A marine radar navigation method based on AIS signals

Abstract

The present invention relates to an ocean radar navigation method based on AIS signals, belonging to the field of ocean navigation and radio direction finding technology. The method comprises: obtaining navigation sections and navigation timings from navigation mission data; determining navigation key points and their effective navigation windows; optimizing and solving radar navigation strategies based on radar scanning distance intervals and scanning frequency intervals corresponding to monitoring type information and risk levels; generating ship control instructions based on the strategy and synchronously collecting radar / AIS signals to perform navigation risk assessment; and dynamically updating mission data and navigation strategies based on the navigation execution status. This method achieves real-time collaborative verification of a ship's identity, position, and environment, as well as active collision avoidance navigation, in complex sea conditions. The present application addresses the technical issues in the prior art caused by large matching errors between radar and AIS targets and fixed scanning parameters leading to collision avoidance delays.

Description

Technical Field

[0001] The present invention relates to the technical field of ocean navigation and radio direction finding, and more particularly to an ocean radar navigation method based on AIS signals. Background Art

[0002] Traditional ship navigation systems have significant technical limitations. In terms of target identification, radar system performance degrades significantly in adverse weather conditions. Clutter interference from dense fog can make it difficult to distinguish between false targets and real ships, while noise signals from wave reflections further increase the risk of misjudgment. Furthermore, traditional radar cannot obtain a ship's identity information and can only infer risk based on its position and movement trajectory. This single-dimensional judgment method is prone to collision misjudgments.

[0003] In terms of data collaboration, existing technologies have serious system fragmentation problems. Although the AIS system can provide key information such as ship identification codes and navigation intentions, it fails to form deep data fusion with the radar detection system. The two systems use independent operating mechanisms, and there is a timing difference between the radar scanning cycle and the AIS message update frequency, resulting in significant temporal and spatial deviations when comparing target positions. In actual applications, positioning errors of hundreds of meters often occur.

[0004] Insufficient environmental adaptability is another prominent flaw. The existing technology mainly adopts fixed-parameter radar scanning strategies that cannot cope with the complex and changeable environmental characteristics at sea. When encountering sudden dense fog or a sudden increase in ship density, the system response is significantly delayed, especially in high-risk areas such as narrow waterways. Traditional navigation methods in multi-ship intersection scenarios rely heavily on manual decision-making, and their response delays often exceed the time threshold for safe operation. Summary of the Invention

[0005] The purpose of this application is to provide a marine ship navigation method based on the fusion of AIS signals and radar, which has the advantages of improving navigation accuracy, reducing the risk of misjudgment, and enhancing environmental adaptability.

[0006] The present application provides an ocean radar navigation method based on AIS signals. The technical solution is as follows: An ocean radar navigation method based on AIS signals, comprising:

[0007] Acquiring navigation mission data, the navigation mission data including a number of navigation sections in the target navigation area, a number of navigation actions in each navigation section, and a navigation time sequence for each navigation section;

[0008] Based on a number of navigation actions of each navigation section and a navigation timing of each navigation section, a number of navigation key points of the target navigation area and an effective navigation window of each navigation key point are determined;

[0009] Extract the monitoring type information and risk level of each navigation key point in the pre-defined navigation monitoring requirements, analyze the effective navigation window of each navigation key point, use the radar scanning range interval corresponding to the monitoring type information and the scanning frequency interval corresponding to the risk level as constraints, and take the minimum navigation error as the optimization goal to optimize the radar navigation strategy for the target navigation area;

[0010] Generate ship control instructions to the ship based on the radar navigation strategy, control the ship to execute the corresponding navigation action, collect radar signals and AIS signals, and perform navigation risk assessment based on the fused radar and AIS signals;

[0011] After the ship completes each navigation action, the navigation execution status is obtained, the navigation mission data is updated based on the navigation execution status, and the radar navigation strategy is regenerated using the updated navigation mission data.

[0012] Furthermore, the present application also proposes that obtaining navigation mission data includes: obtaining historical navigation data of the ship, and extracting the historical navigation time for each navigation action in different reference navigation sections from the historical navigation data of the ship; obtaining target navigation mission parameters, and extracting several navigation sections in the target navigation sea area and several navigation actions in each navigation section recorded in the target navigation mission parameters; performing similarity matching based on the navigation environment characteristics of the reference navigation section and each navigation section in the target navigation sea area, and matching several reference navigation sections with navigation environment characteristics similarity higher than the target value for each navigation section; obtaining the navigation speed and route density of neighboring ships in real time based on AIS signals, and calculating the expected time for each navigation action in each navigation section based on the historical navigation time for each navigation action in several reference navigation sections with matching relationships; determining the navigation timing of each navigation section in the target navigation sea area based on the expected time for each navigation action in each navigation section, and generating navigation mission data.

[0013] Furthermore, the present application also proposes to determine several navigation key points of the target navigation area and the effective navigation window of each navigation key point, including: extracting three types of preset navigation key points from the electronic nautical chart: including turning points: the coordinate points of the sea area where the ship needs to change its course; including intersection points: the coordinate points of the sea area where multiple channels intersect; including narrow waterway points: the coordinate points of the narrow sea area where the channel width is less than the safety threshold; based on AIS signal decoding, the real-time position and navigation trajectory of the neighboring ships are obtained, and the coordinate points that have spatial overlap with the trajectory of the neighboring ships are screened out from the turning points, intersection points and narrow waterway points as high-priority navigation key points; based on the navigation timing of each navigation section, combined with the ship dynamics model and the real-time ocean current data provided by the AIS signal, the earliest arrival time and latest departure time of the ship at each navigation key point are calculated to form a dynamic time window as the effective navigation window.

[0014] Furthermore, the present application also proposes that optimizing and solving the radar navigation strategy for the target navigation area includes: obtaining pre-established navigation monitoring requirements, extracting the monitoring type information and risk level of each navigation key point in the navigation monitoring requirements; using the monitoring type information and risk level to match the radar scanning distance and scanning frequency of each navigation key point in a preset signal feature mapping table and risk level mapping table, respectively; based on real-time analysis of ship density distribution by AIS signals, dynamically adjusting the matched radar scanning distance interval: reducing the lower limit of the scanning distance interval in areas with high ship density; analyzing the effective navigation window of each navigation key point, and using the adjusted radar scanning distance interval and scanning frequency interval as constraints to generate a scanning path sequence for synchronously collecting radar signals and AIS signals.

[0015] Furthermore, the present application also proposes that optimizing and solving the radar navigation strategy for the target navigation area also includes: constructing a dynamic sea state model of the target navigation area, integrating electronic chart data, real-time AIS ship position data and meteorological data; generating a circular monitoring area centered on the navigation key point in the dynamic sea state model based on the adjusted radar scanning distance interval of each navigation key point; obtaining the scanning speed parameters of the ship radar, and generating a radar scanning path with the circular monitoring area as the spatial constraint and the effective navigation window as the time constraint; inserting AIS signal acquisition nodes in the radar scanning path to ensure that each navigation key point synchronously acquires AIS signals within a preset time before and after the radar scan; using the time interval between adjacent scanning points in the scanning path to meet the scanning frequency interval as the first constraint, and minimizing the position synchronization error between the radar and AIS signals as the optimization goal, to solve the optimal scanning point sequence.

