straight line, the position calculation track is reliable; when the ship maneuvers, the attitude sensor responds faster. The system determines which signal is more reliable through an algorithm, or corrects the deviation of the sensor heading, and finally outputs a more accurate and stable navigation direction vector. This solves the problem of relying solely on the magnetic compass, which may be disturbed by the metal of the aquaculture facility, or relying solely on the GPS track, which is not accurate at low speed and high maneuverability.

[0081] Further, the specific steps of dynamically integrating the navigation direction vector to obtain the navigation direction vector set of the ship are:

[0082] Vector buffer. The system opens a data buffer area to store the calibrated navigation direction vector generated continuously in the last step in chronological order.

[0083] Space-time association. Each cached vector is bound with its corresponding generation timestamp and real-time position coordinates at that moment to form a time-position-direction trinity data point.

[0084] Set construction. Over time, these bound data points are continuously added to the sequence to form an ordered, historical and current combined navigation direction vector set. This set not only contains the current direction, but also retains the direction change history of the past short period of time.

[0085] In summary, the acquisition of the navigation direction vector set is a process of multi-sensor information fusion and space-time integration. It eliminates the limitations of a single sensor through calibration and obtains more robust ship heading information in the complex electromagnetic and motion environment of aquaculture waters. The set dynamically depicts the ship's maneuvering intention and motion trend, and is a key dynamic parameter indispensable for predicting the ship's future path, analyzing the relative motion relationship between ships, and judging whether there is a conflict situation such as crossing and head-on. Without accurate heading, any position-based collision warning will lose its foresight.

[0086] S2, combining the wave direction gradient and the density gradient of the aquatic plants in the aquaculture area to generate a dynamic environmental resistance influence coefficient;

[0087] The calculation formula of the dynamic environmental resistance influence coefficient is:

[0088]

[0089] wherein: is the dynamic environmental resistance influence coefficient, is the phase coherence intensity, is the critical entanglement coefficient, is the wave direction gradient vector, is the water grass distribution density gradient modulus, is the wave vector-course mismatch angle.

[0090] In particular, the wave direction gradient vector is a vector that describes the rate and direction of change of the wave propagation direction on the surface of the aquaculture water area in space. In the aquaculture area, due to changes in the wind field, the blocking and reflection of the aquaculture facilities, the wave direction is often not uniform, and can be sharply deflected in local areas. This vector characterizes the possible changes in the dominant wave direction that the ship may encounter when moving from the current position to the adjacent area.

[0091] In particular, the water grass distribution density gradient modulus is a scalar that represents the degree of change in the water grass distribution density in the aquaculture water area in space. In the aquaculture area, water grass can be distributed in patches or strips, with significant differences in density. High-density water grass areas will produce significant entanglement resistance and friction resistance to the ship's propeller and hull. The size of this modulus reflects the potential strength of the change in water grass resistance on the ship's navigation path.

[0092] In particular, the wave vector-course mismatch angle is the angle between the ship's navigation direction vector and the local main wave propagation direction indicated by the local wave direction gradient vector. This angle determines whether the wave produces a downstream push, a lateral oscillation, or an upstream resistance to the ship.

[0093] More specifically, for example, head-on When sailing at an angle close to 180 degrees or oblique head-on, the resistance experienced by the ship increases significantly.

[0094] In particular, the phase coherence intensity is an empirical coefficient related to the characteristics of the environmental wave field, reflecting the degree of concentration or order of wave energy in space. In the aquaculture area, regular, long-crested waves have a higher coherence intensity and a more predictable impact on ships; while the broken waves and chaotic waves formed by the aquaculture facilities have a lower coherence intensity and produce more random disturbances.

[0095] In particular, the critical entanglement coefficient is an empirical coefficient related to the physical characteristics of the water grass, used to adjust the sensitivity of the water grass density gradient to resistance. It comprehensively reflects the characteristics of the water grass, such as species, length, and toughness. Different characteristics of water grass have different entanglement abilities when entangling the propeller or attaching to the hull, and different thresholds for the loss of ship power.

[0096] Specifically, the dynamic environmental resistance impact coefficient is the output result of this step, which is a dimensionless coefficient ranging from (0, 1]. This coefficient quantifies the overall environmental resistance impact degree at the current time, the ship's location, and the heading.

[0097] More specifically, for example, The closer the value is to 0, the greater the environmental resistance impact, and the more significant the actual displacement of the ship compared to the ideal displacement. The closer the value is to 1, the smaller the environmental resistance impact.

[0098] Further, the specific steps for generating the dynamic environmental resistance impact coefficient in combination with the wave direction gradient and the water grass distribution density gradient of the cultivation area are as follows:

[0099] Environmental data is synchronously collected, and real-time environmental monitoring data of the cultivation area is obtained in parallel by the system. The spatial and temporal sequence data of wave height and direction are obtained through the deployment of wave radar and buoy sensor array in the cultivation area; the density data of water grass distribution are obtained through underwater acoustic detection, optical remote sensing, or a pre-set aquatic environment monitoring network. These data are spatio-temporally aligned with the real-time position coordinates and heading vector of the ship.

