Automatic underway temperature, salinity, and depth profiling system and method for mesoscale eddy prediction

Abstract

This invention belongs to the field of unmanned surface vessel (USV) automated navigation technology, specifically an automated navigation temperature, salinity, and depth (TDM) profiling system and method for mesoscale eddy prediction. Deployed on an USV and connected to an automated launch and recovery winch, the system includes: a TDM probe device positioned at the end of the A-frame of the automated launch and recovery winch, used for raising and lowering via the winch to measure temperature, salinity, and depth parameters of seawater at different profiles, providing crucial oceanographic data for mesoscale eddy prediction; and transmitting the data to a mother ship / shore-based terminal via a remote intelligent navigation control system. The remote intelligent navigation control system receives various data and transmits them to the mother ship / shore-based terminal, while simultaneously controlling the automated launch and recovery winch, the TDM probe device, and the USV's navigation or mission process according to instructions from the mother ship / shore-based terminal. This invention allows for the deployment and retrieval of TDM profiling equipment during ship navigation, and with upgrades, it can be deployed and retrieved from an USV.

Description

Technical Field

[0001] This invention belongs to the field of unmanned surface vessel (USV) automatic navigation technology, specifically an automatic navigation temperature, salinity, and depth profile observation system and method for mesoscale eddy prediction. Background Technology

[0002] With the global trend towards intelligent and unmanned ocean observation, how to conduct ocean observation more efficiently, economically, and automatically has become a research focus. Therefore, the observation of mesoscale eddies requires breaking with conventional thinking and making significant updates to existing observation methods and technologies. This has led to the emergence of unmanned observation. Unmanned surface vessels (USVs) are remotely controlled, autonomous, mobile observation platforms capable of observing a full range of ocean elements over extended periods. As a crucial technology for observing the fine structure of mesoscale eddies, fully automated ocean observation USVs automatically acquire multi-parameter environmental data of the measured sea area and record and calculate data to meet the requirements of effective data observation, providing important data for cutting-edge oceanographic research. By carrying satellite and communication equipment modules, USVs can utilize digital, information-based, and networked technologies to achieve uninterrupted, real-time transmission of on-site observation information for mesoscale eddies. This allows for direct intervention in mesoscale eddy observation work in situations where other observation equipment cannot achieve or even approach the required level, enabling real-time observation across all dimensions, directions, and sea conditions. This is crucial for effectively acquiring fine structure data of mesoscale eddies.

[0003] While existing temperature, salinity, and depth (TST) profile observation devices have achieved partial automation, they still require human intervention to function properly and need to be mounted on conventional large research vessels for effective measurements. This limits their application in multi-purpose, multidisciplinary spatial dimensions. The following problems currently exist in this field:

[0004] Traditional marine environmental parameter measurement equipment and unmanned surface vessel (USV) navigation control systems have many shortcomings. In temperature, salinity, and depth (TDM) measurement, early TDM equipment had limited functionality, accuracy, and data acquisition and transmission efficiency. For example, some simple TDM probes could not operate stably in the high-pressure environment of the deep sea; their internal sensors were easily damaged by seawater corrosion and pressure shocks, leading to inaccurate measurement data or even equipment failure. Furthermore, previous TDM probes used outdated communication methods with external devices, resulting in significant data transmission delays and failing to meet the needs of real-time monitoring and analysis.

[0005] In terms of unmanned surface vessel (USV) navigation control, traditional navigation control systems lack comprehensive perception and intelligent decision-making capabilities for complex marine environments. On one hand, their communication modules have weak anti-interference capabilities, easily leading to communication interruptions or data transmission errors in adverse weather or signal blockage, severely impacting command transmission and data feedback between the USV and the mother ship / shore-based remote monitoring platform. On the other hand, the path planning and tracking algorithms of intelligent navigation modules are simplistic and fail to adequately consider obstacles, currents, waves, and other factors in the marine environment, causing USVs to easily deviate from their planned routes or even collide during navigation. Furthermore, traditional USV internal state perception and external environment perception functions are incomplete, unable to accurately acquire real-time status information of the USV and detailed data of the surrounding environment, making precise control and safety assurance difficult.

[0006] Meanwhile, in traditional unmanned surface vessel (USV) systems, the modules operate independently, lacking an effective collaborative mechanism. For example, there is no close connection between the temperature, salinity, and depth (TDT) measurement equipment and the USV's navigation control system, making it impossible to adjust the USV's navigation route and operational status in real time according to the needs of the measurement mission. This results in low measurement efficiency and fails to meet the requirements of modern marine scientific research for comprehensive, accurate, and rapid measurement of marine environmental parameters. Summary of the Invention

[0007] The purpose of this invention is to provide an automated underway temperature, salinity, and depth (TDM) profile observation system and method for mesoscale eddy prediction. It adopts a self-designed remote intelligent navigation control system and controls the automatic winch and TDM probe device to achieve comprehensive perception and intelligent decision-making capabilities for complex marine environments.

[0008] The technical solution adopted by the present invention to achieve the above objectives is: an automatic underway temperature, salinity and depth profile observation system for mesoscale eddy prediction, which is installed on an unmanned vessel and connected to an automatic winch, including: a remote intelligent navigation control system and a temperature, salinity and depth probe device connected to it.

[0009] The temperature, salinity, and depth probe device is installed at the end of the A frame of the automatic winding winch. It is used to raise and lower the winch through the automatic winding winch, thereby measuring the temperature, salinity, and depth parameters of seawater at different profiles, providing key ocean data for mesoscale eddy prediction. The measured data is transmitted to the mother ship / shore-based remote monitoring platform through the remote intelligent navigation control system.

[0010] The aforementioned intelligent navigation control system includes: a communication module, a shipborne control module, an internal status perception module, an external environment perception module, an intelligent navigation module, and a navigation control module;

[0011] The communication module is used to transmit in real time the instructions issued by the mother ship / shore-based remote control monitoring platform to the unmanned vessel for automatic winch deployment and take-off, as well as the data feedback from the unmanned vessel to the mother ship / shore-based remote control monitoring platform; the communication module is a Beidou and Tiantong dual-mode communication module, which sends the unmanned vessel's positioning, heading, and speed-related data parameters to the mother ship / shore-based remote control monitoring platform to realize remote monitoring of the mother ship / shore-based remote control monitoring platform;

[0012] The shipborne control module is used to receive, store and transmit instructions issued by the mother ship / shore-based remote control monitoring platform, and send basic data information and video image information of the unmanned vessel during navigation to the mother ship / shore-based monitoring platform in real time through the communication module; at the same time, it receives control instructions for the automatic winch sent by the mother ship / shore-based monitoring platform, controls the automatic winch, and thus realizes the upgraded control of the temperature, salinity and depth probe.

[0013] The internal state perception module is used to collect basic data information on the unmanned vessel's navigation status in real time.

[0014] The external environment perception module is used to collect and fuse environmental data information in real time during the unmanned vessel's navigation.

[0015] The intelligent navigation module is used to receive instructions transmitted by the shipborne control module, and generate a track or return track according to the instructions, and send it to the navigation control module.

[0016] The navigation control module is used to execute the instructions sent by the shipborne control module, and to acquire in real time the basic data information of the internal state perception module, the basic data information of the external environment perception module, the data information of the intelligent navigation module, and the data information of the mission operation assembly. It also controls the unmanned vessel in real time based on all the data information, and sends all the data information to the shipborne control module.

[0017] The intelligent navigation module includes: a path planning module, a path tracking module, and a return-to-home module;

[0018] The path planning module is used to receive data information from the external environment perception module, and perform path planning, generate a track, and perform navigation based on the data information from the external environment perception module.

[0019] The path tracking module is used to monitor in real time whether the current driving state of the unmanned vessel deviates from the planned route through satellite navigation and inertial navigation. If a deviation occurs, a signal is sent to the navigation control module to adjust the unmanned vessel to the planned route; otherwise, the current driving state remains unchanged.

[0020] The return-to-home module is used to generate a return-to-home track when communication is interrupted, and the navigation control module controls the return-to-home based on the return-to-home track.