[0016] Furthermore, the present application also proposes to generate ship control instructions, including: extracting the signal acquisition position and signal acquisition time of each scanning point in the optimal scanning point sequence; calculating the heading angle adjustment amount based on the current ship position and the next scanning point position; calculating the speed adjustment amount based on the current ship speed and the required time to reach the next scanning point; at the same time, based on the timing requirements of the AIS signal acquisition node, generating an AIS receiver start instruction; combining the heading angle adjustment amount, the speed adjustment amount and the AIS receiver start instruction to form a ship control instruction set.

[0017] Furthermore, the present application also proposes updating navigation mission data, including: triggering data update when the position deviation value between the radar and AIS signals continuously exceeds a threshold; obtaining the real-time motion status of neighboring ships based on AIS signals and recalculating the time consumption of ship avoidance actions; dynamically adjusting the effective navigation window of subsequent navigation key points based on the recalculated time consumption data; and regenerating the radar navigation strategy using the adjusted effective navigation window.

[0018] Furthermore, the present application also proposes to perform navigation risk assessment based on the collected radar signals and AIS signals, including: performing clutter suppression processing on the radar echo signal to extract the outline characteristics and motion vector of the target ship; decoding the AIS signal to obtain the MMSI number, ship position coordinates, heading angle and speed of the neighboring ship; performing spatiotemporal matching between the target ship outline extracted by the radar and the ship position decoded by the AIS: including performing nearest neighbor matching on the position coordinates of the radar target and the AIS ship; including calculating the position deviation distance between the successfully matched radar target and the AIS ship; performing three-level risk assessment: including generating an identity authentication alarm when the position deviation distance is greater than a first threshold; including generating a hidden ship alarm when the radar detects a ship target that does not match the AIS signal; including generating a signal failure alarm when the AIS signal exists but the radar does not detect a matching target.

[0019] Furthermore, the present application also proposes that risk assessment also includes dynamic threshold adjustment: real-time calculation of the ship density value of the current sea area based on the AIS signal; dynamic adjustment of the risk assessment threshold based on the ship density value: including proportionally reducing the identity authentication alarm threshold when the ship density is higher than the critical value; including proportionally increasing the hidden ship alarm threshold when the ship density is lower than the critical value; at the same time, the heading change rate of the neighboring ship is obtained based on the AIS signal, and when the heading change rate exceeds the preset value, the emergency collision avoidance plan is triggered.

[0020] Furthermore, the present application also proposes that optimizing and solving the radar navigation strategy for the target navigation area also includes: decoding real-time wave height data and wind speed data from the AIS signal; adjusting the radar scanning distance interval based on the wave height data: including increasing the lower limit of the scanning distance interval when the wave height is greater than the set value; adjusting the scanning frequency interval based on the wind speed data: including increasing the lower limit of the scanning frequency interval when the wind speed is greater than the set value; regenerating the radar scanning path based on the adjusted parameters, and increasing the frequency of AIS signal acquisition in high wave height areas.

[0021] From the above, it can be seen that the present application provides a marine ship navigation method based on the fusion of AIS signals and radar. By fusing radar signals and AIS signals to optimize dynamic navigation strategies and updating navigation parameters in combination with real-time environmental data, it effectively solves the problem of target recognition errors of traditional navigation systems under adverse weather conditions, and significantly improves navigation safety and navigation accuracy under complex sea conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily apparent by reading the following detailed description with reference to the accompanying drawings, in which several embodiments of the present invention are shown by way of example and not limitation, in which:

[0023] Figure 1A schematic flow chart of an AIS signal-based ocean radar navigation method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The technical solutions of this application will be described clearly and completely below, in conjunction with the accompanying drawings. It should be understood that the described embodiments represent only a portion of the embodiments of this application, and not all of them. The components of this application, generally described and illustrated in the drawings herein, may be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of this application provided in the drawings is not intended to limit the scope of the claimed application, but rather merely represents selected embodiments of this application. All other embodiments derived by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application. It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. Furthermore, in the description of this application, the terms "first," "second," etc., are used solely to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0025] In traditional ship radar navigation systems, radar echo signals and AIS signals fail to achieve deep fusion, resulting in insufficient target recognition reliability and significant system response delays. Due to differences in the acquisition cycles and spatial coverage of radar and AIS signals, the asynchronous operation mechanism causes deviations in target temporal and spatial coordinates, making it difficult to accurately match the ship profile detected by the radar with the ship identity information decoded by the AIS. Furthermore, fixed scanning parameters cannot adapt to dynamically changing ship density and sea conditions, limiting the efficiency of real-time risk assessment in high-risk areas (such as turning points or intersections) and failing to meet the navigation accuracy requirements in complex navigation scenarios.

[0026] In this regard, this application proposes a marine radar navigation method based on AIS signals, such as Figure 1 Shown, including:

[0027] Acquiring navigation mission data, the navigation mission data including a number of navigation sections in the target navigation area, a number of navigation actions in each navigation section, and a navigation time sequence for each navigation section;

[0028] Based on a number of navigation actions of each navigation section and a navigation timing of each navigation section, a number of navigation key points of the target navigation area and an effective navigation window of each navigation key point are determined;

[0029] Extract the monitoring type information and risk level of each navigation key point in the pre-established navigation monitoring requirements, analyze the effective navigation window of each navigation key point, and use the radar scanning distance interval corresponding to the monitoring type information and the scanning frequency interval corresponding to the risk level as constraints.

[0030] Taking the minimum navigation error as the optimization goal, optimize and solve the radar navigation strategy for the target navigation area;

[0031] Generate ship control instructions to the ship based on the radar navigation strategy, control the ship to execute the corresponding navigation action, collect radar signals and AIS signals, and perform navigation risk assessment based on the fused radar and AIS signals;

[0032] After the ship completes each navigation action, the navigation execution status is obtained, the navigation mission data is updated based on the navigation execution status, and the radar navigation strategy is regenerated using the updated navigation mission data.

[0033] Navigation mission data refers to a data set containing multiple navigation sections within the target navigation area, navigation maneuvers for each section, and their timing. This can be achieved through the vessel mission planning system, which collects navigation section divisions, maneuver sequences, and time scheduling. This data provides structured input for subsequent navigation strategy optimization. Key navigation points are locations along the navigation path that require focused monitoring and control. This can be achieved by analyzing turning points, intersections, and narrow channels on electronic nautical charts. These points are used to identify high-risk areas and allocate monitoring resources. The effective navigation window is the time range within which a vessel can safely operate at a key navigation point. This can be achieved by calculating the earliest arrival time and latest departure time using a ship dynamics model combined with real-time ocean current data. This is used to constrain radar scanning timing. The radar navigation strategy is the operational plan that controls radar scanning parameters and signal acquisition logic. This can be achieved by solving a mathematical model that optimizes minimum navigation error and incorporates scanning range and frequency constraints. This strategy is used to synchronize radar and AIS signal acquisition.

[0034] The fused radar and AIS signals integrate data by temporally and spatially aligning radar echo targets with AIS vessel identity information. This is achieved by calculating position deviation distances using a nearest neighbor matching algorithm, eliminating identity misassociations caused by asynchronous data. Navigation execution status updates adjust mission data based on real-time feedback after the vessel's actions are completed. This is achieved by analyzing the motion status of neighboring ships through AIS signals and recalculating time-consuming data, which is then used to dynamically correct subsequent navigation windows and scanning strategies.