[0100] Gradient field calculation: based on the obtained wave direction spatio-temporal data, the distribution of wave direction is calculated within a neighborhood space around the current position of the ship, and then the wave direction gradient vector at this position is obtained by spatial differentiation or fitting method.

[0101] Based on the obtained water grass density distribution data, the spatial variation rate of water grass density is calculated within the same spatial range, and the absolute value of the spatial variation rate is taken to obtain the water grass distribution density gradient modulus.

[0102] Mismatch angle calculation: according to the heading vector of the current ship and the principal wave direction implied by the local wave direction gradient vector calculated in the previous step, the included angle between them, i.e., the wave vector-heading mismatch angle, is calculated.

[0103] Table lookup or empirical parameter calling: based on the historical observation data of the cultivation water area and the fluid mechanics characteristics of the ship, the numerical values of the phase coherence intensity and the critical entanglement coefficient are determined in advance or fine-tuned online.

[0104] Coefficient synthesis calculation: the above calculated , , , , are substituted into the given mathematical relationship for calculation. The formula structure embodies the following physical logic: the nonlinear influence of wave gradient, which is The quadratic amplification effect of item adjustment, water grass density gradient and the coupling of heading-wave angle, and finally through the exponential function mapping to a smooth, normalized resistance influence coefficient

[0105] Output dynamic coefficient: the calculated dynamic environmental resistance influence coefficient Output, as the key input for the next step of path correction. This coefficient is a dynamic value, which is updated in real time with the changes of ship position, heading and environmental field.

[0106] In general, the complex wave and water grass combined resistance effect in the aquaculture area, which is difficult to measure directly, is converted into a calculated coefficient closely related to the ship state , which is not a simple resistance value, but a measure of the deviation of the environment on the expected motion of the ship. Its generation enables the early warning system to first quantitatively understand and predict the degree of interference the environment will have on the ship, laying an irreplaceable environmental dynamics foundation for subsequent high-precision path prediction and risk judgment.

[0107] Without this step, any effective early warning model in open waters will fail in the complex environment of the aquaculture area.

[0108] S3, correcting the expected sailing displacement deviation of the ship based on the dynamic environmental resistance influence coefficient to obtain the target sailing path of the ship;

[0109] The expected sailing displacement deviation of the ship is corrected based on the dynamic environmental resistance influence coefficient to obtain the target sailing path of the ship, comprising:

[0110] Generating an ideal displacement baseline of the ship based on a set of sailing direction vectors of the ship and a set of real-time position coordinates of the ship;

[0111] Adjusting the ideal displacement baseline based on the dynamic environmental resistance influence coefficient to obtain a set of corrected displacement components of the ship;

[0112] Reconstructing the sailing trajectory based on the set of corrected displacement components to obtain the target sailing path of the ship.

[0113] Specifically, the expected sailing displacement deviation refers to the difference between the actual displacement of the ship in the future period of time under the influence of the complex environmental resistance in the aquaculture area and the displacement that should be produced along the current heading in an ideal calm and unobstructed water area. This deviation is a vector, which has both the distance of shortening or deviation and the direction.

[0114] Specifically, the target sailing path is a continuous trajectory composed of a series of predicted position coordinates at future time points. It is not the planned route of the ship, but the path that the ship is most likely to actually travel after fully considering the impact of real-time dynamic environmental resistance. This path is the direct basis for subsequent collision risk assessment.

[0115] Specifically, the ideal displacement baseline is a theoretical displacement vector sequence or continuous trajectory. It is generated under a hypothetical condition, i.e., ignoring all environmental resistance such as waves, water grass, strong currents, etc., and assuming that the ship can move freely in the aquaculture water area according to its current sailing direction vector and power performance. It represents the ideal maneuvering capability or driving intention of the ship.

[0116] Specifically, the set of modified displacement components is a set of displacement vectors after adjustment. Each modified displacement component in it is the result of applying the modification rule represented by the dynamic environmental resistance impact coefficient to the displacement vector of the corresponding period or point in the ideal displacement baseline. It quantifies the expected deviation caused by environmental resistance.

[0117] Specifically, the sailing trajectory reconstruction refers to the process of constructing a continuous and smooth future spatial trajectory from a known starting point using a series of displacement vectors through vector accumulation or path integration.

[0118] Further, the specific steps for generating the ideal displacement baseline of the ship based on the set of sailing direction vectors of the ship and the set of real-time position coordinates of the ship are:

[0119] State extrapolation: Taking the set of sailing direction vectors at the current and recent historical time as the main input, and combining the ship's dynamics model such as typical speed, acceleration and deceleration performance, and turning rate, the ship's motion state in a short time domain in the future, such as 30 seconds to 2 minutes, is predicted. This process does not involve environmental resistance calculation, but is based only on the ship's own maneuvering characteristics and current motion trend.

[0120] Baseline generation: The motion state predicted in the previous step, mainly the speed and direction, is converted into corresponding displacement vectors. Then, taking the latest real-time position coordinate as the starting point, these displacement vectors are connected in time sequence to form a theoretical trajectory line or displacement vector sequence extending from the current point to the future, i.e., the ideal displacement baseline. It describes how the ship wants to go or how the ship will go in a vacuum.