[0021] The path planning module includes: an obstacle detection module and an obstacle avoidance decision module;

[0022] The obstacle judgment module is used to predict obstacles based on the basic data information of the external environment perception module. For obstacles with uncertain data information, the module further expands the obstacle based on the predicted obstacle position data, thereby converting the uncertain obstacle position data into specific data and judging whether the obstacle is a static obstacle or a dynamic obstacle.

[0023] The obstacle avoidance decision module is used to avoid dynamic obstacles by changing the speed without changing the original trajectory; for static obstacles, it determines the difference in heading angle between itself and the obstacle, determines which maritime rule to apply, and then changes the speed and direction according to the content of the maritime rule, thereby changing the path to avoid the obstacle. After changing the path to avoid the obstacle, it returns to the original path.

[0024] The basic data information includes: speed, heading, pitch, position, attitude, battery charge, remaining fuel, engine speed, and rudder angle;

[0025] The environmental data information includes: inertial navigation information, radar information, laser information, visual information, AIS information, and nautical chart information.

[0026] The temperature, salinity, and depth probe device includes: a pressure chamber, a temperature sensor, a conductivity cell, a pressure sensor, a power supply module, a data storage module, a data interaction protocol, and a GPS clock;

[0027] The pressure-resistant chamber, as the overall protective outer shell, is used to ensure the normal operation of various electronic components inside the chamber in the high-pressure environment of the deep sea;

[0028] The temperature sensor has its probe exposed outside the pressure-resistant chamber, in full contact with the surrounding seawater, to measure the real-time temperature of the seawater.

[0029] The conductivity cell is installed inside the pressure-resistant chamber and has a channel for contacting seawater, used to measure the conductivity of seawater and obtain the salinity of seawater.

[0030] The pressure sensor is installed in the pressure-resistant chamber to sense the pressure change caused by the change in seawater depth, and thus obtain the depth of the temperature, salinity and depth probe device.

[0031] The power module, located inside the pressure chamber, provides a stable power supply to the entire temperature, salinity, and depth probe device, ensuring that all sensors and other modules continue to operate normally.

[0032] The data storage module is used to store the data collected by the temperature sensor, conductivity cell, and pressure sensor, ensuring the integrity and security of the data for subsequent analysis and research; and through specific communication interfaces and protocol specifications, it enables the collected data to be accurately transmitted to the remote intelligent navigation control system, the mother ship / shore-based monitoring platform's host computer, or other receiving equipment.

[0033] The GPS clock, integrated within the device, provides a precise time reference for the entire system, ensuring the accuracy of data acquisition and facilitating subsequent analysis of data at different points in time.

[0034] It also includes: video surveillance module, antenna, radar, and wireless charging device;

[0035] The video surveillance module includes: a collision avoidance camera and an automatic winch monitoring camera;

[0036] The collision avoidance camera is installed on the top of the unmanned vessel's cabin. It is an external camera part of the video monitoring module of the intelligent navigation control system. It is used to monitor the surrounding environment in real time, provide collision avoidance visual information for the unmanned vessel during navigation, and transmit the image data it collects to the remote intelligent navigation control system to assist the remote intelligent navigation control system in making navigation decisions.

[0037] The automatic winch monitoring camera is an external camera of the video monitoring module used to monitor the working status of the automatic winch in real time. It transmits the captured video images to the video monitoring module so that the mother ship / shore-based remote control monitoring platform can understand the operation of the winch in real time and ensure the normal coordinated operation of the unmanned vessel and the automatic winch.

[0038] The antenna is located on the top of the ship's cabin and is connected to the intelligent navigation control system. It is used to enhance the signal reception and transmission capabilities of Beidou and Tiantong dual-mode communication, and to ensure the stability and reliability of communication between the remote intelligent navigation control system and the mother ship / shore-based remote control monitoring platform.

[0039] The radar is located on the top of the cabin and is connected to the intelligent navigation control system. It is used to monitor obstacles and ship targets around the unmanned ship in real time, and the acquired radar information is integrated by the intelligent navigation control system for path planning and navigation decision-making of the navigation control module.

[0040] The wireless charging device includes: a wireless charging transmitter with a damper, a wireless charging receiver, and an independent charging controller.

[0041] A wireless charging transmitter with a damper is installed at the front end of the A frame of the automatic winding winch, and a wireless charging receiver is provided below the wireless charging transmitter. Both the wireless charging transmitter and the wireless charging receiver are equipped with watertight protective covers.

[0042] A method for an automated underway temperature, salinity, and depth profiling system for mesoscale eddy prediction includes the following steps:

[0043] 1) The mother ship / shore-based remote control monitoring platform issues instructions: set the number of observations and the observation time of the mother ship / shore-based remote control monitoring platform when a data transmission to the shipboard control module is completed;

[0044] 2) The communication module of the remote intelligent navigation control system receives mission instructions from the mother ship / shore-based remote control monitoring platform. The shipboard control module stores the instructions and transmits them to the intelligent navigation module and the navigation control module respectively. The external environment perception module collects environmental data information in real time and performs fusion. The internal state perception module collects basic data information of the unmanned ship's navigation status in real time.

[0045] 3) The intelligent navigation module receives instructions transmitted by the shipborne control module, and generates a track or return track according to the instructions, and sends it to the navigation control module;

[0046] 4) The navigation control module executes the instructions sent by the shipborne control module and acquires the basic data information of the internal status perception module, the basic data information of the external environment perception module, the data information of the intelligent navigation module, and the data information of the mission operation assembly in real time. It then adjusts the unmanned vessel in real time based on all the data information and sends all the data information to the shipborne control module.

[0047] 5) When the unmanned vessel sails to the predetermined measurement area, it controls the automatic winch to lower the temperature, salinity, and depth probe device into the seawater through the remote intelligent navigation control system, and starts the measurement of relevant parameters of the seawater by the temperature, salinity, and depth probe device.

[0048] 6) Temperature sensors, conductivity cells, and pressure sensors collect data and store it in the data storage module. The data storage module transmits the data to the remote intelligent navigation control system through a specific data interaction protocol and communication interface. The remote intelligent navigation control system then transmits the data to the mother ship / shore-based remote control monitoring platform through its communication module.

[0049] 7) When communication is interrupted, the return module of the intelligent navigation module generates a return track, and the navigation control module controls the unmanned vessel to return according to the return track, thus completing the observation mission.

[0050] Step 3) specifically includes:

[0051] 3-1) The path planning module performs path planning and generates a flight path based on the environmental data information from the external environment perception module and in conjunction with the task instructions;

[0052] 3-2) During the path planning process, the obstacle judgment module predicts obstacles based on the basic data information of the external environment perception module. For obstacles with uncertain data information, the obstacle is further expanded based on the predicted obstacle position data to transform the uncertain obstacle position data into specific data and determine whether the obstacle is a static obstacle or a dynamic obstacle.

[0053] 3-3) For dynamic obstacles, the obstacle avoidance decision module changes the speed without changing the original trajectory to avoid the obstacle. For static obstacles, it judges the difference in heading angle with the obstacle, determines which maritime rule to apply, and then changes the speed and direction according to the content of the maritime rule, thereby changing the path to avoid the obstacle. After changing the path to avoid the obstacle, it returns to the original path.

[0054] 3-4) The path tracking module uses radar to monitor in real time whether the current driving status of the unmanned vessel deviates from the planned route. If a deviation occurs, a signal is sent to the navigation control module, which adjusts the unmanned vessel to the planned route. Otherwise, the current driving status remains unchanged.

[0055] In step 4), the real-time control of the unmanned vessel based on all the data information specifically includes:

[0056] 4-1) Data Acquisition Stage

[0057] Acquire basic data information from the internal state perception module, the external environment perception module, the intelligent navigation module, and the task operation assembly;

[0058] Among them, intelligent navigation data: Target trajectory data generated by path planning is received from the intelligent navigation module, including a series of target point coordinates (x, y, y). target ,y target The current navigation deviation information fed back by the path tracking module; if a deviation exists, the deviation angle and deviation distance are obtained.

