Sea surface navigation recognition processing method and system fusing multi-dimensional data

Abstract

The application discloses a sea surface navigation recognition processing method and system fusing multi-dimensional data, and belongs to the field of intelligent control, which comprises the following steps: an interactive control center reads basic data; based on the basic data, a navigation map is called to construct an initial trajectory map; sea surface data is collected to construct a real-time data set; after the initial trajectory map is positioned, compensation is made, the initial trajectory map is updated into an adjusted trajectory map, and a range area is divided according to the map features of the adjusted trajectory map; if it is necessary to change the navigation route, the trajectory of a target ship is adjusted and optimized, and the multi-round optimization results corresponding to the range area are aggregated; a trajectory adjustment result is generated according to the aggregation result, and navigation control of the target ship is performed based on the trajectory adjustment result. The application solves the technical problem that the sea surface environment cannot be dynamically and accurately recognized and the ship cannot be controlled to navigate in the prior art, and achieves the technical effects of accurately recognizing the sea surface environment and dynamically controlling the ship to navigate, improving the navigation efficiency and safety.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control, and in particular to a method and system for identifying and processing sea surface navigation by integrating multi-dimensional data. Background Art

[0002] Throughout the development of ocean navigation technology, the ocean surface environment has become incredibly complex and dynamic, with features such as waves, wind direction, currents, and various obstacles making navigation highly uncertain. Existing ocean navigation control technologies typically rely on static baseline data and predetermined navigation plans. These technologies are unable to accurately identify and dynamically control real-time changes in the ocean surface environment, resulting in low navigation efficiency and increased accident risks. Summary of the Invention

[0003] This application aims to solve the technical problem that the existing technology cannot dynamically and accurately identify the sea surface environment and control the navigation of ships by providing a sea surface navigation identification and processing method and system that integrates multi-dimensional data.

[0004] In view of the above problems, the present application provides a method and system for sea surface navigation identification and processing that integrates multi-dimensional data.

[0005] The first aspect disclosed in the present application provides a method for sea surface navigation identification and processing that integrates multi-dimensional data, the method comprising: an interactive control middle station to read basic data of a target vessel, wherein the basic data includes vessel attribute data and navigation planning data; based on the basic data, calling a navigation map to construct an initial trajectory map; calling the vessel sensor of the target vessel to collect sea surface data to construct a real-time data set, wherein the real-time data set includes position data and image data; positioning and compensating the initial trajectory map through the real-time data set, updating the initial trajectory map to an adjusted trajectory map, and dividing N levels of range areas according to the map features of the adjusted trajectory map; judging whether to change the navigation route based on the adjusted trajectory map, and if the navigation route needs to be changed, optimizing the trajectory of the target vessel through the N levels of range areas respectively, and aggregating multiple rounds of optimization results corresponding to the N levels of range areas; generating a trajectory adjustment result based on the aggregation result, and executing navigation control of the target vessel based on the trajectory adjustment result.

[0006] Another aspect disclosed herein provides a surface navigation identification and processing system for integrating multidimensional data, the system comprising: a basic information reading module for interactively controlling a middle platform and reading basic data of a target vessel, wherein the basic data includes vessel attribute data and navigation planning data; an initial trajectory map module for calling a navigation map based on the basic data to construct an initial trajectory map; a real-time data collection module for calling a target vessel's vessel sensor to collect surface data and construct a real-time data collection, wherein the real-time data collection includes position data and image data; a range area division module for positioning and compensating the initial trajectory map using the real-time data collection, updating the initial trajectory map to an adjusted trajectory map, and dividing the range areas into N levels based on the map features of the adjusted trajectory map; a trajectory adjustment optimization module for determining whether to change the navigation route based on the adjusted trajectory map, and if the navigation route needs to be changed, optimizing the trajectory of the target vessel through the N levels of range areas, respectively, and aggregating multiple rounds of optimization results corresponding to the N levels of range areas; and a navigation control execution module for generating a trajectory adjustment result based on the aggregated result, and executing navigation control of the target vessel based on the trajectory adjustment result.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] By reading basic data through an interactive control system and calling on-board sensors to collect sea surface data in real time, the static and dynamic information of the sea surface can be obtained, and the collection and fusion of sea surface data can be realized; the collected data are integrated to build an initial environmental model, and dynamic tracking modeling of environmental changes is realized through positioning and compensation, and the construction of a sea surface environment model is realized; multiple rounds of navigation route optimization and aggregation are carried out in different range areas to generate real-time response plans for environmental changes and realize dynamic optimization of navigation routes; intelligent control of target ships is implemented according to the optimization results, and real-time response to changes in the sea surface environment is completed to realize the technical solution of intelligent ship control, which solves the technical problem that the existing technology cannot dynamically and accurately identify the sea surface environment and control the navigation of ships. Sea surface navigation identification is realized through multi-dimensional data fusion, achieving the technical effect of accurately identifying the sea surface environment and dynamically controlling ship navigation, improving navigation efficiency and safety.