[0121] Further, the specific steps for adjusting the displacement component vectors of the ideal displacement baseline based on the dynamic environmental resistance impact coefficient to obtain the set of modified displacement components of the ship are:

[0122] Resistance influence mapping: mapping the dynamic environmental resistance influence coefficient to each predicted time point or each segment of the ideal displacement baseline. Since the dynamic environmental resistance influence coefficient is a function of position and heading, the corresponding dynamic environmental resistance influence coefficient value needs to be determined according to the position of each predicted point on the baseline and the predicted heading at that point.

[0123] Vector adjustment operation: for each original displacement vector in the ideal displacement baseline, apply the adjustment rule based on its corresponding dynamic environmental resistance influence coefficient value. The core logic is that the smaller the dynamic environmental resistance influence coefficient value, the greater the degree of attenuation or deflection of the corresponding ideal displacement vector.

[0124] Furthermore, for example, an ideal forward displacement vector, in the area with the wind and dense water grass, its modulus will be significantly shortened, simulating the speed reduction caused by power loss; at the same time, its direction may also be fine-tuned due to the lateral wave push. This adjustment process is point by point and segment by segment.

[0125] The corrected displacement component set is a collection of all new displacement vectors obtained after the above adjustment operation, arranged in the original time sequence, forming the corrected displacement component set. This set contains the quantitative influence of environmental resistance on the maneuverability of the ship.

[0126] Further, the specific steps of reconstructing the sailing trajectory based on the corrected displacement component set to obtain the target sailing path of the ship are:

[0127] Determine the reconstruction starting point: the most accurate real-time position coordinate of the ship, usually the last point after filtering processing, is taken as the absolute starting point of the entire predicted trajectory.

[0128] Vector accumulation synthesis: starting from the starting point, the first corrected displacement vector in the corrected displacement component set is taken out and added to the starting point coordinate to obtain the coordinate of the first future predicted point.

[0129] Then, taking this predicted point as the new starting point, add the second corrected displacement vector to obtain the second predicted point coordinate. Recursively accumulate in this way until all displacement components in the set are processed.

[0130] Generate a continuous path: connect a series of future predicted point coordinates generated by the above accumulation with a smooth curve, such as a spline curve or a continuous line segment, to form a continuous spatial path extending from the current time to a future time. This path is the target sailing path. It is no longer an ideal theory line, but a trajectory that the ship is most likely to actually follow under the real environmental resistance of the cultivation environment.

[0131] In summary, correction and reconstruction is a physical simulation process that transforms theoretical environmental drag coefficients into high-fidelity trajectory predictions. By introducing a dynamic environmental drag influence coefficient, it discounts and deforms the ideal trajectory generated based on the ship's own dynamics, thereby simulating the real navigation effect under the combined effects of complex factors such as wave thrust, weed entanglement, etc.

[0132] In summary, the target navigation path significantly improves the realism and reliability of ship trajectory prediction in the specific scenario of aquaculture waters. This allows subsequent collision risk assessments to move from an idealized judgment of where the ship should be to a realistic assessment of where the ship is likely to be. This fundamentally solves the core shortcomings of traditional methods, which suffer from low prediction accuracy and high false alarm rate due to neglecting the influence of environmental dynamics, and lays an accurate trajectory data foundation for reliable early warning.

[0133] S4. Perform spatiotemporal conflict probability matching between the target navigation path and the navigation behavior characteristic parameters of adjacent vessels to obtain the collision risk level of the vessel.

[0134] The step of performing spatiotemporal conflict probability matching between the target navigation path and the navigation behavior characteristic parameters of adjacent vessels to obtain the collision risk level of the vessels includes:

[0135] Spatiotemporal position overlap detection is performed on the target navigation path and the navigation behavior characteristic parameters of adjacent vessels to generate a set of potential conflict location points;

[0136] Relative motion vector analysis is performed on the set of potential conflict locations and the set of navigation direction vectors to generate a sequence of conflict probability values;

[0137] The collision risk level of the ship is obtained by quantifying the probability value sequence of the conflict occurrence.

[0138] Specifically, adjacent vessels refer to all other vessels within the aquaculture area that are within a predetermined safety radius of the vessel. In aquaculture areas, waterways are narrow and operations are dense, making the identification of adjacent relationships the first step in risk management.

[0139] Specifically, navigation behavior characteristic parameters are a set of data used to describe the dynamic characteristics of a ship, which typically includes, but is not limited to, the real-time position coordinates of adjacent ships, the navigation direction vector set, and possibly derived information such as speed, track history, and ship type. It is a complete characterization of the motion state of adjacent ships.

[0140] Specifically, the spatio-temporal conflict probability matching is a comprehensive analysis process. Spatio-temporal refers to considering both spatial position and time dimension; conflict refers to the state that the trajectories of two ships intersect or the distance is less than a safety threshold at a certain time in the future; probability matching refers to evaluating the possibility of the occurrence of such conflict events through calculation and analysis, rather than a simple yes or no judgment.

[0141] Specifically, the set of potential conflict position points is a data set, each element of which represents a predicted point pair at a certain specific time point in the future and a certain geographic location, at which the target sailing path of the ship and the target sailing path of a neighboring ship are too close in space, i.e., the degree of coincidence exceeds the safety margin. It identifies all risk points that need to be concerned.