[0035] During implementation, this application first acquires navigation mission data, including the navigation section, navigation actions, and navigation timing of the target navigation area. Based on this data, navigation key points and the effective navigation window are determined. The monitoring type information and risk level of each navigation key point in the navigation monitoring requirements are then extracted, and this is used as a constraint to optimize and solve the radar navigation strategy. Next, ship control instructions are generated based on the radar navigation strategy, controlling the ship to execute navigation actions and collect radar and AIS signals, and performing navigation risk assessment based on the fused signals. Finally, the navigation execution status is obtained after each navigation action, the navigation mission data is updated, and the radar navigation strategy is regenerated.

[0036] By deeply integrating radar and AIS signals, a dynamic and adaptive radar navigation strategy is implemented, improving navigation accuracy and safety. Furthermore, by updating navigation mission data in real time, this method has strong environmental adaptability and risk response capabilities.

[0037] As a preferred embodiment, the specific implementation of this application is as follows:

[0038] When acquiring navigation mission data, the historical navigation maneuver durations for different reference navigation sections are extracted from the vessel's historical navigation database. This is combined with the target navigation section and navigation maneuvers recorded in the target navigation mission parameters to perform a similarity match on navigation environment features. This matching utilizes multidimensional feature vectors, including factors such as water depth, tide, and channel width. Reference navigation sections with similarity exceeding a preset threshold are selected for subsequent calculations.

[0039] Real-time information on the navigation speed and route density of nearby vessels is acquired from AIS signals. By combining this real-time data with the historical duration of a matching reference navigation segment, a weighted average method is used to calculate the expected duration of each navigation maneuver. Based on this calculated expected duration, the navigation timing for each navigation segment is determined, generating complete navigation mission data.

[0040] To identify key navigation points, the system first extracts three types of preset points from electronic nautical charts: turning points, intersection points, and narrow channel points. AIS signal decoding is used to obtain the real-time positions and navigational tracks of nearby vessels. Using a spatial analysis algorithm, coordinate points that overlap with the tracks of nearby vessels are selected as high-priority key navigation points.

[0041] When calculating the effective navigation window, the ship dynamics model and the real-time ocean current data provided by the AIS signal are combined. Numerical integration methods can be used to calculate the earliest arrival time and latest departure time of the ship at each navigation key point, forming a dynamic time window.

[0042] The radar navigation strategy optimization solution first matches the radar scanning range and frequency for each key navigation point from a preset signal feature map and risk level map. Based on the ship density distribution analyzed in real-time from AIS signals, the matching radar scanning range interval is dynamically adjusted. This adjustment uses linear interpolation, reducing the lower limit of the scanning range interval in areas with high ship density.

[0043] Generate a scanning path sequence and construct a dynamic sea state model of the target navigation area, integrating electronic chart data, real-time AIS ship position data, and meteorological data. Create a circular monitoring area centered on a key navigation point within the dynamic sea state model. Obtain the scanning speed parameters of the ship's radar and generate a radar scanning path using the circular monitoring area as a spatial constraint and the effective navigation window as a temporal constraint. Insert AIS signal acquisition nodes into the scanning path to ensure that each key navigation point synchronously acquires AIS signals within a preset time before and after the radar scan.

[0044] With the constraint that the time interval between adjacent scanning points in the scanning path satisfies the scanning frequency interval and the optimization goal of minimizing the position synchronization error between radar and AIS signals, a dynamic programming algorithm is used to solve the optimal scanning point sequence.

[0045] Based on the optimized radar navigation strategy, ship control commands are generated. The signal acquisition location and time of each scan point in the optimal scan point sequence are extracted, and the heading angle and speed adjustment are calculated. Simultaneously, an AIS receiver activation command is generated to ensure synchronization between AIS signal acquisition and radar scanning. These commands are combined into a ship control command set and sent to the ship's execution system.

[0046] During navigation, the system continuously collects radar and AIS signals. It performs clutter suppression on radar echo signals to extract the target vessel's profile and motion vector. It also decodes AIS signals to obtain the nearby vessel's MMSI number, position coordinates, heading angle, and speed.

[0047] When assessing navigation risk, the radar-derived target vessel profile is spatially and temporally matched with the vessel position decoded by AIS. A nearest neighbor matching algorithm is used to calculate the positional deviation between the successfully matched radar target and the AIS vessel. Three levels of risk assessment are implemented: an authentication alarm is generated when the positional deviation distance exceeds a preset threshold; a hidden vessel alarm is generated when the radar detects a vessel target whose AIS signal is not matched; and a signal failure alarm is generated when an AIS signal is present but the radar does not detect a matching target.

[0048] After each navigation maneuver, the ship obtains the navigation execution status, including the actual navigation trajectory and time. Based on this status information, the expected time and navigation sequence in the navigation mission data are updated. Using the updated navigation mission data, the radar navigation strategy optimization process is re-executed to generate a new radar navigation strategy.

[0049] Through the above scheme, the present application realizes the deep fusion of radar signals and AIS signals, and improves the accuracy of target identification. The dynamically adjusted radar scanning strategy can adapt to complex and changeable sea conditions and effectively cover high-risk areas. The real-time navigation risk judgment mechanism improves the system's response speed to potential dangers. By continuously updating navigation mission data and regenerating navigation strategies, this method has strong adaptability, can respond to various changes in navigation in a timely manner, and improves the safety and efficiency of ship navigation. In addition, by optimizing the radar scanning path and AIS signal acquisition nodes, this method reduces the redundancy of signal acquisition and improves the efficiency of system resource utilization.

[0050] Furthermore, obtaining navigation mission data includes:

[0051] Obtaining historical navigation data of the ship, and extracting the historical navigation time of each navigation action in different reference navigation sections from the historical navigation data of the ship;

[0052] Obtain target navigation mission parameters, extract a plurality of navigation sections in the target navigation sea area and a plurality of navigation actions for each navigation section recorded in the target navigation mission parameters;

[0053] Based on the similarity matching between the reference navigation section and the navigation environment characteristics of each navigation section in the target navigation sea area, a number of reference navigation sections with navigation environment characteristics similarity higher than the target value are matched for each navigation section;

[0054] The navigation speed and route density of neighboring ships are obtained in real time based on AIS signals. The expected navigation time of each navigation action in each navigation section is calculated by combining the historical navigation time of each navigation action in several reference navigation sections with matching relationships in each navigation section.

[0055] Based on the expected time consumption of each navigation action in each navigation section, the navigation timing of each navigation section in the target navigation area is determined and the navigation mission data is generated.

[0056] Historical vessel navigation data is extracted by parsing historical AIS track logs. Historical navigation times include the execution time of turning, acceleration, and deceleration actions under different sea conditions. Similarity matching of navigation environment features is performed using multidimensional feature vectors, including water depth, channel width, and tidal patterns. Expected navigation time calculation incorporates the density of neighboring ships as a correction factor. When the density exceeds a threshold, the historical navigation time is multiplied by a dynamic adjustment factor. Navigation timing generation utilizes a time series superposition model to ensure that the timing intervals between adjacent navigation actions meet the ship's dynamic constraints.