[0009] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A possible flow chart of a method for identifying and processing sea navigation by fusing multi-dimensional data is provided for an embodiment of the present application;

[0011] Figure 2 A schematic flow chart of possible aggregation results obtained in a method for processing sea navigation identification by fusing multidimensional data is provided for an embodiment of the present application;

[0012] Figure 3 A schematic diagram of a possible flow chart of trajectory compensation of trajectory adjustment results in a method for identifying and processing sea navigation data that integrates multi-dimensional data is provided for an embodiment of the present application;

[0013] Figure 4 A possible structural diagram of a surface navigation identification and processing system that integrates multi-dimensional data is provided for an embodiment of the present application.

[0014] Explanation of reference numerals: basic information reading module 11 , initial trajectory map module 12 , real-time data collection module 13 , range area division module 14 , trajectory adjustment and optimization module 15 , navigation control execution module 16 . DETAILED DESCRIPTION

[0015] The overall idea of ​​the technical solution provided by this application is as follows:

[0016] The embodiments of the present application provide a method and system for identifying and processing sea surface navigation by integrating multidimensional data. By collecting and deeply integrating multi-source sea surface data, including static basic data, dynamic sensor data, and geospatial data, an initial model of the sea surface environment is constructed and positioning and compensation are implemented to form a dynamic model of environmental changes. Based on this dynamic environmental model, different range areas are divided, and multiple rounds of trajectory optimization and aggregation are performed within each range area to generate a real-time adjustment plan for the navigation route. Finally, intelligent control of the ship is implemented according to the adjustment plan to achieve real-time response to changes in the sea surface environment.

[0017] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically introduced in conjunction with the drawings in the specification.

[0018] Example 1

[0019] like Figure 1 As shown, the embodiment of the present application provides a method for identifying and processing sea navigation by fusing multi-dimensional data, the method comprising:

[0020] Step S100: The interactive control center reads the basic data of the target vessel, wherein the basic data includes vessel attribute data and navigation planning data;

[0021] Specifically, in order to obtain the basic data of the target vessel, the middle station is interactively controlled through wireless communication, onboard computers, etc. to read the basic data of the target vessel. Among them, the basic data includes the attribute data of the target vessel and its navigation planning data. The vessel attribute data includes the specific type of vessel (such as cargo ship, passenger ship, etc.), size parameters (length, width, draft, etc.) and load information, etc., which are used for subsequent navigation planning and path optimization. The navigation planning data includes the starting port, destination port, and detailed route and speed information of each section of the target vessel, reflecting the overall navigation plan of the target vessel and providing a basic basis for subsequent navigation control and real-time path optimization.

[0022] The above basic data are read through the interactive control center to provide basic data for the intelligent navigation control of the target ship, and provide necessary information support for subsequent navigation map construction, path optimization and final navigation control.

[0023] Step S200: Based on the basic data, calling the navigation map to construct an initial trajectory map;

[0024] Specifically, based on the basic data of the target vessel, nautical map information is used to construct an initial track map. Nautical maps store topographical information of the relevant sea area, including coastline, water depth, channel location, navigation signs, and other data. By calling nautical maps through GIS software platforms, detailed geographical information of the target vessel's navigation area can be obtained. The nautical map information is expressed in the form of an electronic map, a map coordinate system is established, and the port location, planned channel, and other geographic element information are marked on the map. Then, based on the basic attributes of the vessel, an appropriate route type is selected, such as a great circle route, and the initial route and track are planned on the electronic nautical map.

[0025] By calling nautical maps based on basic data, map data management, editing and spatial analysis are achieved, and the initial track map of the target ship is finally output, providing a reference benchmark for subsequent real-time path planning and optimization.

[0026] Step S300: calling the ship sensor of the target ship to collect sea surface data and construct a real-time data set, wherein the real-time data set includes position data and image data;

[0027] Specifically, in order to obtain the real-time operating status of the target vessel and the surrounding sea surface environment information, the ship sensors installed on the target vessel are called to collect sea surface data and construct a real-time data set, which includes the real-time position data of the target vessel and the surrounding sea surface image data.

[0028] Vessel sensors, including satellite positioning sensors, radars, and cameras, are installed on target vessels and provide real-time awareness of their location and surrounding sea surface environment. The satellite positioning sensor receives satellite signals to obtain the target vessel's real-time latitude and longitude coordinates; the radar scans the surrounding sea surface to obtain the distance and direction of targets; and the camera captures video images of the sea surface surrounding the target vessel. The positioning, target, and image information collected by these vessel sensors form a real-time data set. Position data, obtained by the satellite positioning sensor, represents the target vessel's real-time spatial location; image data, obtained by the radar and camera, provides information about obstacles and the traffic environment in the sea area surrounding the target vessel.