[0059] Acquire task operation assembly data: Receive task operation assembly data, including the measurement point coordinate sequence of the temperature, salinity and depth measurement task and the status data of the automatic winch equipment;

[0060] 4-2) Data Fusion and Analysis Stage

[0061] a. Establish the state vector:

[0062] All the acquired data are combined into a comprehensive state vector S;

[0063] b. Target track matching analysis:

[0064] The current unmanned surface vessel's position coordinates (x, y) in the integrated state vector S are compared with the target point coordinates (x, y) of the target trajectory. target ,y target Perform a comparative analysis to calculate the distance d between the current position and the next target point. a and azimuth θ a , the formula is as follows:

[0065]

[0066] θ a =arctan2(y target -y,x target -x)

[0067] c. Based on the current heading θ and θ a The difference is used to determine whether a course adjustment is needed;

[0068] d. Obstacle risk assessment:

[0069] The presence of obstacles is determined based on radar and visual information; if an obstacle is detected, the distance d from the obstacle is used to determine its location. o Azimuth β o Given the current velocity V of the unmanned vessel, the collision time TTC is calculated as follows:

[0070]

[0071] If the TTC is less than the safety threshold, a collision risk is identified, and obstacle avoidance measures are required.

[0072] e. Environmental Factor Impact Analysis:

[0073] Considering the water depth h in the nautical chart information, combined with the draft h of the unmanned vessel... d To determine if there is a risk of stranding; if hh d If the depth is less than the safe water depth margin, a shallow water alarm will be issued and the navigation strategy will be adjusted. At the same time, the motion stability of the ship will be analyzed based on the acceleration and angular velocity data in the inertial navigation information. If abnormal fluctuations are found, the navigation status may need to be adjusted to ensure stability.

[0074] 4-3) Regulation Decision Generation Stage

[0075] Heading adjustment decision: If the target track matching analysis indicates that a heading adjustment is needed, the appropriate rudder angle adjustment Δδ is calculated using a PID control algorithm based on the difference between the current heading and the target heading, i.e.:

[0076]

[0077] Where, e(t)=θ a-θ, i.e., heading deviation, K P K i K d The parameters of the PID controller are tuned based on the dynamic characteristics and navigation environment of the unmanned vessel.

[0078] Speed ​​adjustment decision: Taking into account obstacle risk assessment, mission requirements, and environmental factors, decide whether to adjust the speed; if there is a collision risk, for dynamic obstacles, change the speed according to the obstacle avoidance decision module rules; for static obstacles, determine which maritime rules to apply based on the difference in heading angle with the obstacle, and if deceleration is required, calculate the appropriate speed reduction amount; at the same time, if the mission requires maintaining low-speed cruising in a specific area, or if environmental factors affect navigation efficiency, adjust the speed accordingly.

[0079] Integrated control command generation: Combine the calculated rudder angle adjustment Δδ and speed adjustment ΔV into an integrated control command C = [Δδ, ΔV];

[0080] 4-4) Implementation and Data Feedback Stage

[0081] Sending control commands: The integrated control command C is sent to the unmanned vessel's actuators, such as the servo motor and engine control system, to adjust the unmanned vessel's navigation status. The servo motor adjusts the rudder angle based on the received Δδ, and the engine control system adjusts the engine speed based on ΔV, thereby changing the unmanned vessel's course and speed;

[0082] Data feedback: All data involved in the control, namely all data in the state vector S and the generated control commands C, are sent back to the shipboard control module; the shipboard control module transmits these data to the mother ship / shore-based remote control monitoring platform through the communication module for real-time monitoring and subsequent data analysis; at the same time, the navigation control module itself records these data for retrospective analysis of the navigation process and fault diagnosis.

[0083] Step 5) specifically includes:

[0084] 5-1) Delegation Operation:

[0085] The system issues commands through the remote intelligent flight control system to control the operation of the automatic winding winch; since the temperature, salinity and depth probe device is located at the end of the A frame of the automatic winding winch, the automatic winding winch gradually lowers the cable connected to the temperature, salinity and depth probe device according to the commands.

[0086] 5-2) Temperature Measurement

[0087] As the temperature, salinity, and depth probe is lowered into the seawater, the temperature sensor begins to operate. The probe is exposed outside the pressure-resistant chamber to ensure full contact with the surrounding seawater. The temperature sensor is based on the principle of a thermistor, whose resistance changes with the seawater temperature. When the probe comes into contact with the seawater, the heat from the seawater is transferred to the thermistor, causing a corresponding change in its resistance. By using a pre-calibrated relationship between resistance and temperature, the change in resistance is converted into a temperature value, thereby accurately measuring the real-time temperature of the seawater.

[0088] 5-3) Salinity Measurement

[0089] When the temperature, salinity, and depth probe device is placed in seawater, seawater flows into the conductivity cell through the channel. The conductivity cell is equipped with two electrodes. When a certain voltage is applied across the electrodes, ions in the seawater will move directionally under the influence of the electric field, forming an electric current. By measuring the magnitude of the current, the conductivity of the seawater is calculated according to Ohm's law. Then, using a specific algorithm, the conductivity is converted into the salinity of the seawater.

[0090] 5-4) Depth Measurement

[0091] The pressure sensor is a piezoresistive pressure sensor. When seawater pressure acts on the sensor's sensitive element, the resistance value of the sensitive element changes, and this change is proportional to the magnitude of the pressure. As the temperature, salinity, and depth probe device continues to sink, the seawater pressure gradually increases, and the resistance value of the pressure sensor changes accordingly. By measuring the change in resistance value and combining it with a pre-calibrated pressure-depth conversion relationship, the depth of the temperature, salinity, and depth probe device can be obtained.

[0092] 5-5) Throughout the measurement process, the power module continuously provides a stable power supply to the temperature sensor, conductivity cell, pressure sensor, and data storage module, ensuring that each module can operate continuously and normally.

[0093] 5-6) The data storage module stores the data collected by the temperature sensor, conductivity cell and pressure sensor in real time to ensure the integrity and security of the data. This data can then be transmitted to the remote intelligent navigation control system via the data interaction protocol, and then from the remote intelligent navigation control system to the mother ship / shore-based remote control monitoring platform. At the same time, the GPS clock provides a precise time reference for the entire measurement process, ensuring the accuracy of the data acquisition time and facilitating the subsequent analysis and comparison of data at different time points.

[0094] The present invention has the following beneficial effects and advantages:

[0095] 1. Compared with existing similar technologies, this invention has the advantages of lightweight and compact structure, simple and flexible operation, stable system operation, and strong corrosion resistance. This invention can be used to deploy and retrieve temperature, salinity and depth profiling equipment while the ship is underway. After upgrading and modification, it can be used to deploy and retrieve underway temperature, salinity and depth profiling equipment on unmanned vessels.

[0096] 2. The temperature, salinity, and depth probe device of this invention features a sophisticated structural design. Its pressure-resistant chamber ensures the normal operation of internal electronic components under the high pressure environment of the deep sea. Temperature sensors, conductivity cells, and pressure sensors can accurately measure seawater temperature, salinity, and depth parameters. Furthermore, through the automatic winch operation, it can measure seawater parameters at different profiles, providing crucial high-quality data for oceanographic research such as mesoscale eddy prediction. Simultaneously, the data storage module and data interaction protocol guarantee secure data storage and rapid, accurate transmission, significantly improving the efficiency and accuracy of data acquisition.

[0097] 3. The remote intelligent navigation control system of this invention integrates multiple functional modules, including an advanced communication module, an intelligent navigation module, and a navigation control module. The communication module employs dual-mode BeiDou and TianTong communication, possessing strong anti-interference capabilities to ensure stable and reliable communication between the unmanned vessel and the mother ship / shore-based remote control monitoring platform. The intelligent navigation module, through path planning, path tracking, and return-to-base modules, comprehensively considers various environmental data collected by the external environment perception module, such as inertial navigation, radar, and laser information, to achieve high-precision path planning and real-time accurate path tracking, effectively preventing the unmanned vessel from deviating from its course or colliding during navigation. The navigation control module, based on data from the internal state perception module, external environment perception module, and intelligent navigation module, performs real-time precise control of the unmanned vessel, ensuring its safe and stable navigation in complex marine environments.