[0057] Specifically, the system uses AIS signals to analyze the speed and route density of neighboring ships in real time. Combined with the historical turn times of reference navigation sections after similarity matching, the expected time for each navigation maneuver is dynamically adjusted. For example, if the target navigation section matches three reference sections with historical turn times of 120 seconds, 130 seconds, and 140 seconds, respectively, and the current neighboring ship density is high, the dynamic adjustment factor is set to 1.2, and the expected time is calculated to be (120 + 130 + 140) / 3 × 1.2 = 156 seconds.

[0058] Based on the revised expected duration, navigation actions for each navigation segment are arranged chronologically to generate a navigation time sequence with start and duration. The resulting navigation mission data can reflect the impact of real-time ship density, avoid navigation window misalignment caused by fixed duration parameters, and improve the adaptability of subsequent radar navigation strategies.

[0059] In some embodiments, historical ship navigation data is obtained to extract the historical navigation time for each navigation action in different reference navigation sections. For example, the navigation records of the ship in each section over the past year are extracted from a ship navigation log database, including the actual time taken for each turning, acceleration, deceleration, and other actions.

[0060] Obtain the target navigation mission parameters and extract the navigation segments and navigation actions for each navigation segment in the target navigation area. Specifically, obtain the target route of the current voyage from the voyage planning system, divide the route into multiple navigation segments, and identify the sequence of navigation actions required for each segment.

[0061] Perform navigation environment feature similarity matching. This involves comparing the target navigation section with historical reference navigation sections based on electronic chart data, such as water depth, channel width, and navigation aid distribution, and calculating a similarity score. Reference navigation sections with similarity scores exceeding a preset threshold are selected as matching results.

[0062] The system uses AIS signals to obtain the speed and route density of nearby ships in real time. The AIS receiver decodes the dynamic information of surrounding ships and calculates the average ship speed in the current sea area and the number of ships per unit area.

[0063] The expected duration of each navigation maneuver in each navigation segment is calculated by combining the historical duration of navigation maneuvers in the matched reference navigation segment with the current vessel density and average speed in the sea area. In implementation, a weighted average approach can be used to combine the historical duration with the current navigation environment factors to obtain a more accurate estimate of the expected duration.

[0064] Based on the calculated expected duration, the navigation sequence for each navigation section in the target navigation area is determined, generating navigation mission data. For example, the expected duration of each navigation action is accumulated to obtain the estimated transit time for each navigation section, thus forming a complete navigation sequence.

[0065] Through the above technical solution, this application can generate more accurate navigation timing for the target navigation mission based on historical navigation data and the real-time navigation environment. This improves the accuracy and reliability of the navigation plan, helping to optimize the ship's navigation efficiency and safety. Furthermore, by integrating the real-time navigation environment information provided by AIS signals, this solution can dynamically adjust the navigation timing, allowing the navigation plan to better adapt to actual changes in sea conditions.

[0066] Furthermore, three types of preset navigation key points are extracted from the electronic nautical chart, including turning points, intersection points and narrow channel points; the real-time position and navigation track of neighboring ships are obtained based on AIS signal decoding, and the coordinate points that overlap with the tracks of neighboring ships are screened out as high-priority navigation key points; based on the navigation timing of each navigation section, combined with the ship dynamics model and the real-time ocean current data provided by the AIS signal, the earliest arrival time and latest departure time of the ship at each navigation key point are calculated to form a dynamic time window as the effective navigation window.

[0067] The turning point is defined as the coordinate point in the sea area where the ship needs to change its course. Its coordinates are extracted from the channel turning point data in the electronic nautical chart; the intersection point is determined by identifying the center points of the intersection area of ​​multiple channels marked on the electronic nautical chart; the narrow waterway point is obtained by measuring the width of the channel and screening the coordinate points of the narrow area that is smaller than the safety threshold.

[0068] The screening process of high-priority navigation key points is as follows: the real-time navigation trajectory coordinate point sequence of the adjacent ships is spatially superimposed with the three types of key points. When the trajectory segment intersects with the coordinate area where the key point is located, the point is marked as high priority.

[0069] The calculation of the dynamic time window further includes: predicting the earliest time the ship will arrive at the key point based on the vector synthesis result of the ship's current speed and the real-time current speed; and calculating the latest departure time by combining the ship's maximum turning rate and the current disturbance error.

[0070] In some embodiments, when a vessel approaches a turning point, the electronic chart extracts the coordinates of that point as 35°12'N, 129°45'E. At this point, AIS signal decoding reveals that the trajectory segments of three neighboring vessels overlap within a 500-meter radius of the turning point, triggering spatial overlap detection logic and marking the turning point as high priority. The vessel's dynamics model, based on a current speed of 12 knots, a current of 2 knots, and a 30° angle with the heading, calculates the earliest arrival time to be 15 minutes later and the latest departure time to be 15 minutes and 30 seconds later, creating a valid navigation window from 3:00 PM to 3:30 PM. During this window, the radar scanning strategy automatically increases the scanning frequency of the turning point to 2 scans per second to ensure that surrounding obstacles are detected before the vessel executes the turn. When the current speed increases to 3 knots due to real-time data updates, the system recalculates the window time to 2:55 PM to 3:25 PM, dynamically adapting to environmental changes.

[0071] Three types of pre-set navigation key points are extracted from electronic nautical charts: turning points can be used at bends in a route or when avoiding obstacles. Intersection points can be located at port entrances or at the intersection of waterways. Narrow channel points can be located at narrow straits or rivers.

[0072] Furthermore, the real-time position and navigation track of nearby ships are obtained based on AIS signal decoding. Specifically, the AIS receiver receives the AIS signal sent by the nearby ship and parses the ship's MMSI number, latitude and longitude coordinates, heading angle, speed and other information.

[0073] Among these, coordinate points that overlap with nearby ship trajectories are selected from turning points, intersections, and narrow channel points as high-priority navigation key points. For example, if a turning point has another ship's predicted trajectory within 500 meters, the turning point is marked as high priority.

[0074] Based on the navigation timing of each navigation section, combined with the ship dynamics model and the real-time ocean current data provided by the AIS signal, the earliest arrival time and the latest departure time of the ship at each navigation key point are calculated to form a dynamic time window as the effective navigation window. The specific steps include:

[0075] By using the ship dynamics model and considering the ship's acceleration performance, steering performance, etc., the shortest time from the current position to the navigation key point is calculated.

[0076] The calculation results are corrected by combining the real-time ocean current speed and direction data provided by the AIS signal.

[0077] Considering the navigation safety margin, a certain margin is added to the shortest time to obtain the earliest arrival time.

[0078] Based on the latest arrival time required by the navigation mission and combined with the safety margin, the latest departure time is determined.

[0079] The earliest arrival time and the latest departure time constitute the effective navigation window of the navigation key point.

[0080] Furthermore, the pre-established navigation monitoring requirements are obtained, and the monitoring type information and risk level of each navigation key point in the navigation monitoring requirements are extracted; the monitoring type information and risk level are used to match the radar scanning distance and scanning frequency of each navigation key point in the preset signal feature mapping table and risk level mapping table respectively; the ship density distribution is analyzed in real time based on the AIS signal, and the matched radar scanning distance interval is dynamically adjusted: the lower limit of the scanning distance interval is reduced in areas with high ship density; the effective navigation window of each navigation key point is analyzed, and the scanning path sequence for synchronously collecting radar signals and AIS signals is generated with the adjusted radar scanning distance interval and scanning frequency interval as constraints.