[0029] By deploying sensor equipment on the target ship and establishing a sensor data acquisition system, real-time acquisition and processing of positioning signals, radar echoes and video images are achieved. The processed information is transmitted to the interactive control center via wired or wireless means, and a real-time data set is constructed to provide a real-time reference basis for subsequent track control and path planning, thereby achieving the purpose of accurately identifying the sea surface environment and improving navigation safety.

[0030] Step S400: performing post-positioning compensation on the initial trajectory map using the real-time data set, updating the initial trajectory map into an adjusted trajectory map, and dividing the range areas into N levels according to the map features of the adjusted trajectory map;

[0031] Specifically, the real-time position data obtained is used to determine the deviation between the real-time spatial coordinates of the target vessel and the real-time spatial environment and the initial trajectory map. Based on this deviation, the coordinates of the initial trajectory map are converted and corrected to display the real-time navigation status of the target vessel, and the real-time environmental information not displayed in the initial trajectory map is supplemented, such as the presence of abnormal obstacles, moving obstacles, etc., to generate an adjusted trajectory map. In addition to positioning compensation, the distribution of geographical elements within the scope of the adjusted trajectory map, such as sea areas, land, waterways, etc., is identified based on real-time image data, and N levels of range areas are divided according to the nature of the elements and their relationship with the target vessel. For example, the farthest area for the target vessel is defined as the first level, and the closest area is defined as the Nth level. The N levels of range areas are divided for subsequent track adjustment and path planning.

[0032] By importing real-time data sets into an electronic nautical map environment, coordinate conversion and compensation are achieved for the initial trajectory map, ensuring that the map accurately reflects the target vessel's real-time operating status. Image recognition technology is used to parse map element information and divide the range area based on the distribution of elements and the position of the target vessel. This provides environmental constraints for subsequent trajectory planning and enables accurate identification of the sea surface environment.

[0033] Step S500: determining whether to change the navigation route based on the adjusted trajectory map; if the navigation route needs to be changed, optimizing the target vessel trajectory through the N levels of range areas, and aggregating multiple rounds of optimization results corresponding to the N levels of range areas;

[0034] Specifically, to determine the target vessel's real-time route, the adjusted trajectory map is used to determine whether the initial route needs to be changed. If a change is necessary, the target vessel's trajectory is optimized within each range, and the results of multiple optimization rounds corresponding to each range are aggregated.

[0035] After obtaining the adjusted trajectory map, determine whether the initial route meets the requirements of safety and navigation efficiency under the current map environment. If not, route adjustment and trajectory optimization are required. According to the N divided range areas, various path planning algorithms such as A* algorithm and ant colony algorithm are used in each range area. Combined with the electronic navigation map environment and range area constraints, route optimization calculations are performed separately to generate multiple groups of route plans to achieve the optimization calculation of the initial route. Then, based on the evaluation model, the best plan in each group of plans is selected, and finally the selected best plans are aggregated to obtain the overall optimization result. Among them, the evaluation model includes multiple evaluation indicators, such as navigation time, route length, collision risk, and fuel consumption evaluation.

[0036] By judging whether the route has changed, the trajectory is adjusted and optimized in N levels of range areas respectively, which improves the efficiency of path planning, realizes dynamic route planning, aggregates the multiple rounds of optimization results corresponding to N levels of range areas, and provides a precise and complete navigation plan for subsequent track control.

[0037] Step S600: Generate a trajectory adjustment result according to the aggregation result, and perform navigation control of the target vessel based on the trajectory adjustment result.

[0038] Specifically, the aggregation results include the target vessel’s adjusted route, speed information, and other control parameters. This information constitutes the trajectory adjustment plan, which is the optimal reference trajectory for the target vessel during real-time control to achieve safe and efficient navigation.

[0039] First, a control model for the target vessel is established based on its kinematic and dynamic models, determining the mapping relationships between various control variables. Then, based on the trajectory adjustment plan, the plan information is converted into usable inputs for the control model. This input is then fed into the control model, where control algorithms such as fuzzy control or incremental PID control are employed to output control commands recognizable by the target vessel's automatic navigation system, such as steering gear angle and propeller output power. These commands are then fed into the target vessel's control system, which then drives the target vessel according to the plan through the steering gear and propulsion system. If the target vessel is unmanned, its control system can directly receive and execute the trajectory adjustment plan to achieve autonomous driving. Furthermore, a corresponding early warning plan is matched to the trajectory adjustment plan to ensure navigational control of the target vessel. For example, when the AIS signal of the target vessel is interrupted or the location information is abnormal, the navigation assistance system is entered and the alarm system is turned on to remind the ship management personnel to promptly check whether the vessel's AIS equipment is normal or whether there are other problems; for example, when the target vessel exceeds the speed limit of the designated sea area, the system adjusts the ship's speed or course to comply with the speed limit regulations of the sea area; when a certain type of vessel enters a specific area set by the system, the system activates the alarm system to remind the ship management personnel to take corresponding actions in a timely manner, such as avoidance or emergency rescue.