[0098] 4. This invention organically integrates a temperature, salinity, and depth (TST) probe, a remote intelligent navigation control system, and multiple devices and modules such as collision avoidance cameras, antennas, and radar into a highly integrated system. The various modules collaborate and share information, enabling real-time adjustments to the unmanned surface vessel's (USV) navigation status and measurement operations according to the needs of marine research missions, achieving highly efficient collaborative work. For example, when the TST probe needs to perform measurements in a specific area, the remote intelligent navigation control system can precisely control the USV to navigate to that area according to the measurement mission requirements, adjusting its speed and attitude in real time to ensure accurate data acquisition. Simultaneously, collision avoidance cameras, radar, and other equipment provide comprehensive protection for the USV's navigation safety, working in conjunction with the navigation control system to promptly detect and avoid potential dangers.

[0099] 5. This invention is applicable to a variety of marine research scenarios and application needs. Whether in scientific expeditions in the deep ocean or in environmental monitoring and resource surveys in coastal areas, it can leverage its advantages. Furthermore, its modular design concept gives the system excellent scalability and upgradeability, allowing for the easy addition or replacement of relevant equipment and modules according to different mission requirements and technological advancements, further enhancing the system's performance and application scope. Attached Figure Description

[0100] Figure 1 System framework diagram of the present invention.

[0101] Figure 2 A schematic diagram showing the positional relationship of the components and hardware of this invention;

[0102] Among them, 1 is an unmanned boat, 2 is a collision avoidance camera, 3 is antenna 3, 4 is radar, 5 is a flashing indicator light, 6 is an automatic winch monitoring camera, 7 is an intelligent navigation control system, 8 is an automatic winch, 9 is a wireless charging device, and 10 is a temperature, salinity and depth probe device.

[0103] Figure 3 The method flowchart of the present invention. Detailed Implementation

[0104] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0105] like Figures 1-2 The diagram shown is a system framework diagram and a device layout diagram of the present invention. The present invention is an automatic underway temperature, salinity and depth profile observation system for mesoscale eddy prediction, which is installed on an unmanned vessel 1 and connected to an automatic winch 8. The system is characterized by including: a remote intelligent navigation control system 7 and a temperature, salinity and depth probe device 10 connected to it.

[0106] Among them, the temperature, salinity and depth probe device 10 is set at the end of the A frame of the automatic winding winch 8. It is used to raise and lower the winch through the automatic winding winch 8, and then measure the temperature, salinity and depth parameters of seawater at different profiles, providing key ocean data for mesoscale eddy prediction. The measured data is transmitted to the mother ship / shore-based remote monitoring platform through the remote intelligent navigation control system 7.

[0107] In this embodiment, the automatic launch and recovery winch 8 is applied to a winch independently developed by the Institute of Oceanology, Chinese Academy of Sciences, and a corresponding patent has been applied for. The patent publication number is CN112455603A, and the patent title is: "Invention Patent for a Launch and Recovery Device and Method for a Mobile Temperature, Salinity and Depth Profiling Instrument". The temperature, salinity and depth probe device 10 is installed at the end of the A-frame of this device.

[0108] The remote intelligent navigation control system includes: a communication module, a shipborne control module, an internal status perception module, an external environment perception module, an intelligent navigation module, and a navigation control module. Its mother ship / shore-based remote monitoring platform is installed in a shore-based control room or on a research vessel. It receives various environmental and ship parameters sent by the unmanned vessel navigation control system through a gateway module and network communication. The mother ship / shore-based remote monitoring platform can control the automatic winch 8 through the communication module, thereby upgrading the temperature, salinity, and depth probe to measure the temperature, salinity, and depth data of seawater at different profiles. The temperature, salinity, and depth data are transmitted to the computer on the mother ship / shore-based remote monitoring platform through the communication module.

[0109] The communication module is used to transmit in real time the instructions issued by the mother ship / shore-based remote control monitoring platform to the unmanned vessel's automatic winch deployment and recovery, as well as the data feedback from the unmanned vessel 1 to the mother ship / shore-based remote control monitoring platform; the communication module is a Beidou and Tiantong dual-mode communication module, which sends the unmanned vessel's positioning, heading, and speed-related data parameters to the mother ship / shore-based remote control monitoring platform to realize remote monitoring of the mother ship / shore-based remote control monitoring platform;

[0110] The shipborne control module is used to receive, store, and transmit instructions issued by the mother ship / shore-based remote control monitoring platform, and send basic data and video image information of the unmanned vessel during navigation to the mother ship / shore-based monitoring platform in real time through the communication module; at the same time, it receives control instructions for the automatic winch sent by the mother ship / shore-based monitoring platform, controls the automatic winch, and thus realizes the upgraded control of the temperature, salinity, and depth probe.

[0111] The internal state perception module is used to collect basic data information on the unmanned vessel's navigation status in real time;

[0112] The external environment perception module is used to collect and fuse environmental data information in real time during the navigation of the unmanned vessel through remote sensors.

[0113] The intelligent navigation module is used to receive instructions transmitted by the shipborne control module, and generate a track or return track according to the instructions, and send it to the navigation control module.

[0114] The navigation control module is used to execute the instructions sent by the shipborne control module, and to acquire in real time the basic data information of the internal state perception module, the basic data information of the external environment perception module, the data information of the intelligent navigation module, and the data information of the mission operation assembly. Based on all the data information, it performs real-time control of the unmanned vessel 1, and at the same time, sends all the data information to the shipborne control module.

[0115] The intelligent navigation module includes: a path planning module, a path tracking module, and a return-to-home module;

[0116] The path planning module receives data from the external environment perception module, and performs path planning, generates a track, and performs navigation based on the data.

[0117] The path tracking module is used to monitor in real time whether the current driving status of the unmanned vessel deviates from the planned route through satellite navigation and inertial navigation. If a deviation occurs, a signal is sent to the navigation control module to adjust the unmanned vessel 1 to the planned route; otherwise, the current driving status remains unchanged.

[0118] The return-to-home module is used to generate a return-to-home track when communication is interrupted. The navigation control module then controls the return-to-home process based on the return-to-home track.

[0119] The path planning module includes: an obstacle detection module and an obstacle avoidance decision module;

[0120] The obstacle judgment module is used to predict obstacles based on the basic data information of the external environment perception module. For obstacles with uncertain data information, the module further expands the obstacle based on the predicted obstacle position data, thereby converting the uncertain obstacle position data into specific data and judging whether the obstacle is a static obstacle or a dynamic obstacle.

[0121] The obstacle avoidance decision module is used to avoid dynamic obstacles by changing the speed without changing the original trajectory; for static obstacles, it determines the difference in heading angle between itself and the obstacle, determines which maritime rules to apply, and then changes the speed and direction according to the content of the maritime rules, thereby changing the path to avoid the obstacle. After changing the path to avoid the obstacle, it returns to the original path.

[0122] Basic data information includes: speed, heading, bearing, position, attitude, battery charge, remaining fuel, engine speed, and rudder angle;

[0123] Environmental data information includes: inertial navigation information, radar information, laser information, visual information, AIS information, and nautical chart information.

[0124] The temperature, salinity, and depth probe device 10 includes: a pressure chamber, a temperature sensor, a conductivity cell, a pressure sensor, a power supply module, a data storage module, a data interaction protocol, and a GPS clock;

[0125] The pressure chamber, serving as an overall protective shell, is used to ensure the normal operation of various electronic components inside the chamber in the high-pressure environment of the deep sea;

[0126] A temperature sensor, with its probe exposed outside the pressure chamber, is in full contact with the surrounding seawater to measure the real-time temperature of the seawater.

[0127] The conductivity cell is installed inside the pressure-resistant chamber and has a channel for contacting seawater. It is used to measure the conductivity of seawater and obtain the salinity of seawater.

[0128] A pressure sensor, installed inside the pressure-resistant chamber, is used to sense the pressure change caused by the change in seawater depth, thereby obtaining the depth of the temperature, salinity, and depth probe device 10.

[0129] The power module, located inside the pressure-resistant chamber, provides a stable power supply to the entire temperature, salinity, and depth probe device 10, ensuring that all sensors and other modules continue to operate normally.