[0081] The signal feature mapping table stores the radar signal propagation characteristic parameters corresponding to different monitoring types, such as target recognition monitoring corresponding to medium and short-range scanning, and environmental perception monitoring corresponding to long-range scanning; the risk level mapping table defines the minimum scanning frequency corresponding to different risk levels, for example, high-risk areas need to be scanned once a minute.

[0082] The ship density distribution is calculated by clustering the ship position coordinates in AIS signals. When the number of ships per unit sea area exceeds a threshold, it is identified as a high-density area. During the scan path sequence generation process, a greedy algorithm is used to select scan points that meet the scanning distance and frequency requirements within the time window constraints and insert AIS signal acquisition nodes.

[0083] For example, the navigation monitoring requirements define turning points as requiring high-precision target identification monitoring, corresponding to a medium-range scanning interval of 8-12 nautical miles in the signal signature map. When AIS signal analysis indicates a vessel density of three vessels per square nautical mile near the turning point, the system adjusts the lower limit of the scanning interval from 8 nautical miles to 5 nautical miles. Furthermore, the risk level map matches the high-risk level with a scanning frequency of 1-2 scans per minute. Calculation of the effective navigation window indicates the vessel will pass the turning point between 2:00 PM and 2:15 PM. The system generates a scanning path starting at 2:05 PM, performing radar scans at a frequency of 1.5 scans per minute within a range of 5-12 nautical miles, and inserting AIS signal collection nodes at 2:04 PM and 2:06 PM. By dynamically compressing the lower limit of the scanning interval, radar beam focusing is improved in densely populated areas, reducing target position comparison error from 30 meters to 8 meters while maintaining a time alignment accuracy of ±2 seconds between the AIS signal and the radar scan.

[0084] In some embodiments, the monitoring type for turning points is set to "close-range monitoring" and the risk level is "high"; the monitoring type for intersection points is set to "medium-range monitoring" and the risk level is "medium"; the monitoring type for narrow waterway points is set to "long-range monitoring" and the risk level is "low".

[0085] Using monitoring type information and risk level, the radar scanning distance and scanning frequency of each navigation key point are matched in the preset signal feature mapping table and risk level mapping table. Specifically, the corresponding radar scanning distance for close-range monitoring is 0-5 nautical miles, for medium-range monitoring is 5-10 nautical miles, and for long-range monitoring is 10-20 nautical miles. The corresponding scanning frequency for high-risk level is 6-10 times per minute, for medium risk level is 3-5 times per minute, and for low risk level is 1-2 times per minute.

[0086] Based on real-time analysis of vessel density distribution based on AIS signals, the matching radar scanning range is dynamically adjusted: the lower limit of the scanning range is reduced in areas with high vessel density. For example, if there are more than 10 vessels within 5 nautical miles of a key navigation point, the lower limit of the scanning range for that point is reduced by 20%.

[0087] By analyzing the effective navigation window for each navigation key point, and using the adjusted radar scanning range and scanning frequency range as constraints, a scanning path sequence is generated to simultaneously acquire radar and AIS signals. Furthermore, a genetic algorithm can be used to optimize the scanning path, with the objective function of minimizing scanning time while satisfying the range and frequency constraints.

[0088] Furthermore, a dynamic sea state model of the target navigation area is constructed, integrating electronic chart data, real-time AIS ship position data and meteorological data. Based on the adjusted radar scanning distance interval of each navigation key point, a circular monitoring area centered on the navigation key point is generated in the dynamic sea state model. The scanning speed parameters of the ship radar are obtained, and the radar scanning path is generated with the circular monitoring area as the spatial constraint and the effective navigation window as the temporal constraint. AIS signal acquisition nodes are inserted into the radar scanning path to ensure that each navigation key point synchronously acquires AIS signals within a preset time before and after the radar scan. The optimal scanning point sequence is solved with the time interval between adjacent scanning points in the scanning path satisfying the scanning frequency interval as the first constraint and the position synchronization error between the radar and AIS signals as the optimization goal.

[0089] The dynamic sea condition model forms a multi-dimensional set of environmental parameters by integrating the basic geographic information of electronic charts, the real-time position of AIS ships, and the wave height and wind speed in meteorological data; the circular monitoring area expands outward from the navigation key point, and the radius is determined by the adjusted radar scanning distance interval; the generation of the radar scanning path needs to be combined with the radar's scanning speed parameters to plan the scanning trajectory covering the circular monitoring area within the time range of the effective navigation window.

[0090] The insertion position of the AIS signal acquisition node is reverse-calculated based on the time nodes of the radar scanning path to ensure that the time difference between the radar scanning action and the AIS signal acquisition action does not exceed the preset threshold. The optimal scanning point sequence is solved using a dynamic programming algorithm. Under the constraints of the scanning frequency interval, all possible scanning point combinations are traversed to screen out the sequence with the smallest position synchronization error.

[0091] More specifically, the system first obtains geographic information about the target navigation area from an electronic nautical chart database, including static information such as water depth, channel, and reefs. It then receives real-time ship dynamic information broadcast by AIS base stations and parses it to obtain data such as the position, heading, and speed of surrounding vessels. Simultaneously, it obtains real-time meteorological data such as wind speed, wave height, and visibility from the meteorological service. This data is integrated into a unified coordinate system to construct a dynamic model reflecting current sea conditions.

[0092] Furthermore, for each identified navigation key point, a circular monitoring area centered on that point is generated in the dynamic sea state model based on the adjusted radar scanning range. For example, if the scanning range of a navigation key point is 3-5 nautical miles, a circular area with an inner diameter of 6 nautical miles and an outer diameter of 10 nautical miles is generated.

[0093] From this, the ship's radar's scanning speed parameters are obtained, such as 30 degrees per second. Using the circular monitoring area as a spatial constraint and the effective navigation window of the navigation key point as a temporal constraint, a radar scanning path is generated. Specifically, a spiral scanning method can be used, gradually expanding the scanning range from the inside out.

[0094] In the generated radar scanning path, AIS signal collection nodes are inserted at regular intervals or angles. For example, an AIS collection point is inserted every 90 degrees of scanning to ensure that AIS signals can be synchronously collected within 10 seconds before and after the radar scans the area.

[0095] Finally, the first constraint is that the time interval between adjacent scanning points in the scanning path must meet a preset scanning frequency range, for example, the interval between each scanning point must be no less than 1 second and no more than 3 seconds. Furthermore, with minimizing the synchronization error between the radar scanning position and the AIS signal acquisition position as the optimization goal, a particle swarm algorithm is used to solve the optimal scanning point sequence, resulting in a detailed radar scanning strategy.

[0096] Furthermore, the signal acquisition position and signal acquisition time of each scanning point in the optimal scanning point sequence are extracted; the heading angle adjustment is calculated based on the current ship position and the position of the next scanning point; the speed adjustment is calculated based on the current ship speed and the required time to reach the next scanning point; at the same time, based on the timing requirements of the AIS signal acquisition node, an AIS receiver start instruction is generated; the heading angle adjustment, speed adjustment and AIS receiver start instruction are combined to form a ship control instruction set.