[0040] By obtaining the aggregated optimization results, a trajectory adjustment plan for the target ship is generated, control instructions for the control system are generated, the trajectory adjustment plan is converted into control instructions, and the control instructions are output to complete navigation control, achieving the purpose of improving navigation efficiency and safety by accurately identifying the sea surface environment and dynamically adjusting the ship's navigation route.

[0041] Further, such as Figure 2 As shown, the embodiment of the present application also includes:

[0042] Step S610: performing multi-sensor data verification on the real-time data set to obtain a data verification result;

[0043] Step S620: performing region segmentation based on the data verification result to generate a region of interest;

[0044] Step S630: compensating the trajectory optimization results within the N levels of the range area by using the focus area;

[0045] Step S640: Obtain the aggregation result according to the compensation result.

[0046] Specifically, to ensure the accuracy and reliability of real-time data sets, multiple sensor data are cross-checked. Data verification algorithms compare similar information obtained by various sensors, determine consistency between the information, and obtain a judgment result. For example, information obtained from the same location or spatial range is directly compared, such as the location of a target ship obtained by a positioning sensor and image recognition. The consistency of the information is determined by comparing the coordinate values ​​obtained from the two. If the difference exceeds a predetermined threshold, it indicates that a certain information is suspicious. Correlation analysis is also performed on information obtained by different sensors. For example, target features such as size and direction of target information obtained by radar and camera are matched to determine whether the obtained target is the same. If the match is low, the information is suspicious. Thus, data verification results are generated.

[0047] The trajectory adjustment optimization results within each range area are compensated or corrected based on the environmental information within the focus area. For example, if a new obstacle is found in the focus area, it is necessary to replan the route to bypass the obstacle and replace the original route; the environmental changes in the focus area affect the speed segment or time period passing through the area, and the speed curve or time parameter table is adjusted accordingly. For example, if the sea conditions deteriorate, the speed curve passing through the focus area needs to be lowered; if there are large environmental changes in a range area, the original result plans of multiple adjacent range areas also need to be replanned to adapt to the new environment. While retaining the structure of the original result plan, local optimization is performed within the focus area to achieve compensation for the trajectory adjustment optimization results. Based on the revised optimization results of each range area, the plan is re-aggregated to obtain the revised aggregation results, which provide a reference for the final trajectory adjustment plan.

[0048] By utilizing the data verification mechanism between multiple sensors, the accuracy of real-time data sets is improved, the new environmental constraint range is determined by the identified area of ​​interest, and the original trajectory adjustment optimization results are compensated and corrected based on the environmental changes in the area of ​​interest. Finally, the aggregation results are updated to improve the accuracy of environmental information acquisition. Combined with dynamic environmental changes, dynamic planning of the navigation path is realized, thereby realizing dynamic control of ship navigation and improving navigation efficiency and safety.

[0049] Furthermore, the embodiment of the present application also includes:

[0050] Step S631: setting a security constraint threshold based on the attention level of the attention area;

[0051] Step S632: when performing trajectory adjustment optimization, calculating the actual distance between each adjusted trajectory and the target area;

[0052] Step S633: constructing a mapping relationship value between distance and safety, matching the mapping relationship value according to the actual distance, and generating a trajectory safety value for the adjusted trajectory;

[0053] Step S634: determining whether the trajectory safety value can satisfy the safety constraint threshold;

[0054] Step S635: If the trajectory safety value cannot meet the safety constraint threshold, the adjusted trajectory corresponding to the trajectory safety value is eliminated.

[0055] Specifically, based on the severity of environmental changes or potential threats identified within the area of ​​interest, a corresponding safety constraint threshold is set, representing the minimum safety requirement for passage through the area to ensure safe navigation. The threshold value depends on the risk level posed by environmental changes within the area of ​​interest. When performing trajectory adjustment optimization calculations to obtain each optional adjusted trajectory, the actual distance between each adjusted trajectory and the area of ​​interest is measured, representing the physical distance between the adjusted trajectory and hazardous environmental elements (such as obstacles or dangerous waters) when passing through the area.