[0142] Specifically, the relative motion vector analysis is a vector analysis of the motion trend of the two moving objects, i.e., the ship and the neighboring ship, at the conflict point in the future. Instead of simply looking at the speed and direction of each, it analyzes the approaching speed, approaching direction, and changing trend of the relative position of each other to determine whether to cross, approach each other, or overtake in the same direction, and the degree of urgency of the approach.

[0143] Specifically, the sequence of conflict occurrence probability values is a sequence of probability values arranged in time sequence. Each value corresponds to a potential conflict position point, quantifies the possibility of an actual collision or dangerous approach event at the point, and its value is between 0 and 1. It integrates the severity of position coincidence, the urgency of relative motion, and the uncertainty of the sensor and the prediction model itself.

[0144] Specifically, the collision risk level is the final output of this step, which is an intuitive and graded risk assessment result. It maps the continuous sequence of conflict occurrence probability values, combined with time urgency, to a limited number of discrete risk levels through pre-set rules, facilitating quick understanding and response by the decision-making module.

[0145] Further, the specific steps for spatio-temporal position coincidence detection of the target sailing path and the sailing behavior characteristic parameters of the neighboring ship to generate the set of potential conflict position points are as follows:

[0146] Path synchronization extraction: the system synchronously acquires the target sailing path of the ship and the sailing behavior characteristic parameters of each neighboring ship. For a neighboring ship, its future short-time trajectory is predicted using its characteristic parameters in a manner similar to the ship.

[0147] Spatio-temporal grid comparison: the future time axis is discretized into multiple time segments. In each future time segment, the spatial distance between the predicted position of the ship and the predicted position of each neighboring ship is calculated.

[0148] Safety domain judgment: compare the spatial distance with a comprehensive safety domain radius determined by the ship size, maneuvering performance of the own ship and the neighboring ships, and the extra safety margin required by the environment of the aquaculture water area.

[0149] Conflict point identification and collection: if the distance between the predicted positions of two ships in a time slice is less than the comprehensive safety domain radius, it is determined that there is a risk of exceeding the spatio-temporal position coincidence degree at this time and at this set of spatial coordinates. The system records this time point, the predicted coordinate point of the own ship and the neighboring ship as a potential conflict position point. After traversing all neighboring ships and all future time slices, all identified conflict points are aggregated to form a set of potential conflict position points.

[0150] Further, the specific steps of performing relative motion vector analysis on the set of potential conflict position points and the set of sailing direction vectors to generate a sequence of conflict occurrence probability values are:

[0151] Motion state extraction: for each conflict point in the set of potential conflict position points, extract the predicted sailing direction vectors of the own ship and the corresponding neighboring ship at the predicted time, as well as their precise predicted positions.

[0152] Relative motion calculation: calculate the motion vector of the neighboring ship relative to the own ship, taking the own ship as the reference. This includes the magnitude and direction of the relative speed. Key calculations are whether the two ships are approaching each other, or moving in the same direction with a speed difference, or crossing each other.

[0153] Closest point of encounter and time estimation: based on the positions of the two ships and the relative motion vector, calculate the closest distance they can reach and the time required to reach this closest point.

[0154] Probability value synthesis: input factors such as spatio-temporal position coincidence, time urgency, closest distance, and uncertainty estimates of sensor and trajectory prediction into a risk assessment function. The function outputs a value between 0 and 1, which is the conflict occurrence probability value at that conflict point. Repeat this process for each conflict point in the set, and arrange these probability values in chronological order to form a sequence of conflict occurrence probability values.

[0155] Further, the specific steps of quantifying the risk level of the sequence of conflict occurrence probability values to obtain the collision risk level of the ship are:

[0156] Sequence feature extraction: analyze the sequence of conflict occurrence probability values to identify the maximum value, the duration of the probability value exceeding a certain threshold, and the time urgency corresponding to the high-probability conflict point.

[0157] Multidimensional mapping: Establish a risk quantification matrix or rule set with probability value and time urgency as the main dimensions. For example, a probability value greater than 0.8 and a time urgency of less than 60 seconds may be mapped to an emergency level; a probability value between 0.5 and 0.8 and a time urgency between 60 and 180 seconds may be mapped to a high level.

[0158] Risk Level Determination: Based on the mapping rules established in the previous step, the current risk situation is matched and determined. The system considers the worst-case scenario, such as the highest risk point in the sequence, and outputs a final, definitive collision risk level. This level is a clear and explicit decision signal.

[0159] In summary, matching and quantification represents an intelligent upgrade from geometric prediction to probabilistic risk assessment. It transcends the binary logic of traditional methods that simply determine whether an intersection occurs, and dynamically calculates and quantifies the probability and urgency of collisions in densely trafficked aquaculture waters through spatiotemporal conflict probability matching.

[0160] The collision risk level provides the system with a precise and graded basis for decision-making, so that the triggering of warnings and collision avoidance commands is no longer based on rigid thresholds, but on a comprehensive assessment of the depth and breadth of risks.