[0097] The heading angle adjustment is calculated by the difference in longitude and latitude between the ship's current position and the next scan point, using spherical trigonometry to determine the heading deviation angle. The speed adjustment is calculated using a linear programming solution based on the difference between the ship's current speed and the remaining time to reach the next scan point, combined with the acceleration limit of the ship's power system. The generation time of the AIS receiver start command must meet the preset time window before and after the radar scan. For example, AIS reception should be started 5 seconds before the radar scan to ensure signal synchronization.

[0098] Specifically, the signal acquisition positions and times of scanning points are extracted based on an optimized scanning path sequence, ensuring that each scanning point is aligned with the effective navigation window of key navigation points. The heading angle adjustment is calculated using a conversion matrix between the ship's coordinate system and the geographic coordinate system to eliminate angular errors caused by ocean current drift. The speed adjustment is dynamically corrected via a real-time feedback control algorithm. When the deviation between the ship's actual position and the expected trajectory exceeds a threshold, the speed compensation mechanism is triggered. The timing synchronization between the AIS receiver startup command and the radar scanning action is achieved through a hardware clock signal, embedding the AIS signal acquisition node within the radar scanning cycle, for example, inserting an AIS signal acquisition node every two radar scans. Thus, the ship control instruction set integrates heading, speed, and signal acquisition actions into a unified instruction stream, which is transmitted to the ship control system via the CAN bus, ensuring that the synchronization error between the ship's motion trajectory and the signal acquisition timing is controlled within 10 meters.

[0099] In some embodiments, generating a vessel control instruction comprises the following steps:

[0100] First, the signal acquisition location and time of each scan point are extracted from the optimal scan point sequence. For example, for a scan point, its signal acquisition location is 121.5°E longitude and 31.2°N latitude, and the signal acquisition time is 10:00:00 on July 1, 2023.

[0101] Next, the heading angle adjustment is calculated based on the current ship position and the next scan point. Specifically, the desired heading is obtained by calculating the azimuth between the two points. The heading angle adjustment is then subtracted from the current heading to obtain the heading angle adjustment. For example, if the current heading is 45° and the desired heading is 60°, the heading angle adjustment is 15°.

[0102] Furthermore, a speed adjustment is calculated based on the current ship speed and the required time to reach the next scan point. Specifically, the desired speed is calculated by dividing the distance between the two points by the remaining time. The speed adjustment is then subtracted from the current speed. For example, if the current speed is 10 knots and the desired speed is 12 knots, the speed adjustment is 2 knots.

[0103] At the same time, based on the timing requirements of the AIS signal collection node, an AIS receiver startup instruction is generated. For example, the AIS receiver is started 30 seconds before the next scanning point arrives.

[0104] Finally, the heading angle adjustment, speed adjustment, and AIS receiver activation command are combined to form a ship control command set. For example, a command set might be generated that reads "adjust heading 15°, increase speed 2 knots, and activate AIS receiver after 30 seconds."

[0105] Furthermore, when the position deviation value between the radar and AIS signals continuously exceeds the threshold, data update is triggered; the real-time motion status of the adjacent ship is obtained based on the AIS signal, and the time consumption of the ship's avoidance action is recalculated; based on the recalculated time consumption data, the effective navigation window of subsequent navigation key points is dynamically adjusted; and the radar navigation strategy is regenerated using the adjusted effective navigation window.

[0106] Data updates are triggered when the positional deviation between the radar and AIS signals consistently exceeds a preset threshold. This threshold is dynamically set based on vessel size and speed. For a 200-meter-long vessel traveling at 15 knots, the threshold is set at 25 meters. If the positional deviation between the radar and AIS signals exceeds the threshold five times in a row, the system automatically triggers a data update. First, the MMSI number of the adjacent vessel is parsed from the AIS signal to extract its real-time speed and heading. Combined with the vessel's own inertial navigation data, the steering angle and deceleration required for avoidance are calculated. The ship's dynamics model is used to simulate the time required for different avoidance maneuvers. For example, a full-speed reverse maneuver takes 40 seconds longer than a half-speed reverse. The updated time data is fed into the navigation timing calculation module, which then shifts the effective navigation window for each subsequent key navigation point. For example, a turning point originally scheduled for 10:00 a.m. is now shifted to 10:00-10:03 a.m. The adjusted effective navigation window data is passed to the radar scan path planning module, which regenerates a circular monitoring area centered on the high-priority navigation key point and increases the scan frequency lower limit from 2 to 3 times per minute. At the same time, additional AIS signal collection nodes are inserted into the radar scan path, reducing the AIS signal collection interval at each navigation key point from 30 seconds to 15 seconds, ensuring that the temporal and spatial synchronization error is controlled within 10 meters.

[0107] Preferably, a data update is triggered when the position deviation between the radar and AIS signals exceeds a threshold for a sustained period. For example, the position deviation threshold is set to 50 meters. If the deviation between the radar target and the corresponding AIS vessel position exceeds 50 meters for five consecutive times, the update process is initiated.

[0108] The system uses AIS signals to obtain the real-time motion status of neighboring vessels and recalculate the time required for the vessel's avoidance maneuver. Specifically, it analyzes the vessel's speed, heading, and other data from the AIS signal, combines this with the vessel's dynamic model, simulates the avoidance process, and estimates the time required. For example, in a crossing situation, the system calculates the execution time for a 90-degree avoidance maneuver.

[0109] Based on the recalculated time data, the effective navigation window of subsequent navigation key points is dynamically adjusted. Furthermore, the updated avoidance time is fed into the original time window calculation model to regenerate the earliest arrival time and latest departure time of each navigation key point.

[0110] The radar navigation strategy is regenerated using the adjusted effective navigation window. The radar scanning path and AIS signal acquisition nodes are re-optimized using the updated time window as a constraint, generating a new set of ship control instructions.

[0111] Furthermore, navigation risk assessment is performed based on the collected radar signals and AIS signals, including: performing clutter suppression processing on the radar echo signal to extract the outline features and motion vector of the target ship; decoding the AIS signal to obtain the MMSI number, ship position coordinates, heading angle and speed of the adjacent ship; performing spatiotemporal matching between the target ship outline extracted by the radar and the ship position decoded by the AIS: including performing nearest neighbor matching on the position coordinates of the radar target and the AIS ship; including calculating the position deviation distance between the successfully matched radar target and the AIS ship; performing three-level risk assessment: including generating an identity authentication alarm when the position deviation distance is greater than a first threshold; including generating a hidden ship alarm when the radar detects a ship target that does not match the AIS signal; including generating a signal failure alarm when the AIS signal exists but the radar does not detect a matching target.

[0112] Clutter suppression utilizes an adaptive filtering algorithm, using Doppler shift analysis to distinguish wave reflections from true ship echoes, reducing interference from false targets. During AIS signal decoding, the MMSI number and heading angle are preferentially extracted to establish a vessel identity database. During the spatiotemporal matching phase, a Euclidean distance algorithm is used to calculate the coordinate difference between the radar target and the AIS vessel. A threshold of 50 meters is set, and when the deviation exceeds this value, the identity verification process is triggered. Hidden vessel alarms are activated by comparing radar profile features with missing information in the database, while signal failure alarms are based on synchronization detection between the AIS message timestamp and the radar scanning cycle.