[0056] Based on the correspondence between actual distance and safety, a distance-safety mapping model or rule is established to define corresponding safety levels at different distances, which is used to determine the safety of the adjusted trajectory. Based on the distance-safety mapping value, the corresponding safety requirement value is determined based on the actual distance, which serves as the trajectory safety value of the adjusted trajectory. During trajectory optimization, the trajectory safety value of each adjusted trajectory corresponding to the actual distance from the area of ​​interest is compared with a set safety constraint threshold to determine whether the trajectory safety value meets the threshold requirement. If the trajectory safety value is below the threshold, the adjusted trajectory is not safe enough and poses a certain risk. Adjusted trajectories with trajectory safety values ​​below the threshold do not meet the minimum safety requirements for passing through the area of ​​interest and should not be adopted and should be eliminated or discarded.

[0057] By setting safety constraint thresholds corresponding to environmental changes in the area of ​​concern and mapping the trajectory safety value based on the actual distance of the adjusted trajectory within the area, the safety of the adjusted trajectory can be judged and screened, and an adjusted trajectory that meets safety requirements when passing through the area of ​​concern can be obtained, effectively improving the safety and reliability of sea navigation.

[0058] Furthermore, the embodiment of the present application also includes:

[0059] Step S410: determining whether the newly added obstacle is a movable vessel based on the real-time data set;

[0060] Step S420: When the newly added obstacle is a movable vessel, a connection instruction is sent to the movable vessel;

[0061] Step S430: After the movable vessel receives the connection, the navigation track of the movable vessel is encrypted and exchanged;

[0062] Step S440: re-planning the route based on the navigation track and the initial track map, and synchronously sending the route planning result to the movable vessel.

[0063] Specifically, by analyzing the environmental information expressed in the real-time data set, the system determines whether a newly detected obstacle is a movable vessel. For example, it can identify a vessel by identifying the target's outline and texture through image recognition, or by identifying a large metallic area in the radar echo signal. If the newly detected obstacle is a vessel, a connection request is initiated to the identified movable vessel, requesting the establishment of an information exchange channel. After sending the connection command, the system waits for the other vessel to respond and confirm the establishment of the information exchange channel. When the movable vessel responds to the connection command and confirms the establishment of the information exchange channel, encrypted data is exchanged with the vessel using a secure and reliable communication protocol and encryption method. The system then obtains the movable vessel's current position, speed, and heading information, thereby determining its navigation trajectory.

[0064] Based on the obtained navigation track information of the movable vessel and the original initial track map, the planned path of the target vessel is replanned. The new planned path needs to bypass the navigation range of the movable vessel to avoid collision. The replanned path is synchronized with the movable vessel to guide it to avoid the target vessel.

[0065] By judging obstacles, when the obstacle is a movable vessel, communication interaction is carried out to obtain the other party's navigation track, and the path is re-planned based on the navigation track of the other ship and the trajectory map of the target ship. The planned route is synchronized to guide the movable ship to take avoidance action according to the new path, thereby achieving coordinated collision avoidance between the two ships, achieving the effect of handling dynamic environments during navigation, and improving the safety of sea navigation.

[0066] Furthermore, the embodiment of the present application also includes:

[0067] Step S451: Setting a response verification period;

[0068] Step S452: performing continuous monitoring and verification on the movable vessel within the response verification period;

[0069] Step S453: If the yaw is not within the expected constraint range in the continuous monitoring verification result, an avoidance planning instruction is generated;

[0070] Step S454: replanning the navigation trajectory of the target vessel using the avoidance planning instruction.

[0071] Specifically, a time period is set during which the response and avoidance of the movable vessel are monitored and verified. The length of this time period is determined based on the frequency of environmental changes and the dynamic response capabilities of the target vessel. During this time period, the environmental perception system continuously monitors the current position, speed, heading, and other information of the movable vessel. The monitoring results are compared with the planned path to verify that the movable vessel is following the planned path. If the monitoring results indicate that the movable vessel is following the planned path, monitoring continues.

[0072] When continuous monitoring results indicate that a mobile vessel's navigation status deviates significantly from its planned path, exceeding permitted constraints, it indicates that it is not following guidance and poses a collision risk. At this point, avoidance planning instructions must be regenerated to direct the target vessel to perform evasive maneuvers away from the mobile vessel. Based on the avoidance planning instructions, the path planning algorithm is re-applied to dynamically plan the target vessel's trajectory and generate a new avoidance path. This new trajectory must bypass the monitored mobile vessel's current space to avoid collision and ensure safety.

[0073] By setting a response verification cycle, the response of the movable vessel is continuously monitored according to the verification cycle. When the vessel deviates significantly and does not follow the guidance, a new avoidance path is quickly replanned and generated to guide the target vessel to perform evasive action to prevent collision and improve navigation safety.