[0161] In summary, the system has greatly enhanced its intelligence and reliability in complex multi-ship encounter situations, effectively avoiding early warning failures or ineffective warnings due to misjudgment or omissions, thereby significantly improving the overall safety of collaborative operations of vessels in aquaculture waters.

[0162] S5. When the collision risk level exceeds a preset threshold, the corresponding heading adaptive adjustment command of the ship is triggered and fed back to the control unit of the ship;

[0163] When the collision risk level exceeds a preset threshold, triggering the corresponding adaptive course adjustment command for the vessel and feeding it back to the vessel's control unit includes:

[0164] A risk status assessment is performed on the collision risk level and the preset threshold to generate a risk exceedance indication signal;

[0165] The risk exceeding the limit indication signal is converted into a course adjustment command for the vessel;

[0166] The course adjustment command is converted into a control signal and fed back to the ship's control unit.

[0167] Specifically, the preset threshold is a pre-defined boundary value used to distinguish different risk response levels. It is not a fixed single value, but may be a set of thresholds corresponding to collision risk levels.

[0168] More specifically, for example, the system sets a rule that when the assessed risk level reaches high, i.e. exceeds the threshold of regular monitoring, active adjustment needs to be initiated. The threshold is set by comprehensively considering the navigation safety standards of the aquaculture waters, the ship maneuvering characteristics and the false alarm tolerance.

[0169] Specifically, the risk overrun indication signal is a standardized logic or digital signal generated internally by the system. It explicitly represents the state that the current collision risk level has exceeded the preset threshold, and is the starting flag for triggering the subsequent series of response processes. The signal itself does not contain specific collision avoidance schemes, but only indicates the instruction to take immediate action.

[0170] Specifically, the heading adaptive adjustment instruction is a specific maneuvering command generated by the system after the risk overrun indication signal is triggered. The core content of the instruction is to suggest or require the ship to change its current heading. The adaptivity is reflected in that the generation of the instruction is based on the real-time collision risk level, the target navigation path and the direction vector of the ship and the target ship; the instruction aims to enable the newly planned heading of the ship to adaptively avoid the identified conflict while minimizing the interference with the original operation task.

[0171] Specifically, the control unit refers to an electronic control device or an automatic steering system installed on the ship, which can receive external instructions and drive the ship's execution mechanism. It is the final execution interface for converting digital instructions into physical maneuvering actions.

[0172] Further, the specific steps for generating the risk overrun indication signal by evaluating the collision risk level and the preset threshold are as follows:

[0173] Signal input and comparison: the system receives the collision risk level in real time, for example, low, medium, high, and emergency. At the same time, the preset threshold rules stored in the strategy library are called, for example: threshold 1 corresponds to high level, and threshold 2 corresponds to emergency level.

[0174] Logical judgment: compare the current collision risk level with the preset threshold. The judgment logic is to check whether the current risk level is equal to or higher than the lowest action level specified by the preset threshold.

[0175] Signal generation and output: generate a risk overrun indication signal with high priority. The signal is usually a Boolean quantity or a specific status code, and is sent to the instruction generation module through the internal data bus. If the result is false, a signal indicating normal state is generated, and the system remains in monitoring mode.

[0176] Further, the specific steps for converting the risk overrun indication signal into the heading adjustment instruction of the ship are as follows:

[0177] Signal triggering and scenario analysis: When the instruction generation module receives the risk overrun indication signal, it is immediately activated. It first retrieves the current risk assessment detailed data, including the specific potential conflict location point set, the relevant sailing direction vector set, and the ship's dynamic constraints.

[0178] Collision avoidance strategy calculation: Based on the above data, the module calculates one or more feasible short-term collision avoidance headings. The calculation principles usually include: starboard avoidance, increased distance, avoidance of sharp turns, and efficiency optimization. This may involve simple geometric calculations or optimization based on cost functions.

[0179] Instruction encapsulation: From the calculated feasible solutions, select an optimal or suboptimal heading change value. Encapsulate this recommended heading, along with the expected execution intensity or rate, into a structured data packet, namely the heading adaptive adjustment instruction. The instruction contains the core information of what to do and how much angle to change.

[0180] Further, the specific steps for converting the heading adjustment instruction into a control signal form and feeding back to the control unit of the ship are:

[0181] Protocol conversion: The system encodes and converts the internally generated, structured heading adaptive adjustment instruction data packet into a communication protocol and data format that can be recognized and accepted by the ship control unit.

[0182] Signal output and transmission: Through physical communication interfaces such as serial ports, network ports, and wireless data radio stations, the converted standard control signal is sent out in real time. In aquaculture waters, it is necessary to ensure the reliability and low delay of the communication link to cope with complex electromagnetic environments.

[0183] Feedback to the control unit: After the control unit on the ship receives the signal, it is parsed and understood as a heading adjustment instruction.

[0184] Subsequently, the control unit or the operator confirms the execution, or directly drives the steering mechanism and other execution mechanisms, so that the ship starts to adjust the heading according to the instruction.

[0185] Overall, triggering and feedback are the key hubs for converting risk assessment conclusions into closed-loop control actions. It realizes intelligent decision triggering through risk state assessment, generates specific collision avoidance schemes that comply with sailing rules and aquaculture environment constraints through instruction conversion, and finally accurately projects digital world decisions onto physical world ship maneuvering through signal feedback.