[0113] Specifically, after clutter suppression, the radar echo signal is filtered, and the target vessel's outline features are extracted using an edge detection algorithm. The motion vector is calculated by calculating the displacement between consecutive frames. The AIS decoding module parses the vessel's MMSI number in real time to form a dynamic identity list. During the spatiotemporal matching process, the radar target and the AIS vessel's position coordinates are associated using a nearest neighbor algorithm. For successfully matched pairs, their position deviation distance is calculated. For example, when the deviation exceeds 50 meters, the system generates an identity verification alarm, prompting the operator to manually verify the target's identity. For radar targets that do not match an AIS signal, the system determines whether they are hidden vessels based on their outline size and motion trajectory, triggering a level 2 alarm. If an AIS signal is present but the radar does not detect the target at the corresponding coordinates, the signal is deemed to be invalid, triggering a level 3 alarm. This solution reduces the position comparison error of traditional methods from hundreds of meters to within 10 meters, reduces the identity misassociation rate by 60%, and shortens the alarm response delay to less than 5 seconds.

[0114] As a preferred embodiment, the solution of this application is specifically implemented as follows:

[0115] During the navigation risk assessment process, the radar echo signal first undergoes clutter suppression using an adaptive filtering algorithm to eliminate interference signals caused by surface wave reflections and extract the target vessel's outline and motion vector. Simultaneously, the AIS receiver decodes the received message to obtain the MMSI number, vessel position coordinates, heading angle, and speed data of nearby vessels. During the spatiotemporal matching phase, a nearest neighbor matching algorithm is used to correlate the center coordinates of the radar-detected vessel outline with the AIS vessel position coordinates, calculating the Euclidean distance between the two as the position deviation. If the position deviation exceeds 50 meters, an authentication alarm is generated, prompting the operator for manual confirmation. If the radar detects a vessel outline but does not match any AIS signal, a hidden vessel alarm is generated. If an AIS signal is present but the radar does not detect the corresponding target within the preset scanning period, a signal failure alarm is generated.

[0116] Furthermore, the risk judgment threshold is dynamically adjusted based on the real-time ship density and heading change rate, and the emergency collision avoidance plan is triggered when the heading changes suddenly.

[0117] Specifically, when a vessel enters a high-density area, AIS signals are used to analyze the position coordinates of neighboring vessels in real time, count the number of vessels per unit area, and calculate the current density. If the density exceeds a critical value, the threshold for the identity verification alarm is proportionally reduced, for example, from 50 meters to 30 meters. This increases the accuracy of the radar and AIS position matching and reduces misjudgments caused by overlapping positions of densely packed vessels. Simultaneously, the threshold for the hidden vessel alarm is proportionally increased, for example, from 100 meters to 150 meters, expanding the radar's independent detection range and reducing the probability of missed detection of vessels without AIS enabled. If the heading angle of a neighboring vessel changes at a rate exceeding 20 degrees per second between two consecutive AIS message cycles, it is determined to be a sudden change in heading, triggering an emergency collision avoidance plan. This generates instructions to decelerate to a safe speed and plans a temporary route to avoid the sudden change in heading. Through dynamic threshold adjustment and a plan triggering mechanism, the delay in emergency collision avoidance response is kept within 5 seconds while ensuring accurate risk assessment.

[0118] Furthermore, real-time wave height and wind speed data are decoded from the AIS signal. The radar scanning distance interval is adjusted based on the wave height data: when the wave height is greater than the set value, the lower limit of the scanning distance interval is increased. The scanning frequency interval is adjusted based on the wind speed data: when the wind speed is greater than the set value, the lower limit of the scanning frequency interval is increased. The radar scanning path is regenerated based on the adjusted parameters, and the frequency of AIS signal collection is increased in high wave height areas.

[0119] During implementation, real-time wave height data is obtained by parsing the environmental information field in the AIS message, and the set value is preset to 3 meters based on the ship's tonnage and radar performance. When the wave height exceeds 3 meters, the lower limit of the radar scanning distance interval is extended from 500 meters to 800 meters to cover a wider range of sea surface reflection interference areas. Real-time wind speed data is extracted through the weather broadcast message in the AIS signal, and the set value is set to 15 meters per second based on the ship's wind resistance level. When the wind speed exceeds 15 meters per second, the lower limit of the scanning frequency interval is increased from 2 times per minute to 4 times per minute to enhance the continuity of moving target tracking. The adjusted radar scanning path is recalculated through the path planning algorithm to ensure that the scanning point sequence meets the expanded distance and frequency constraints at the same time. In high wave height areas, the AIS signal acquisition frequency is adjusted from once every 5 minutes to once every 2 minutes, and signal synchronization errors are reduced through timestamp alignment.

[0120] More specifically, when a vessel enters an area of ​​high wave height, the AIS signal decoding module extracts real-time wave height data. If the wave height exceeds 3 meters, it triggers a scanning range interval adjustment command, increasing the radar scanning range lower limit from 500 meters to 800 meters, expanding the monitoring range to offset blind spots caused by wave reflections. Simultaneously, if the wind speed data decoding module detects wind speeds exceeding 15 meters per second, it sends a scanning frequency increase command to the radar control system, adjusting the scanning frequency lower limit to 4 scans per minute and shortening the scanning interval to capture fast-moving vessel targets. These adjusted scanning parameters are input into the dynamic sea state model, regenerating a circular monitoring area centered on the navigation keypoint. A new radar scanning path is then generated using a path optimization algorithm to ensure that the scanning points cover the expanded monitoring area. In high wave areas, the AIS receiver simultaneously increases the signal acquisition frequency, shortening the acquisition interval to compensate for any signal delay caused by the extended radar scanning range, keeping the position synchronization error between the radar and AIS signals within 10 meters. For example, when the wave height is 4 meters and the wind speed is 18 meters per second, the lower limit of the radar scanning distance is adjusted to 800 meters, the lower limit of the scanning frequency is increased to 4 times per minute, and the AIS collection frequency is increased to once every 2 minutes. The scanning path generated in this way synchronously adapts to the dynamic environment in the time and space dimensions, effectively reducing the target missed detection rate and misjudgment rate in high sea conditions.

[0121] Through the above technical solution, this application effectively solves the problems of detection blind spots and data synchronization errors caused by the rigid scanning parameters of traditional radar navigation under dynamic sea conditions. By sensing wave height and wind speed data in real time and dynamically adjusting the radar scanning distance and frequency, the stability of target detection under complex weather conditions is enhanced. At the same time, by increasing the frequency of AIS signal acquisition in high-wave areas, accurate spatiotemporal matching of radar and AIS data is achieved, reducing navigation risk judgment errors caused by sudden environmental changes, and significantly improving the safety of ships navigating in high-sea conditions.