[0074] Furthermore, the embodiment of the present application also includes:

[0075] Step S611: constructing a detection sensitivity correlation value of the vessel sensor to the environmental feature;

[0076] Step S612: collecting and obtaining real-time weather characteristics, performing an impact analysis on the ship sensor based on the real-time weather characteristics, and generating a detection correlation value;

[0077] Step S613: completing the data verification based on the detection sensitivity association value and the detection association value.

[0078] Specifically, first, based on the performance parameters of various onboard sensors and the principles of environmental feature detection, the sensor's detection sensitivity to different environmental features and at different detection distances is established. A sensor detection sensitivity model is constructed, resulting in the ship's sensor's detection sensitivity correlation value for environmental features. The sensitivity model defines the sensor's detection sensitivity to specific features and the degree of impact under different environmental conditions, such as the impact of optical image sensors on target recognition under varying visibility conditions or at different distances, or the changes in radar's sensitivity to target detection under varying sea conditions or at different distances. Next, current real-time weather and environmental characteristics, such as wind speed, sea state, visibility, and air pressure, are obtained. Based on the established sensor detection sensitivity model, the impact of current weather conditions on the detection performance of each sensor is analyzed, resulting in a detection correlation value representing the sensor's sensitivity or detection accuracy to environmental features under the current weather conditions.

[0079] Based on the sensor's sensitivity correlation value for environmental characteristics and the correlation value obtained under current weather conditions, the sensor data collected is verified to verify its accuracy and reliability under the current data. If the data judgment shows a significant deviation, retesting or switching to other sensors will be adopted to obtain more accurate data.

[0080] By establishing a detection-sensitive relationship between sensors and environmental features, and obtaining weather information in real time to analyze its impact on detection performance, the validity of sensor-collected data can be verified, ensuring the accuracy and reliability of perception data, thereby achieving precise identification of the sea surface environment.

[0081] Further, such as Figure 3 As shown, the embodiment of the present application also includes:

[0082] Step S631: When the concerned area exists, generating a keep updating instruction;

[0083] Step S632: continuously collecting regional data of the region of interest through the keep updating instruction, and performing regional data compensation for the region of interest;

[0084] Step S633: performing control optimization of the local path based on the regional data compensation result;

[0085] Step S634: performing trajectory compensation of the trajectory adjustment result based on the control optimization result.

[0086] Specifically, when the environment perception and recognition system detects that there is a region of interest, such as a region with complex sea conditions, obstacles, severe weather, etc., a keep updating instruction is generated, which requires continuous high-frequency collection and updating of environmental information in the region, so as to track the changes in the region in real time. According to the keep updating instruction, various types of environmental information such as sea condition data, weather data, image information, etc. are collected frequently in the region of interest, and the environmental data of the region collected at present is compensated and corrected through time series prediction, spatial interpolation, model calculation, etc. The compensated regional environmental data can more accurately reflect the real-time situation of the region.

[0087] Based on the compensated and corrected environmental data of the region of interest, the path of the target ship in the region is controlled and optimized to generate the optimal local path under the current conditions, such as bypassing the severe sea condition area, avoiding the strong rainfall center, etc. The optimized path can safely and efficiently pass through the region. The local path obtained by optimization is compensated at the connection with the original global path to make the sailing trajectory transition smooth and stable, and the trajectory adjustment result is obtained to guide the target ship to safely pass through the region of interest.

[0088] By high-frequency collection and compensation of the region of interest under dynamic changing environment, accurate real-time environmental information is obtained, and based on this information, local path control optimization is performed in the region to generate a safe and efficient passing path. Finally, the optimized path and the original path are connected to obtain the final executable trajectory adjustment result, which guides the target ship to safely pass through the region, realizes the technical effect of dynamically controlling the ship, and greatly improves the safety and efficiency of the ship passing through the complex environment.

[0089] In summary, the sea surface navigation recognition processing method provided by the embodiments of the present application has the following technical effects:

[0090] The interactive control center reads the basic data of the target ship, including ship attribute data and navigation planning data, to provide static information for building the initial environment model; based on the basic data, the navigation map is called to build the initial trajectory map to achieve preliminary modeling of the sea surface environment; the ship sensor of the target ship is called to collect sea surface data and build a real-time data set, including position data and image data, to obtain dynamic information of the sea surface environment; the initial trajectory map is positioned and compensated through the real-time data set, and the initial trajectory map is updated to the adjusted trajectory map, and the map features of the adjusted trajectory map are divided into N levels. Range area, to achieve dynamic tracking modeling of environmental changes; based on the adjustment trajectory map, determine whether to change the navigation route. If the navigation route needs to be changed, the trajectory of the target ship is adjusted and optimized through N levels of range areas respectively, and the multiple rounds of optimization results corresponding to the N levels of range areas are aggregated. Multiple rounds of trajectory optimization and aggregation are performed in different range areas to generate a navigation route adjustment plan; the trajectory adjustment result is generated according to the aggregation result, and the navigation control of the target ship is executed based on the trajectory adjustment result, completing the real-time response to the changes in the sea surface environment, achieving the technical effect of accurately identifying the sea surface environment and dynamically controlling the navigation of the ship, and improving the navigation efficiency and safety.