[0130] The data storage module is used to store the data collected by the temperature sensor, conductivity cell, and pressure sensor, ensuring the integrity and security of the data for subsequent analysis and research; and through specific communication interfaces and protocol specifications, it enables the collected data to be accurately transmitted to the remote intelligent navigation control system 7; the mother ship / shore-based monitoring platform host computer or other receiving equipment;

[0131] The GPS clock, integrated within the device, provides a precise time reference for the entire system, ensuring the accuracy of data acquisition and facilitating subsequent analysis of data at different points in time.

[0132] like Figure 2 As shown, this embodiment is applied to unmanned boat 1, which is also equipped with: a video monitoring module, an antenna 3, a radar 4, a flashing indicator light 5, and a wireless charging device 9.

[0133] The video surveillance module includes: a collision avoidance camera 2 and an automatic winch monitoring camera 6;

[0134] The collision avoidance camera 2 is installed on the top of the cabin of the unmanned vessel 1. It is an external camera part of the video monitoring module of the intelligent navigation control system 7. It is used to monitor the surrounding environment in real time, provide collision avoidance visual information for the unmanned vessel during navigation, and transmit the image data it collects to the remote intelligent navigation control system 7 to assist the remote intelligent navigation control system 7 in making navigation decisions.

[0135] The automatic winch monitoring camera 6 is an external camera of the video monitoring module used to monitor the working status of the automatic winch in real time and transmit the captured video image information to the video monitoring module so that the mother ship / shore-based remote control monitoring platform can understand the operation of the winch in real time and ensure the normal coordinated operation of the unmanned vessel and the automatic winch.

[0136] The communication module of the remote intelligent navigation control system transmits in real time commands from the mother ship / shore-based remote control monitoring platform to the unmanned vessel for automatic winch deployment and take-off, as well as data feedback from the unmanned vessel to the mother ship / shore-based remote control monitoring module. The communication module can adopt a Beidou and Tiantong dual-mode communication module, and send relevant data parameters such as the unmanned vessel's positioning, heading, and speed to the mother ship / shore-based remote control monitoring platform through antenna 3, so as to realize remote monitoring of the mother ship / shore-based remote control monitoring platform.

[0137] The shipborne control module of the automatic winch remote intelligent navigation control system receives, stores, and transmits instructions issued by the mother ship / shore-based remote control monitoring platform, and sends basic data and video image information collected by the video monitoring module during the unmanned vessel's navigation to the mother ship / shore-based monitoring platform in real time through the communication module.

[0138] Antenna 3 is located on the top of the cabin and is connected to the intelligent navigation control system 7. It is used to enhance the signal reception and transmission capabilities of Beidou and Tiantong dual-mode communication, and to ensure the stability and reliability of communication between the intelligent navigation control system 7 and the mother ship / shore-based remote control monitoring platform.

[0139] Radar 4 is located on the top of the cabin and is connected to the intelligent navigation control system 7. It is used to monitor obstacles and ship targets around the unmanned ship in real time, and the acquired radar information is integrated by the intelligent navigation control system 7 for path planning and navigation decision-making of the navigation control module.

[0140] The flashing indicator light 5 is located on the top of the unmanned vessel 1 and is connected to the remote intelligent navigation control system 7. It is used to alert surrounding vessels or personnel of the presence and working status of the unmanned vessel by flashing the light, so as to avoid collision accidents.

[0141] The wireless charging device 9 includes: a wireless charging transmitter with a de-oscillator, a wireless charging receiver, and an independent charging controller.

[0142] A wireless charging transmitter with a damper is installed at the front end of the A frame of the automatic winding winch 8. A wireless charging receiver is provided below the wireless charging transmitter. Both the wireless charging transmitter and the wireless charging receiver are equipped with watertight protective covers.

[0143] The wireless charging receiver has four coils, and the number of independent charging controllers is four. One wireless charging transmitter coil corresponds to two wireless charging receiver coils to ensure ideal charging performance.

[0144] In this embodiment, the equipment can be transported to the survey area aboard a mother ship, flexibly deployed to the target location, and automatically lowered and retrieved, achieving automated observation. The integrated equipment can complete simultaneous observations of temperature, salinity, and depth in a single deployment. After reaching the target depth, it can be quickly retrieved, and then a second deployment can begin, repeating the cycle. Calculations show that it can achieve 5-8 high-frequency observations per hour, which is 10 times faster than manual observation, effectively solving the problems of insufficient frequency or low temporal resolution in small-scale turbulence observations.

[0145] Furthermore, in this embodiment, the unmanned surface vessel 1 (USV1) does not interfere with other operations of the mother ship, allowing it to focus specifically on turbulent current observations. During USV1's automatic observation, the mother ship can navigate to other sites to conduct operations without needing to provide close support to USV1. USV1 can also form a formation with the mother ship to conduct synchronous and collaborative observations. This allows for collaborative observations where both vessels are in fixed positions or moving synchronously, and their relative positions and distances can be flexibly set according to the marine conditions, effectively addressing the issue of low spatial resolution.

[0146] like Figure 3 The diagram shown is a flowchart of the method of the present invention. The method of the automatic underway temperature, salinity, and depth profiling observation system for mesoscale eddy prediction of the present invention includes the following steps:

[0147] 1) The mother ship / shore-based remote control monitoring platform issues instructions: set the number of observations and the observation time of the mother ship / shore-based remote control monitoring platform when a data transmission to the shipboard control module is completed;

[0148] 2) The communication module of the remote intelligent navigation control system 7 receives the mission instructions issued by the mother ship / shore-based remote control monitoring platform. The shipboard control module stores the instructions and transmits them to the intelligent navigation module and the navigation control module respectively. The external environment perception module collects environmental data information in real time and performs fusion. The internal state perception module collects basic data information of the unmanned ship's navigation status in real time.

[0149] 3) The intelligent navigation module receives instructions transmitted by the shipborne control module, and generates a track or return track according to the instructions, and sends it to the navigation control module;

[0150] 4) The navigation control module executes the instructions sent by the shipborne control module and acquires the basic data information of the internal state perception module, the basic data information of the external environment perception module, the data information of the intelligent navigation module, and the data information of the task operation assembly in real time. Based on all the data information, it performs real-time control of the unmanned ship 1 and sends all the data information to the shipborne control module.

[0151] 5) When the unmanned vessel sails to the predetermined measurement area, the remote intelligent navigation control system 7 controls the automatic winch 8 to lower the temperature, salinity and depth probe device 10 into the seawater, and starts the measurement of relevant parameters of the seawater by the temperature, salinity and depth probe device 10.

[0152] 6) Temperature sensors, conductivity cells and pressure sensors collect data and store it in the data storage module. The data storage module transmits the data to the remote intelligent navigation control system 7 through a specific data interaction protocol and communication interface. The remote intelligent navigation control system 7 then transmits the data to the mother ship / shore-based remote control monitoring platform through its communication module.

[0153] 7) When communication is interrupted, the return module of the intelligent navigation module generates a return track, and the navigation control module controls the unmanned vessel to return according to the return track, thus completing the observation mission.

[0154] Step 3), specifically:

[0155] 3-1) The path planning module performs path planning and generates a flight path based on the environmental data information from the external environment perception module and in conjunction with the task instructions;

[0156] 3-2) During the path planning process, the obstacle judgment module predicts obstacles based on the basic data information of the external environment perception module. For obstacles with uncertain data information, the obstacle is further expanded based on the predicted obstacle position data to transform the uncertain obstacle position data into specific data and determine whether the obstacle is a static obstacle or a dynamic obstacle.

[0157] 3-3) For dynamic obstacles, the obstacle avoidance decision module changes the speed without changing the original trajectory to avoid the obstacle. For static obstacles, it judges the difference in heading angle with the obstacle, determines which maritime rule to apply, and then changes the speed and direction according to the content of the maritime rule, thereby changing the path to avoid the obstacle. After changing the path to avoid the obstacle, it returns to the original path.

[0158] 3-4) The path tracking module uses radar 4 to monitor in real time whether the current driving status of the unmanned vessel deviates from the planned route. If a deviation occurs, a signal is sent to the navigation control module, which adjusts the unmanned vessel 1 to travel to the planned route. Otherwise, the current driving status remains unchanged.