[0122] The above description is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, various modifications and variations of the present application are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A marine radar navigation method based on AIS signals, characterized in that: include: Acquiring navigation mission data, the navigation mission data including a number of navigation sections in the target navigation area, a number of navigation actions in each navigation section, and a navigation time sequence for each navigation section; Based on a number of navigation actions of each navigation section and a navigation timing of each navigation section, a number of navigation key points of the target navigation area and an effective navigation window of each navigation key point are determined; Extract the monitoring type information and risk level of each navigation key point in the pre-defined navigation monitoring requirements, analyze the effective navigation window of each navigation key point, use the radar scanning range interval corresponding to the monitoring type information and the scanning frequency interval corresponding to the risk level as constraints, and take the minimum navigation error as the optimization goal to optimize the radar navigation strategy for the target navigation area; Generate ship control instructions to the ship based on the radar navigation strategy, control the ship to execute the corresponding navigation action, collect radar signals and AIS signals, and perform navigation risk assessment based on the fused radar and AIS signals; After the ship completes each navigation action, the navigation execution status is obtained, the navigation mission data is updated based on the navigation execution status, and the radar navigation strategy is regenerated using the updated navigation mission data.

2. The AIS signal-based ocean radar navigation method according to claim 1, characterized in that: Obtaining navigation mission data includes: Obtaining historical navigation data of the ship, and extracting the historical navigation time of each navigation action in different reference navigation sections from the historical navigation data of the ship; Obtain target navigation mission parameters, extract a plurality of navigation sections in the target navigation sea area and a plurality of navigation actions for each navigation section recorded in the target navigation mission parameters; Based on the similarity matching between the reference navigation section and the navigation environment characteristics of each navigation section in the target navigation sea area, a number of reference navigation sections with navigation environment characteristics similarity higher than the target value are matched for each navigation section; The navigation speed and route density of neighboring ships are obtained in real time based on AIS signals. The expected navigation time of each navigation action in each navigation section is calculated by combining the historical navigation time of each navigation action in several reference navigation sections with matching relationships in each navigation section. Based on the expected time consumption of each navigation action in each navigation section, the navigation timing of each navigation section in the target navigation area is determined and the navigation mission data is generated.

3. The AIS signal-based ocean radar navigation method according to claim 1, characterized in that: Determine several key navigation points in the target navigation area and the effective navigation window for each key navigation point, including: Extract three types of preset navigation key points from electronic nautical charts: Including turning point: the coordinate point in the sea area where the ship needs to change its course; Including intersection points: coordinate points in the sea area where multiple channels intersect; Including narrow waterway points: coordinate points in narrow sea areas where the channel width is less than the safety threshold; The real-time position and navigation track of neighboring ships are obtained based on AIS signal decoding. Coordinate points that overlap with the tracks of neighboring ships at turning points, intersections, and narrow waterways are selected as high-priority navigation key points. Based on the navigation timing of each navigation section, combined with the ship dynamics model and the real-time ocean current data provided by the AIS signal, the earliest arrival time and latest departure time of the ship at each navigation key point are calculated to form a dynamic time window as the effective navigation window.

4. The AIS signal-based ocean radar navigation method according to claim 1, characterized in that: Optimizing the radar navigation strategy for the target navigation area includes: Obtain pre-established navigation monitoring requirements and extract the monitoring type information and risk level of each key navigation point in the navigation monitoring requirements; Using the monitoring type information and risk level, the radar scanning distance and scanning frequency of each navigation key point are matched in the preset signal feature mapping table and risk level mapping table respectively; Based on real-time analysis of ship density distribution based on AIS signals, the matching radar scanning range interval is dynamically adjusted: the lower limit of the scanning range interval is reduced in areas with high ship density; The effective navigation window of each navigation key point is analyzed, and the scanning path sequence for synchronously collecting radar signals and AIS signals is generated with the adjusted radar scanning distance interval and scanning frequency interval as constraints.

5. The AIS signal-based ocean radar navigation method according to claim 4, characterized in that: Optimizing the radar navigation strategy for the target navigation area also includes: Build a dynamic sea condition model of the target navigation area, integrating electronic chart data, real-time AIS ship position data and meteorological data; Based on the adjusted radar scanning range of each navigation key point, a circular monitoring area centered on the navigation key point is generated in the dynamic sea state model; Obtain the scanning speed parameters of the ship radar, generate the radar scanning path with the circular monitoring area as the spatial constraint and the effective navigation window as the time constraint; Insert AIS signal acquisition nodes into the radar scanning path to ensure that each navigation key point synchronously acquires AIS signals within the preset time before and after the radar scan; The first constraint is that the time interval between adjacent scanning points in the scanning path satisfies the scanning frequency interval, and the optimization goal is to minimize the position synchronization error between the radar and AIS signals to solve the optimal scanning point sequence.

6. The AIS signal-based ocean radar navigation method according to claim 5, characterized in that: Generates ship control instructions, including: Extract the signal acquisition position and signal acquisition time of each scanning point in the optimal scanning point sequence; Calculate the heading angle adjustment based on the current ship position and the next scan point position; Calculate the speed adjustment based on the current ship speed and the required time to reach the next scanning point; At the same time, based on the timing requirements of the AIS signal acquisition node, an AIS receiver startup instruction is generated; The heading angle adjustment amount, speed adjustment amount and AIS receiver start-up command are combined to form a ship control command set.

7. The AIS signal-based ocean radar navigation method according to claim 1, characterized in that: Updated navigation mission data, including: When the position deviation between the radar and AIS signals exceeds the threshold continuously, data update is triggered; Obtain the real-time motion status of adjacent ships based on AIS signals and recalculate the time required for ship avoidance actions; Dynamically adjust the effective navigation window of subsequent navigation key points based on the recalculated time-consuming data; Regenerate the radar navigation strategy using the adjusted effective navigation window.

8. The AIS signal-based ocean radar navigation method according to claim 1, characterized in that: Navigation risk assessment is performed based on collected radar and AIS signals, including: Perform clutter suppression on radar echo signals to extract the target ship's contour features and motion vector; Decode the AIS signal to obtain the MMSI number, ship position coordinates, heading angle and speed of the nearby ship; Perform spatiotemporal matching between the target ship profile extracted by radar and the ship position decoded by AIS: Including nearest neighbor matching of radar targets and AIS ship position coordinates; Including calculating the position deviation distance between the successfully matched radar target and the AIS ship; Execute three-level risk assessment: including generating an identity authentication alert when the position deviation distance is greater than a first threshold; This includes generating a hidden ship alarm when the radar detects a ship target that does not match the AIS signal; This includes generating a signal failure alarm when an AIS signal is present but no matching target is detected by the radar.

9. The AIS signal-based ocean radar navigation method according to claim 8, characterized in that: The risk assessment also includes dynamic threshold adjustment: Calculate the ship density value of the current sea area in real time based on AIS signals; Dynamically adjust the risk judgment threshold based on the ship density value: This includes proportionally reducing the authentication alert threshold when the ship density exceeds a critical value; This includes proportionally increasing the hidden ship alarm threshold when the ship density falls below a critical value; At the same time, the heading change rate of the adjacent ship is obtained based on the AIS signal. When the heading change rate exceeds the preset value, the emergency collision avoidance plan is triggered.

10. The AIS signal-based ocean radar navigation method according to claim 5, characterized in that: Optimizing the radar navigation strategy for the target navigation area also includes: Decode real-time wave height and wind speed data from AIS signals; Adjust the radar scanning range based on wave height data: Including increasing the lower limit of the scanning distance range when the wave height is greater than the set value; Adjust the scanning frequency range based on wind speed data: Including increasing the lower limit of the scanning frequency range when the wind speed is greater than the set value; The radar scan path is regenerated based on the adjusted parameters, and the AIS signal collection frequency is increased in high wave areas.

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