[0091] Example 2

[0092] Based on the same inventive concept as the method for identifying and processing sea navigation by fusing multi-dimensional data in the aforementioned embodiment, Figure 4 As shown, an embodiment of the present application provides a sea navigation identification and processing system that integrates multi-dimensional data, the system comprising:

[0093] The basic information reading module 11 is used for interactive control of the middle platform to read the basic data of the target ship, wherein the basic data includes ship attribute data and navigation planning data;

[0094] The initial track map module 12 calls the navigation map based on the basic data to construct the initial track map;

[0095] A real-time data collection module 13 is used to call the ship sensor of the target ship to collect sea surface data and construct a real-time data collection, wherein the real-time data collection includes position data and image data;

[0096] a range region division module 14 for compensating the initial trajectory map after positioning using the real-time data set, updating the initial trajectory map into an adjusted trajectory map, and dividing the range regions into N levels according to map features of the adjusted trajectory map;

[0097] A trajectory adjustment optimization module 15 determines whether to change the navigation route based on the adjusted trajectory map. If the navigation route needs to be changed, the trajectory of the target vessel is adjusted and optimized through the N levels of the range areas, and multiple optimization results corresponding to the N levels of the range areas are aggregated;

[0098] The navigation control execution module 16 is configured to generate a track adjustment result according to the aggregation result, and execute navigation control of the target vessel based on the track adjustment result.

[0099] Furthermore, the embodiment of the present application also includes:

[0100] A data verification result module is used to perform multi-sensor data verification on the real-time data set to obtain a data verification result;

[0101] A region of interest generation module is configured to perform region segmentation based on the data verification result to generate a region of interest;

[0102] An optimization result compensation module, configured to compensate for optimization results of trajectories within the N levels of the range area by adjusting the focus area;

[0103] The aggregation result acquisition module is used to obtain the aggregation result according to the compensation result.

[0104] Furthermore, the embodiment of the present application also includes:

[0105] A security constraint threshold module, configured to set a security constraint threshold based on the attention level of the attention area;

[0106] An actual distance calculation module, used to calculate the actual distance between each adjusted trajectory and the target area when performing trajectory adjustment optimization;

[0107] A trajectory safety value module is used to construct a mapping relationship value between distance and safety, match the mapping relationship value according to the actual distance, and generate a trajectory safety value for adjusting the trajectory;

[0108] A safety value judgment module, configured to judge whether the trajectory safety value can satisfy the safety constraint threshold;

[0109] The adjustment trajectory elimination module is configured to eliminate the adjustment trajectory corresponding to the trajectory safety value if the trajectory safety value fails to meet the safety constraint threshold.

[0110] Furthermore, the embodiment of the present application also includes:

[0111] A new obstacle determination module is added to determine whether a new obstacle is a movable vessel based on the real-time data set;

[0112] a connection instruction sending module, configured to send a connection instruction to the movable vessel when the newly added obstacle is a movable vessel;

[0113] An encrypted interactive vessel module, configured to encrypt and interact with the navigation track of the movable vessel after the movable vessel receives the connection;

[0114] The route re-planning module re-plans the route based on the navigation track and the initial track map, and synchronously sends the route planning result to the movable vessel.

[0115] Furthermore, the embodiment of the present application also includes:

[0116] Response verification cycle module, used to set the response verification cycle;

[0117] a continuous monitoring and verification module, configured to perform continuous monitoring and verification on the movable vessel within the response verification period;

[0118] An avoidance planning instruction module is used to generate an avoidance planning instruction if the yaw is not within the expected constraint range in the continuous monitoring verification result;

[0119] A navigation trajectory planning module is used to replan the navigation trajectory of the target vessel according to the avoidance planning instruction.

[0120] Furthermore, the embodiment of the present application also includes:

[0121] A sensitive correlation value module, used to construct a sensitive correlation value of the vessel sensor for detecting environmental features;

[0122] a detection correlation value module, configured to collect and obtain real-time weather characteristics, perform an impact analysis of the vessel sensor based on the real-time weather characteristics, and generate a detection correlation value;

[0123] A data verification module completes the data verification based on the detection sensitive association value and the detection association value.