[0186] In general, this step ensures that the early warning system is not simply an alarm, but an intelligent agent that can autonomously and adaptively intervene in the control loop. In aquaculture waters with dense ships and complex environments, this closed-loop capability from perception and early warning to active control is of decisive significance for resolving collision risks and ensuring operational safety within limited time and space, and fundamentally improves the active safety protection level of the system.

[0187] S6、According to the response delay time of the control unit, dynamically update the target navigation path.

[0188] According to the response delay time of the control unit, dynamically update the target navigation path, comprising:

[0189] Combine the response delay time of the control unit with the timestamp sequence of the target navigation path to generate a set of ship route update cycle intervals;

[0190] In the route update cycle interval, combine the dynamic environmental resistance influence coefficient to generate the displacement correction component of the ship;

[0191] Reconstruct the target navigation path through the set of displacement correction components.

[0192] In the route update cycle interval, combine the dynamic environmental resistance influence coefficient to generate the displacement correction component of the ship, comprising:

[0193] Extract the time segment path point of the target navigation path in the route update cycle interval;

[0194] According to the dynamic environmental resistance influence coefficient, decompose the resistance component influence vector of the time segment path point;

[0195] Combine the response delay time and the resistance component influence vector to calculate the displacement lag compensation of the time segment path point;

[0196] Fuse the displacement lag compensation into the set of real-time position coordinates to obtain the displacement correction component of the ship.

[0197] Specifically, the response delay time of the control unit is a measured or estimated time value, representing the total time experienced from the system generating and issuing a heading adjustment instruction to the control unit of the ship actually driving the actuator to make the ship's heading start to change measurably. In aquaculture waters, this delay includes signal transmission, control unit processing, and mechanical actuator response time, which is affected by communication quality, device performance, and environmental interference.

[0198] Specifically, the set of route update cycle intervals is a collection of time windows. The system divides the whole predicted future period into several continuous or overlapping time intervals according to the length of response delay time and the inherent time schedule of the target sailing path. Each interval represents an independent calculation cycle that needs path prediction compensation and update, and the division ensures that the delay effect is included in the starting calculation conditions of each cycle.

[0199] Specifically, the time slice path point refers to a series of predicted position coordinate points that are intercepted from the current target sailing path within a certain route update cycle interval and belong to the time period.

[0200] Specifically, the resistance component influence vector is a vector obtained by directionally decomposing the comprehensive resistance effect represented by the dynamic environmental resistance influence coefficient at a certain time slice path point. It specifically indicates what direction the environmental resistance will hinder or push the ship's displacement at the point.

[0201] Specifically, the displacement lag compensation quantity is a displacement vector that is specifically used to compensate for the prediction error caused by the existence of response delay time. During the delay period, the ship does not maneuver according to the new instructions, but continues to move along the original trend under the influence of environmental resistance, which will cause the actual position to deviate from the path point predicted in the last cycle. This compensation quantity is an estimate of this deviation.

[0202] Specifically, the displacement correction component is the latest estimate of the ship's displacement vector within a certain time slice in the future after considering the compensation of the response delay time.

[0203] Further, the specific steps of generating the set of route update cycle intervals of the ship in combination with the response delay time of the control unit and the timestamp sequence of the target sailing path are as follows:

[0204] Parameter acquisition: the system acquires the response delay time of the control unit, which is pre-calibrated or estimated online. At the same time, the timestamp sequence corresponding to each predicted point on the current target sailing path is read, which defines the total length and resolution of the prediction.

[0205] Cycle division: taking the current system time as the starting point, the first update cycle interval is usually set from the current time to the future time. This interval covers the delay blind area where the instruction is being delivered and executed, and the ship's state has not changed. The subsequent cycles can be divided by fixed time length or prediction step or according to the key points of the path, forming a set of route update cycle intervals that continuously cover the whole prediction period. The division of each interval clearly associates the starting boundary of the delay time's influence on path prediction.

[0206] Further, the specific step of generating the displacement correction component of the ship within the route update cycle interval in combination with the dynamic environmental resistance influence coefficient is:

[0207] Path point extraction: for the route update cycle interval currently being processed, from the existing target navigation path, all predicted coordinate points with timestamps falling within this interval are screened out, and these points constitute the time slice path points of the current interval.

[0208] Resistance vector decomposition: for each time slice path point, according to its geographical location and the predicted heading at that point, the dynamic environmental resistance influence coefficient and the related wave and water grass direction information are called. Through physical models or empirical rules, the comprehensive resistance effect of the point is decomposed into specific resistance component influence vectors in the ship motion coordinate system. For example, it is decomposed into head wave resistance, side thrust and water grass entanglement caused deceleration effect.

[0209] Hysteresis compensation calculation: the core is to calculate the displacement hysteresis compensation amount. The system considers that at the beginning of the current route update cycle interval, the ship is still moving according to the old, un-updated control instructions. During this delay period, the displacement of the ship is affected by the continuous resistance component influence vectors. Therefore, the displacement hysteresis compensation amount is equal to: the additional displacement deviation caused by the integration of the old ship motion state and the continuous action of the resistance component influence vector in the delay period. This deviation is not included in the last round of prediction.