[0159] In step 4), the real-time control of the unmanned vessel 1 based on all the data information specifically includes:

[0160] 4-1) Data Acquisition Stage

[0161] Acquire basic data information from the internal state perception module, the external environment perception module, the intelligent navigation module, and the task operation assembly;

[0162] Among them, intelligent navigation data: Target trajectory data generated by path planning is received from the intelligent navigation module, including a series of target point coordinates (x, y, y). target ,y target The current navigation deviation information fed back by the path tracking module; if a deviation exists, the deviation angle and deviation distance are obtained.

[0163] Acquire task operation assembly data: Receive task operation assembly data, including the measurement point coordinate sequence of the temperature, salinity and depth measurement task and the status data of the automatic winch equipment;

[0164] 4-2) Data Fusion and Analysis Stage

[0165] a. Establish the state vector:

[0166] All the acquired data are combined into a comprehensive state vector S;

[0167] b. Target track matching analysis:

[0168] The current unmanned surface vessel's position coordinates (x, y) in the integrated state vector S are compared with the target point coordinates (x, y) of the target trajectory. target ,y target Perform a comparative analysis to calculate the distance d between the current position and the next target point. a and azimuth θ a , the formula is as follows:

[0169]

[0170] θ a =arctan2(y target -y,x target -x)

[0171] c. Based on the current heading θ and θ a The difference is used to determine whether a course adjustment is needed;

[0172] d. Obstacle risk assessment:

[0173] The presence of obstacles is determined based on radar and visual information; if an obstacle is detected, the distance d from the obstacle is used to determine its location. o Azimuth β o Given the current velocity V of the unmanned vessel, the collision time TTC is calculated as follows:

[0174]

[0175] If the TTC is less than the safety threshold, a collision risk is identified, and obstacle avoidance measures are required.

[0176] e. Environmental Factor Impact Analysis:

[0177] Considering the water depth h in the nautical chart information, combined with the draft h of the unmanned vessel... d To determine if there is a risk of stranding; if hh d If the depth is less than the safe water depth margin, a shallow water alarm will be issued and the navigation strategy will be adjusted. At the same time, the motion stability of the ship will be analyzed based on the acceleration and angular velocity data in the inertial navigation information. If abnormal fluctuations are found, the navigation status may need to be adjusted to ensure stability.

[0178] 4-3) Regulation Decision Generation Stage

[0179] Heading adjustment decision: If the target track matching analysis indicates that a heading adjustment is needed, the appropriate rudder angle adjustment Δδ is calculated using a PID control algorithm based on the difference between the current heading and the target heading, i.e.:

[0180]

[0181] Where, e(t)=θ a -θ, i.e., heading deviation, K P K i K d The parameters of the PID controller are tuned based on the dynamic characteristics and navigation environment of the unmanned vessel.

[0182] Speed ​​adjustment decision: Taking into account obstacle risk assessment, mission requirements, and environmental factors, decide whether to adjust the speed; if there is a collision risk, for dynamic obstacles, change the speed according to the obstacle avoidance decision module rules; for static obstacles, determine which maritime rules to apply based on the difference in heading angle with the obstacle, and if deceleration is required, calculate the appropriate speed reduction amount; at the same time, if the mission requires maintaining low-speed cruising in a specific area, or if environmental factors affect navigation efficiency, adjust the speed accordingly.

[0183] Integrated control command generation: Combine the calculated rudder angle adjustment Δδ and speed adjustment ΔV into an integrated control command C = [Δδ, ΔV];

[0184] 4-4) Implementation and Data Feedback Stage

[0185] Sending control commands: The integrated control command C is sent to the unmanned vessel's actuators, such as the servo motor and engine control system, to adjust the unmanned vessel's navigation status. The servo motor adjusts the rudder angle based on the received Δδ, and the engine control system adjusts the engine speed based on ΔV, thereby changing the unmanned vessel's course and speed;

[0186] Data feedback: All data involved in the control, namely all data in the state vector S and the generated control commands C, are sent back to the shipboard control module; the shipboard control module transmits these data to the mother ship / shore-based remote control monitoring platform through the communication module for real-time monitoring and subsequent data analysis; at the same time, the navigation control module itself records these data for retrospective analysis of the navigation process and fault diagnosis.

[0187] Step 5), specifically:

[0188] 5-1) Delegation Operation:

[0189] The remote intelligent flight control system 7 issues commands to control the operation of the automatic winding winch 8; since the temperature, salinity and depth probe device 10 is located at the end of the A frame of the automatic winding winch 8, the automatic winding winch 8 gradually lowers the cable connected to the temperature, salinity and depth probe device 10 according to the commands.

[0190] 5-2) Temperature Measurement

[0191] As the temperature, salinity, and depth probe device 10 is lowered into the seawater, the temperature sensor begins to operate. The probe of the temperature sensor is exposed outside the pressure-resistant chamber to ensure full contact with the surrounding seawater. The temperature sensor is based on the principle of a thermistor, whose resistance changes with the seawater temperature. When the probe comes into contact with the seawater, the heat from the seawater is transferred to the thermistor, causing a corresponding change in its resistance. By using a pre-calibrated relationship between resistance and temperature, the change in resistance is converted into a temperature value, thereby accurately measuring the real-time temperature of the seawater.

[0192] 5-3) Salinity Measurement

[0193] When the temperature, salinity, and depth probe device 10 is in seawater, seawater flows into the conductivity cell through the channel. The conductivity cell is equipped with two electrodes. When a certain voltage is applied across the electrodes, ions in the seawater will move directionally under the influence of the electric field, forming an electric current. By measuring the magnitude of the current, the conductivity of the seawater is calculated according to Ohm's law. Then, using a specific algorithm, the conductivity is converted into the salinity of the seawater.

[0194] 5-4) Depth Measurement

[0195] The pressure sensor is a piezoresistive pressure sensor. When seawater pressure acts on the sensor's sensitive element, the resistance value of the sensitive element changes and is proportional to the magnitude of the pressure. As the temperature, salinity, and depth probe device 10 continues to sink, the seawater pressure gradually increases, and the resistance value of the pressure sensor changes accordingly. By measuring the change in resistance value and combining it with the pre-calibrated pressure-depth conversion relationship, the depth of the temperature, salinity, and depth probe device 10 is obtained.

[0196] 5-5) Throughout the measurement process, the power module continuously provides a stable power supply to the temperature sensor, conductivity cell, pressure sensor, and data storage module, ensuring that each module can operate continuously and normally.

[0197] 5-6) The data storage module stores the data collected by the temperature sensor, conductivity cell and pressure sensor in real time to ensure the integrity and security of the data. This data can then be transmitted to the remote intelligent navigation control system 7 via the data interaction protocol, and then from the remote intelligent navigation control system 7 to the mother ship / shore-based remote control monitoring platform. At the same time, the GPS clock provides a precise time reference for the entire measurement process, ensuring the accuracy of the data acquisition time and facilitating the subsequent analysis and comparison of data at different time points.

[0198] Those skilled in the art will understand that the above description is merely a preferred embodiment of the present invention, and the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. This is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0199] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention. Clearly, those skilled in the art can make various alterations and modifications to the invention without departing from its spirit and scope. Thus, if these modifications and modifications of the invention fall within the scope of the claims and their equivalents, the invention is also intended to include these modifications and modifications.