[0124] Furthermore, the embodiment of the present application also includes:

[0125] A keep-update instruction module, configured to generate a keep-update instruction when the area of ​​interest exists;

[0126] A regional data compensation module, configured to continuously collect regional data of the region of interest through the keep-update instruction and perform regional data compensation on the region of interest;

[0127] The local control optimization module is used to perform control optimization of the local path based on the regional data compensation results;

[0128] The trajectory compensation module performs trajectory compensation on the trajectory adjustment result based on the control optimization result.

[0129] Any step of the method described above can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor to implement any method in the embodiments of the present application, without any unnecessary restrictions.

[0130] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. A method for identifying and processing sea surface navigation by integrating multi-dimensional data, characterized in that: The method comprises: The interactive control center reads the basic data of the target vessel, wherein the basic data includes vessel attribute data and navigation planning data; Based on the basic data, calling the navigation map to build an initial trajectory map; Invoking the ship sensor of the target ship to collect sea surface data and construct a real-time data set, wherein the real-time data set includes position data and image data; Positioning and compensating the initial trajectory map using the real-time data set, updating the initial trajectory map into an adjusted trajectory map, and dividing the range areas into N levels according to map features of the adjusted trajectory map; Determining whether to change the navigation route based on the adjusted trajectory map, and if the navigation route needs to be changed, optimizing the target vessel trajectory through the N levels of range areas respectively, and aggregating multiple rounds of optimization results corresponding to the N levels of range areas; A trajectory adjustment result is generated according to the aggregation result, and navigation control of the target vessel is performed based on the trajectory adjustment result.

2. The method according to claim 1, wherein The method further comprises: Performing multi-sensor data verification on the real-time data set to obtain a data verification result; Performing region segmentation based on the data verification result to generate a region of interest; Compensating for trajectory adjustment optimization results within the N levels of the range area using the focus area; The aggregation result is obtained according to the compensation result.

3. The method according to claim 2, wherein The method further comprises: Setting a security constraint threshold based on the attention level of the attention area; When performing trajectory adjustment optimization, calculating the actual distance between each adjusted trajectory and the focus area; Constructing a mapping relationship value between distance and safety, matching the mapping relationship value according to the actual distance, and generating a trajectory safety value for adjusting the trajectory; Determining whether the trajectory safety value can meet the safety constraint threshold; If the trajectory safety value cannot meet the safety constraint threshold, the adjusted trajectory corresponding to the trajectory safety value is eliminated.

4. The method according to claim 1, wherein The method further comprises: Determining whether the newly added obstacle is a movable vessel based on the real-time data set; When the newly added obstacle is a movable vessel, initiating a connection instruction to the movable vessel; When the movable vessel receives the connection, encrypting and exchanging the navigation track of the movable vessel; Re-route planning is performed based on the navigation track and the initial track map, and the route planning result is synchronously sent to the movable vessel.

5. The method according to claim 4, wherein The method further comprises: Set the response verification period; Conducting continuous monitoring verification on the movable vessel during the response verification period; If the yaw is not within the expected constraint range in the continuous monitoring verification results, an avoidance planning instruction is generated; The navigation trajectory of the target vessel is replanned using the avoidance planning instruction.

6. The method according to claim 2, wherein The method further comprises: Constructing a detection sensitivity correlation value of the vessel sensor to the environmental characteristics; Acquire real-time weather characteristics, perform an impact analysis of the ship sensor based on the real-time weather characteristics, and generate a detection correlation value; The data verification is completed based on the detection sensitivity association value and the detection association value.

7. The method according to claim 2, wherein The method further comprises: When the area of ​​interest exists, generating a keep-update instruction; continuously collecting regional data of the region of interest through the keep updating instruction, and performing regional data compensation on the region of interest; Perform local path control optimization based on regional data compensation results; The trajectory compensation of the trajectory adjustment result is performed based on the control optimization result.

8. A sea navigation identification and processing system integrating multi-dimensional data, characterized in that: The system comprises: A basic information reading module, which is used for the interactive control center to read the basic data of the target ship, wherein the basic data includes ship attribute data and navigation planning data; An initial track map module, which calls a navigation map based on the basic data to construct an initial track map; A real-time data collection module, the real-time data collection module is used to call the ship sensor of the target ship to collect sea surface data and construct a real-time data collection, wherein the real-time data collection includes position data and image data; a range area division module, the range area division module being configured to perform post-positioning compensation on the initial trajectory map using the real-time data set, update the initial trajectory map into an adjusted trajectory map, and divide the range areas into N levels according to map features of the adjusted trajectory map; a trajectory adjustment optimization module, which determines whether to change the navigation route based on the adjusted trajectory map. If the navigation route needs to be changed, the trajectory of the target vessel is adjusted and optimized through the N levels of the range areas, and aggregating multiple rounds of optimization results corresponding to the N levels of the range areas; A navigation control execution module is used to generate a track adjustment result according to the aggregation result, and execute navigation control of the target vessel based on the track adjustment result.

Images