[0210] Correction component generation: the calculated displacement hysteresis compensation amount is taken as a basic offset, and is fused with the ideal displacement of the time slice predicted according to the latest ship state and environmental coefficient. At the same time, the compensation amount information is also fused into the estimation of the latest real-time position coordinate set used as the starting point of the next prediction. Finally, a new set of displacement correction components suitable for the current update cycle interval is obtained, which includes the delay compensation effect.

[0211] Further, the specific step of reconstructing the target navigation path through the displacement correction component set is:

[0212] Global integration: for each route update cycle interval, repeat the above steps to generate a corresponding set of displacement correction components. Integrate all the components generated in all intervals in the future time sequence to form a complete set of displacement correction components covering the entire prediction field.

[0213] Path reconstruction: using the new and more accurate displacement correction component set, a new future navigation trajectory starting from the latest ship state estimate after compensation correction is reconstructed according to the vector accumulation and trajectory smoothing method. This new trajectory is the dynamically updated target navigation path.

[0214] In general, the dynamic update is a calibrator to realize the synchronization of the prediction model with the real physical world. It creatively introduces the key real constraint of the response delay time of the control unit, structurally manages the delay effect by generating a set of flight path update cycle intervals, and actively compensates for the accumulated trajectory prediction error due to system reaction delay by calculating and fusing displacement lag compensation. This makes the target navigation path issued by the system no longer a static prediction based on ideal instantaneous response, but a dynamic and rolling prediction that can foresee the consequences of its own instruction execution delay and correct in advance.

[0215] In general, in the collision avoidance scene of the breeding water area where the environment changes rapidly and the time effectiveness is extremely high, this mechanism greatly improves the accuracy, robustness and reliability of the system closed-loop control, and ensures that the collision avoidance decision can be effectively implemented even in the presence of inherent delay. It is the core technical support to solve the problem of system response lag.

[0216] As shown in Figure 2 , it is a functional module diagram of a ship anti-collision early warning system for a breeding water area provided by an embodiment of the application.

[0217] The ship anti-collision early warning system 100 for a breeding water area can be installed in an electronic device. According to the functions to be realized, the ship anti-collision early warning system 100 for a breeding water area can include a ship state perception module 101, a dynamic environment modeling module 102, a trajectory planning correction module 103, a collision risk assessment module 104, a warning decision and instruction generation module 105, and a path dynamic update and compensation module 106. The modules of the application can also be referred to as units, which refer to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, and are stored in the memory of the electronic device.

[0218] In this embodiment, the functions of each module / unit are as follows:

[0219] The ship state perception module 101 is used to obtain a set of real-time position coordinates and a set of sailing direction vectors of ships in the breeding area.

[0220] The dynamic environment modeling module 102 is used to generate a dynamic environment resistance influence coefficient in combination with the wave direction gradient and the water grass distribution density gradient of the breeding area.

[0221] The trajectory planning correction module 103 is used to correct the expected sailing displacement deviation of the ship according to the dynamic environment resistance influence coefficient to obtain a target sailing path of the ship.

[0222] The collision risk assessment module 104 is configured to perform spatio-temporal conflict probability matching between the target navigation path and the navigation behavior characteristic parameters of the adjacent ship, so as to obtain a collision risk level of the ship.

[0223] The early warning decision and instruction generation module 105 is configured to trigger a corresponding heading self-adaptive adjustment instruction of the ship and feed back to the control unit of the ship when the collision risk level exceeds a preset threshold.

[0224] The path dynamic updating and compensation module 106 is configured to dynamically update the target navigation path according to a response delay time of the control unit.

[0225] In several embodiments provided in the present application, it should be understood that the disclosed method and system can be implemented in other ways. For example, the system embodiments described above are only illustrative, for example, the division of the modules is only a logical function division, and another division mode can be used in actual implementation.

[0226] The modules described as separate components can or can not be physically separated, and the components displayed as modules can or can not be physical units, that is, they can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment scheme according to actual needs.

[0227] In addition, the function modules in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of hardware plus software function modules.

[0228] It is obvious for those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application.

[0229] The embodiments of the present application can acquire and process related data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology and application system for using digital computers or computer-controlled machines to simulate, extend and expand human intelligence, perceive environment, acquire knowledge and use knowledge to obtain optimal results.

[0230] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A method for ship collision avoidance early warning in aquaculture waters, characterized in that, The method includes: S1. Obtain the real-time position coordinates and navigation direction vectors of ships within the aquaculture area; S2. A dynamic environmental resistance influence coefficient is generated by combining the wave direction gradient and aquatic plant distribution density gradient of the aquaculture area, including: in: This is the dynamic environmental resistance influence coefficient. For phase coherence intensity, The critical entanglement coefficient. The gradient vector is the wave direction. The density gradient modulus of aquatic plants. This is the wave vector-heading mismatch angle; S3. Correcting the expected navigation displacement deviation of the ship based on the dynamic environmental resistance influence coefficient to obtain the target navigation path of the ship, including: The ideal displacement baseline of the ship is generated based on the ship's navigation direction vector set and the ship's real-time position coordinate set; The displacement component vector of the ideal displacement baseline is adjusted based on the dynamic environmental resistance influence coefficient to obtain the corrected displacement component set of the ship. Based on the modified displacement component set, the real-time position coordinate set is reconstructed to obtain the target navigation path of the ship. S4. Perform spatiotemporal conflict probability matching between the target navigation path and the navigation behavior characteristic parameters of adjacent vessels to obtain the collision risk level of the vessel. S5. When the collision risk level exceeds a preset threshold, the corresponding heading adaptive adjustment command of the ship is triggered and fed back to the control unit of the ship; S6. Dynamically update the target navigation path based on the response delay time of the control unit.