Claims

1. An automated underway temperature, salinity, and depth profiling system for mesoscale eddy prediction, mounted on an unmanned vessel (1) and connected to an automated winch (8), characterized in that, include: The remote intelligent flight control system (7) and the temperature, salinity and depth probe device (10) connected to it; The temperature, salinity and depth probe device (10) is set at the end of the A frame of the automatic winding winch (8), and is used to raise and lower the winch by the automatic winding winch (8) to measure the temperature, salinity and depth parameters of seawater at different profiles, providing key ocean data for mesoscale eddy prediction; the measured data is transmitted to the mother ship / shore-based remote control monitoring platform through the remote intelligent navigation control system (7); The aforementioned intelligent navigation control system includes: a communication module, a shipborne control module, an internal status perception module, an external environment perception module, an intelligent navigation module, and a navigation control module; The communication module is used to transmit in real time the instructions issued by the mother ship / shore-based remote control monitoring platform to the unmanned vessel for automatic winch deployment and take-off, as well as the data feedback from the unmanned vessel (1) to the mother ship / shore-based remote control monitoring platform; the communication module is a Beidou and Tiantong dual-mode communication module, which sends the unmanned vessel's positioning, heading, and speed-related data parameters to the mother ship / shore-based remote control monitoring platform to realize remote monitoring of the mother ship / shore-based remote control monitoring platform; The shipborne control module is used to receive, store and transmit instructions issued by the mother ship / shore-based remote control monitoring platform, and send basic data information and video image information of the unmanned vessel during navigation to the mother ship / shore-based monitoring platform in real time through the communication module; at the same time, it receives control instructions for the automatic winch sent by the mother ship / shore-based monitoring platform, controls the automatic winch, and thus realizes the upgraded control of the temperature, salinity and depth probe. The internal state perception module is used to collect basic data information on the unmanned vessel's navigation status in real time. The basic data information includes: speed, heading, bow, position, attitude, battery charge, remaining fuel, engine speed, and rudder angle; environmental data information includes: inertial navigation information, radar information, laser information, visual information, AIS information, and nautical chart information. The external environment perception module is used to collect and fuse environmental data information in real time during the unmanned vessel's navigation. The intelligent navigation module is used to receive instructions transmitted by the shipborne control module, and generate a track or return track according to the instructions, and send it to the navigation control module. The navigation control module is used to execute the instructions sent by the shipborne control module, and to obtain the basic data information of the internal state perception module, the basic data information of the external environment perception module, the data information of the intelligent navigation module and the data information of the task operation assembly in real time. It also controls the unmanned ship (1) in real time based on all the data information, and sends all the data information to the shipborne control module. The real-time control of the unmanned vessel (1) based on all data information is specifically as follows: 4-1) Data Acquisition Stage: Acquire basic data information from the internal state perception module, the external environment perception module, the intelligent navigation module, and the task operation assembly; Among them, intelligent navigation data: Target trajectory data generated by path planning is received from the intelligent navigation module, including a series of target point coordinates (x, y, y). target ,y target The current navigation deviation information fed back by the path tracking module; if a deviation exists, the deviation angle and deviation distance are obtained. Acquire task operation assembly data: Receive task operation assembly data, including the measurement point coordinate sequence of the temperature, salinity and depth measurement task and the status data of the automatic winch equipment; 4-2) Data Fusion and Analysis Stage: a. Establish a state vector: Combine all the acquired data into a comprehensive state vector S; b. Target trajectory matching analysis: The current unmanned surface vessel's position coordinates (x, y) in the integrated state vector S are compared with the target point coordinates (x, y) of the target trajectory. target ,y target Perform a comparative analysis to calculate the distance d between the current position and the next target point. a and azimuth θ a ,Right now: c. Based on the current heading θ and θ a The difference is used to determine whether a course adjustment is needed; d. Obstacle Risk Assessment: Determine the presence of obstacle threats based on radar and visual information; if an obstacle is detected, assess the distance d from the obstacle. o Azimuth β o Given the current velocity V of the unmanned vessel, the collision time TTC is calculated as follows: If the TTC is less than the safety threshold, a collision risk is identified, and obstacle avoidance measures are required. e. Environmental Factor Impact Analysis: Considering the water depth h from the nautical chart information, combined with the draft h of the unmanned vessel. d To determine if there is a risk of stranding; if hh d If the water depth is less than the safe depth margin, a shallow water alarm will be issued and the navigation strategy will be adjusted. At the same time, the motion stability of the ship will be analyzed based on the acceleration and angular velocity data in the inertial navigation information. If abnormal fluctuations are found, the navigation state needs to be adjusted to ensure stability. 4-3) Regulation Decision Generation Stage: Heading adjustment decision: If the target track matching analysis indicates that a heading adjustment is needed, the appropriate rudder angle adjustment Δδ is calculated using a PID control algorithm based on the difference between the current heading and the target heading, i.e.: Δδ = Where, e(t)=θ a -θ, i.e., heading deviation, K P K i K d The parameters of the PID controller are tuned based on the dynamic characteristics and navigation environment of the unmanned vessel. Speed ​​adjustment decision: Taking into account obstacle risk assessment, mission requirements and environmental factors, decide whether to adjust the speed; if there is a collision risk, for dynamic obstacles, change the speed according to the rules of the obstacle avoidance decision module; for static obstacles, determine which maritime rules to apply based on the difference in heading angle with the obstacle, and if deceleration is required, calculate the amount of speed reduction. Integrated control command generation: Combine the calculated rudder angle adjustment Δδ and speed adjustment ΔV into an integrated control command C = [Δδ, ΔV]; 4-4) Implementation and Data Feedback Phase: Sending control commands: The integrated control command C is sent to the actuators of the unmanned vessel to adjust the navigation status of the unmanned vessel; the rudder adjusts the rudder angle according to the received Δδ, and the engine control system adjusts the engine speed according to ΔV, thereby changing the course and speed of the unmanned vessel; Data feedback: All data involved in the control, namely all data in the state vector S and the generated control commands C, are sent back to the shipboard control module; the shipboard control module transmits the data to the mother ship / shore-based remote control monitoring platform through the communication module for real-time monitoring and subsequent data analysis; at the same time, the navigation control module records the data itself for retrospective analysis of the navigation process and fault diagnosis.

2. The automated underway temperature, salinity, and depth profiling system for mesoscale eddy prediction according to claim 1, characterized in that, The intelligent navigation module includes: a path planning module, a path tracking module, and a return-to-home module; The path planning module is used to receive data information from the external environment perception module, and perform path planning, generate a track, and perform navigation based on the data information from the external environment perception module. The path tracking module is used to monitor in real time whether the current driving state of the unmanned vessel deviates from the planned route through satellite navigation and inertial navigation. If a deviation occurs, a signal is sent to the navigation control module to adjust the unmanned vessel (1) to drive to the planned route; otherwise, the current driving state remains unchanged. The return-to-home module is used to generate a return-to-home track when communication is interrupted, and the navigation control module controls the return-to-home based on the return-to-home track.

3. The automated underway temperature, salinity, and depth profiling system for mesoscale eddy prediction according to claim 2, characterized in that, The path planning module includes: an obstacle detection module and an obstacle avoidance decision module; The obstacle judgment module is used to predict obstacles based on the basic data information of the external environment perception module. For obstacles with uncertain data information, the module further expands the obstacle based on the predicted obstacle position data, thereby converting the uncertain obstacle position data into specific data and judging whether the obstacle is a static obstacle or a dynamic obstacle. The obstacle avoidance decision module is used to avoid dynamic obstacles by changing the speed without changing the original trajectory; for static obstacles, it determines the difference in heading angle between itself and the obstacle, determines which maritime rule to apply, and then changes the speed and direction according to the content of the maritime rule, thereby changing the path to avoid the obstacle. After changing the path to avoid the obstacle, it returns to the original path.

4. The automated underway temperature, salinity, and depth profiling system for mesoscale eddy prediction according to claim 1, characterized in that, The temperature, salinity, and depth probe device (10) includes: a pressure chamber, a temperature sensor, a conductivity cell, a pressure sensor, a power supply module, a data storage module, a data interaction protocol, and a GPS clock; The pressure-resistant chamber, as the overall protective outer shell, is used to ensure the normal operation of various electronic components inside the chamber in the high-pressure environment of the deep sea; The temperature sensor has its probe exposed outside the pressure-resistant chamber, in full contact with the surrounding seawater, to measure the real-time temperature of the seawater. The conductivity cell is installed inside the pressure-resistant chamber and has a channel for contacting seawater, used to measure the conductivity of seawater and obtain the salinity of seawater. The pressure sensor is installed in the pressure-resistant chamber to sense the pressure change caused by the change in seawater depth, and thus obtain the depth of the temperature, salinity and depth probe device (10). The power module is located inside the pressure chamber and provides a stable power supply for the entire temperature, salinity and depth probe device (10). The data storage module is used to store the data collected by the temperature sensor, conductivity cell and pressure sensor to ensure the integrity and security of the data for subsequent analysis and research; and through the communication interface and protocol specifications, the collected data can be accurately transmitted to the remote intelligent navigation control system (7); the host computer of the mother ship / shore-based monitoring platform or other receiving equipment; The GPS clock, integrated within the device, provides a precise time reference for the entire system, ensuring the accuracy of data acquisition and facilitating subsequent analysis of data at different points in time.

5. The automated underway temperature, salinity, and depth profiling system for mesoscale eddy prediction according to claim 1, characterized in that, Also includes: The video surveillance module, antenna (3), radar (4), and wireless charging device (9) are included. The video monitoring module includes: a collision avoidance camera (2) and an automatic winch monitoring camera (6); The collision avoidance camera (2) is installed on the top of the cabin of the unmanned boat (1). It is an external camera part of the video monitoring module of the intelligent navigation control system (7). It is used to monitor the surrounding environment in real time, provide collision avoidance visual information for the unmanned boat during navigation, and transmit the image data it collects to the remote intelligent navigation control system (7) to assist the remote intelligent navigation control system (7) in making navigation decisions. The automatic winch monitoring camera (6) is an external camera of the video monitoring module used to monitor the working status of the automatic winch in real time and transmit the captured video image information to the video monitoring module so that the mother ship / shore-based remote control monitoring platform can understand the operation of the winch in real time and ensure the normal coordinated operation of the unmanned ship and the automatic winch. The antenna (3) is located on the top of the cabin and connected to the intelligent navigation control system (7) to enhance the signal reception and transmission capabilities of Beidou and Tiantong dual-mode communication, and to ensure the stability and reliability of communication between the remote intelligent navigation control system (7) and the mother ship / shore-based remote control monitoring platform. The radar (4) is located on the top of the cabin and is connected to the intelligent navigation control system (7). It is used to monitor obstacles and ship targets around the unmanned ship in real time, and the acquired radar information is fused by the intelligent navigation control system (7) for path planning and navigation decision-making of the navigation control module of the intelligent navigation control system (7). The wireless charging device (9) includes: a wireless charging transmitter with a damper, a wireless charging receiver, and an independent charging controller. A wireless charging transmitter with a damper is installed at the front end of the A frame of the automatic winding winch (8), and a wireless charging receiver is provided below the wireless charging transmitter. Both the wireless charging transmitter and the wireless charging receiver are equipped with watertight protective covers.

6. A method for an automated underway temperature, salinity, and depth profiling system for mesoscale eddy prediction according to any one of claims 1 to 5, characterized in that, Includes the following steps: 1) The mother ship / shore-based remote control monitoring platform issues instructions: set the number of observations and the observation time of the mother ship / shore-based remote control monitoring platform when a data transmission to the shipboard control module is completed; 2) The communication module of the remote intelligent navigation control system (7) receives the task instructions issued by the mother ship / shore-based remote control monitoring platform. The shipboard control module stores the instructions and transmits them to the intelligent navigation module and the navigation control module respectively. The external environment perception module collects environmental data information in real time and performs fusion. The internal state perception module collects basic data information of the unmanned ship's navigation status in real time. 3) The intelligent navigation module receives instructions transmitted by the shipborne control module, and generates a track or return track according to the instructions, and sends it to the navigation control module; 4) The navigation control module executes the instructions sent by the shipboard control module and obtains the basic data information of the internal state perception module, the basic data information of the external environment perception module, the data information of the intelligent navigation module and the data information of the task operation assembly in real time. It then adjusts the unmanned ship (1) in real time based on all the data information and sends all the data information to the shipboard control module. 5) When the unmanned vessel sails to the predetermined measurement area, the remote intelligent navigation control system (7) controls the automatic winch (8) to lower the temperature, salinity and depth probe device (10) into the seawater and start the temperature, salinity and depth probe device (10) to measure the relevant parameters of the seawater. 6) Temperature sensors, conductivity cells and pressure sensors store the collected data in the data storage module. The data storage module transmits the data to the remote intelligent navigation control system (7) through the data interaction protocol and communication interface. The remote intelligent navigation control system (7) then transmits the data to the mother ship / shore-based remote control monitoring platform through the communication module. 7) When communication is interrupted, the return module of the intelligent navigation module generates a return track, and the navigation control module controls the unmanned vessel to return according to the return track, thus completing the observation mission.

7. The method of an automated underway temperature, salinity, and depth profiling observation system for mesoscale eddy prediction according to claim 6, characterized in that, Step 3) specifically includes: 3-1) The path planning module performs path planning and generates a flight path based on the environmental data information from the external environment perception module and in conjunction with the task instructions; 3-2) During the path planning process, the obstacle judgment module predicts obstacles based on the basic data information of the external environment perception module. For obstacles with uncertain data information, the obstacle is further expanded based on the predicted obstacle position data to transform the uncertain obstacle position data into specific data and determine whether the obstacle is a static obstacle or a dynamic obstacle. 3-3) For dynamic obstacles, the obstacle avoidance decision module changes the speed without changing the original trajectory to avoid the obstacle. For static obstacles, it judges the difference in heading angle with the obstacle, determines which maritime rule to apply, and then changes the speed and direction according to the content of the maritime rule, thereby changing the path to avoid the obstacle. After changing the path to avoid the obstacle, it returns to the original path. 3-4) The path tracking module uses radar (4) to monitor in real time whether the current driving status of the unmanned vessel deviates from the planned route. If a deviation occurs, a signal is sent to the navigation control module, which adjusts the unmanned vessel (1) to travel to the planned route. Otherwise, the current driving status remains unchanged.

8. The method of an automated underway temperature, salinity, and depth profiling observation system for mesoscale eddy prediction according to claim 6, characterized in that, Step 5) specifically includes: 5-1) Delegation Operation: The remote intelligent flight control system (7) issues commands to control the operation of the automatic winding winch (8); since the temperature, salinity and depth probe device (10) is set at the end of the A frame of the automatic winding winch (8), the automatic winding winch (8) gradually lowers the cable connected to the temperature, salinity and depth probe device (10) according to the commands. 5-2) Temperature measurement: As the temperature, salinity, and depth probe device (10) is lowered into the seawater, the temperature sensor begins to work. The probe of the temperature sensor is exposed outside the pressure-resistant chamber so that the probe can fully contact the surrounding seawater. The temperature sensor is based on the principle of thermistor, and the resistance value of the thermistor changes with the change of seawater temperature. When the probe comes into contact with the seawater, the heat of the seawater is transferred to the thermistor, and the resistance value of the thermistor changes accordingly. Through the pre-calibrated correspondence between the resistance value and the temperature, the change in resistance value is converted into a temperature value, thereby accurately measuring the real-time temperature of the seawater. 5-3) Salinity measurement: When the temperature, salinity and depth probe device (10) is in the seawater, the seawater flows into the conductivity cell through the channel. The conductivity cell is equipped with two electrodes. When a certain voltage is applied to the two ends of the electrodes, the ions in the seawater will move in a direction under the action of the electric field and form a current. By measuring the magnitude of the current, the conductivity of the seawater is calculated according to Ohm's law, and then the conductivity is converted into the salinity of the seawater. 5-4) Depth measurement: The pressure sensor is a piezoresistive pressure sensor. When seawater pressure acts on the sensitive element of the sensor, the resistance value of the sensitive element will change and is proportional to the magnitude of the pressure. As the temperature, salinity and depth probe device (10) continues to sink, the seawater pressure gradually increases, and the resistance value of the pressure sensor also changes accordingly. By measuring the change in resistance value and combining it with the pre-calibrated pressure-depth conversion relationship, the depth of the temperature, salinity and depth probe device (10) can be obtained. 5-5) Throughout the measurement process, the power module continuously provides a stable power supply to the temperature sensor, conductivity cell, pressure sensor, and data storage module, ensuring that each module can operate continuously and normally. 5-6) The data storage module stores the data collected by the temperature sensor, conductivity cell and pressure sensor in real time to ensure the integrity and security of the data, so that the data can be transmitted to the remote intelligent navigation control system (7) through the data interaction protocol, and then transmitted by the remote intelligent navigation control system (7) to the mother ship / shore-based remote control monitoring platform; at the same time, the GPS clock provides a precise time reference for the entire measurement process, ensuring the time accuracy of data collection, and facilitating the subsequent analysis and comparison of data at different time points.

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