2. The method for ship collision avoidance early warning in aquaculture waters as described in claim 1, characterized in that, The steps for obtaining the real-time location coordinate set include: The original satellite positioning signal corresponding to the ship is analyzed by spatiotemporal coordinate sequence to obtain the real-time position coordinate set of the ship.

3. The method for ship collision avoidance early warning in aquaculture waters as described in claim 1, characterized in that, The steps for obtaining the navigation direction vector set include: The ship's navigation direction is calibrated based on the real-time position coordinate set and the ship's attitude sensor data to obtain the ship's navigation direction vector; The navigation direction vectors are dynamically integrated in space to obtain the navigation direction vector set of the ship.

4. The method for ship collision avoidance early warning in aquaculture waters as described in claim 1, characterized in that, The step of performing spatiotemporal conflict probability matching between the target navigation path and the navigation behavior characteristic parameters of adjacent vessels to obtain the collision risk level of the vessels includes: Spatiotemporal position overlap detection is performed on the target navigation path and the navigation behavior characteristic parameters of adjacent vessels to generate a set of potential conflict location points; Relative motion vector analysis is performed on the set of potential conflict locations and the set of navigation direction vectors to generate a sequence of conflict probability values; The collision risk level of the ship is obtained by quantifying the probability value sequence of the conflict occurrence.

5. The method for ship collision avoidance early warning in aquaculture waters as described in claim 1, characterized in that, When the collision risk level exceeds a preset threshold, triggering the corresponding adaptive course adjustment command for the vessel and feeding it back to the vessel's control unit includes: A risk status assessment is performed on the collision risk level and the preset threshold to generate a risk exceedance indication signal; The risk exceeding the limit indication signal is converted into a course adjustment command for the vessel; The course adjustment command is converted into a control signal and fed back to the ship's control unit.

6. The method for ship collision avoidance early warning in aquaculture waters as described in claim 1, characterized in that, The step of dynamically updating the target navigation path based on the response delay time of the control unit includes: The route update cycle interval set of the ship is generated by combining the response delay time of the control unit with the timestamp sequence of the target navigation path; Within the route update cycle, the displacement correction component of the ship is generated by combining the dynamic environmental resistance influence coefficient. The target navigation path is reconstructed using the displacement correction component set.

7. The method for ship collision avoidance early warning in aquaculture waters as described in claim 6, characterized in that, The process of generating the ship's displacement correction component within the route update cycle interval, in conjunction with the dynamic environmental resistance influence coefficient, includes: Extract time segment path points of the target navigation path within the route update cycle interval; The resistance component influence vector of the path point in the time segment is decomposed based on the dynamic environmental resistance influence coefficient. The displacement hysteresis compensation amount of the path point in the time segment is calculated by combining the response delay time and the influence vector of the resistance component. The displacement hysteresis compensation is fused into the real-time position coordinate set to obtain the displacement correction component of the ship.

8. A ship collision avoidance early warning system for aquaculture waters, used to implement the ship collision avoidance early warning method for aquaculture waters as described in any one of claims 1-7, characterized in that, The system includes: The ship status perception module is used to acquire the real-time position coordinates and navigation direction vectors of ships within the aquaculture area; The dynamic environment modeling module is used to generate dynamic environmental resistance influence coefficients by combining the wave direction gradient and aquatic plant distribution density gradient of the aquaculture area, including: in: This is the dynamic environmental resistance influence coefficient. For phase coherence intensity, The critical entanglement coefficient. The gradient vector is the wave direction. The density gradient modulus of aquatic plants. This is the wave vector-heading mismatch angle; A trajectory planning correction module is used to correct the expected navigation displacement deviation of the ship based on the dynamic environmental resistance influence coefficient, so as to obtain the target navigation path of the ship, including: The ideal displacement baseline of the ship is generated based on the ship's navigation direction vector set and the ship's real-time position coordinate set; The displacement component vector of the ideal displacement baseline is adjusted based on the dynamic environmental resistance influence coefficient to obtain the corrected displacement component set of the ship. Based on the modified displacement component set, the real-time position coordinate set is reconstructed to obtain the target navigation path of the ship. The collision risk assessment module is used to perform spatiotemporal conflict probability matching between the target navigation path and the navigation behavior characteristic parameters of adjacent vessels to obtain the collision risk level of the vessel. The early warning decision and instruction generation module is used to trigger the corresponding course adaptive adjustment instruction of the ship and feed it back to the control unit of the ship when the collision risk level exceeds a preset threshold. The path dynamic update and compensation module is used to dynamically update the target navigation path based on the response delay time of the control unit.

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