A method, system and device for controlling a marine buoy antenna based on multi-source perception

Abstract

The application discloses a kind of offshore buoy antenna control methods based on multi-source perception, comprising: collecting buoy data and satellite orbit parameters, based on buoy data to judge sea state, combined with satellite orbit parameters to judge: sea state grade reaches or exceeds preset sea state threshold and satellite orbit parameter is lower than preset satellite threshold, conform to time disable all tilt antennas, only keep vertical antenna, and send instruction to switch;Otherwise, it is normal condition, at this time, the antenna with the highest equivalent gain in all available antennas is selected as the communication antenna, and the instruction is sent to switch;Before sending instruction switches, first judge whether it meets the sending condition, directly switch if it meets, otherwise delay.The application fuses satellite orbit, attitude perception, sea state judgment, time slot scheduling and other multi-dimensional information, forms perception, decision and execution closed loop;Sea state grade is used as the hard condition of low elevation angle antenna enable, to realize beforehand avoidance, avoid invalid emission.

Description

Technical Field

[0001] This invention relates to the field of wireless communication, and more specifically, to a method, system, and apparatus for controlling marine buoy antennas based on multi-source sensing. Background Technology

[0002] Ocean observation satellite communication buoys are the core infrastructure of a three-dimensional marine environmental monitoring network. They continuously collect key marine environmental parameters such as hydrology, meteorology, and water quality through various onboard sensors, and transmit the observation data back to the shore-based monitoring center in real time via satellite communication links. They are crucial equipment supporting marine disaster prevention and mitigation, marine resource development, and research on air-sea interactions. The stability of their communication system directly determines the continuity and reliability of the observation data, and is essential for ensuring the buoy's long-term stable operation under complex sea conditions. Current optimization strategies for satellite communication on ocean observation buoys include the following: Strategy 1: Using a multi-antenna array, RF switch matrix, and signal strength detection circuit, data transmission is completed by switching to the channel with the optimal signal after real-time measurement of the received signal strength of each antenna. Strategy 2: Relying on a satellite orbit prediction module and servo control mechanism, satellite visibility is calculated in advance, and antennas are scheduled to point towards the target satellite, enabling seamless communication during multiple satellite transit periods. Strategy 3: Integrating environmental sensors such as anemometers and wave height meters, combined with a communication quality monitoring module, communication power and transmission rate are dynamically adjusted based on sea state parameters. Strategy 4: Using reconfigurable antenna elements and phase control circuits, the antenna radiation pattern is dynamically adjusted to enhance the directional signal to the target satellite. These technologies attempt to improve the stability of buoy satellite communication from different dimensions, including antenna selection, satellite scheduling, environmental adaptation, and radiation pattern optimization.

[0003] However, all of the aforementioned existing technologies have significant drawbacks in adapting to the complex application scenarios of deep-sea buoys: Scheme 1 is a passive response mechanism, which can only trigger switching after the communication quality deteriorates, cannot predict the trend of signal changes, has high switching latency, and cannot distinguish between short-term wave obstruction and signal attenuation caused by buoy attitude deviation, easily leading to unnecessary frequent switching; Scheme 2 relies entirely on mechanical servo structures to complete antenna pointing adjustment, resulting in a complex overall structure, low reliability, slow switching speed, and high power consumption, making it difficult to adapt to the dynamic sea conditions of buoy swaying, and extremely difficult to maintain in long-term unattended scenarios; Scheme 3 suffers from a disconnect between environmental perception and communication control logic, relying on post-event measurement data for adjustments, failing to form a complete perception-decision-execution closed loop, and the integration of multiple sensors leads to high system redundancy, high algorithm computational load, and difficulty in guaranteeing real-time performance; Scheme 4's orientation pattern reconstruction scheme has high hardware costs and high power consumption, completely failing to meet the core requirement of long-term low-power operation of buoys. These shortcomings collectively make it difficult for existing technologies to ensure continuous and stable satellite communication for marine observation buoys in extreme sea conditions while meeting the requirements of low power consumption, high reliability, and fast response. Summary of the Invention

[0004] The present invention aims to overcome at least one defect in the prior art and provide a method, system and device for controlling marine buoy antennas based on multi-source sensing, in order to solve the problems existing in the background mentioned above.

[0005] The technical solution adopted in this invention is a method for controlling a marine buoy antenna based on multi-source sensing, comprising the following steps: S1. Collect buoy data and satellite orbit parameters; S2. Calculate the current sea state level based on the buoy data; S3. Based on the sea state level and the satellite orbit parameters, determine whether the sea state level reaches or exceeds the preset sea state threshold and the satellite orbit parameters are lower than the preset satellite threshold. If yes, disable all tilt antennas and retain only the vertical antennas, and proceed to step S5; otherwise, proceed to step S4. S4. Calculate the equivalent gain of all available antennas in the buoy, and select the antenna with the highest equivalent gain as the communication antenna. S5. Switch the communication antenna to the transceiver link for communication.

[0006] By establishing a direct link between attitude perception and sea state assessment, and using sea state level as a hard condition for antenna enablement, antenna adjustments based on attitude changes can be made quickly and accurately. High-risk antennas can be proactively shut down before adverse environments arrive, fundamentally avoiding invalid transmissions and achieving stable transmission.

[0007] In order to collect accurate data, the specific steps of step S1, which involve collecting buoy data and satellite orbit data, are as follows: S11. Collect and process the buoy's position, acceleration data, and attitude angle data, and calculate the buoy's roll angle, pitch angle, and yaw angle; S12. Based on the satellite orbital parameters and buoy position, and the planning of satellite tracking and communication links, the SGP4 orbital prediction model is used to calculate the azimuth and elevation angles of the satellite at future moments, generating the satellite trajectory. The inputs of the SGP4 orbital prediction model include the TLE orbital elements and the prediction time, and the output is the position and velocity of the satellite in the geocentric coordinate system.

[0008] Collecting buoy acceleration and attitude angle data facilitates subsequent sea state calculations. Transforming TLE data into three-dimensional spatial coordinates, i.e., position / velocity, supports real-time trajectory monitoring for automatic antenna pointing. Predicting the trajectory of the nadir point and the visible time window, calculating antenna elevation / azimuth angle and path loss, and optimizing satellite communication network resource allocation and automatic tracking control.

[0009] In order to conduct environmental assessment and sea state classification, the specific steps of step S2, which involve calculating the current sea state level based on buoy data, are as follows: S21. Squaring, averaging, and taking the square root of the sampled vertical acceleration values ​​of the buoy to obtain the root mean square of the acceleration; S22. Calculate the deviation between each roll angle sample value and the average value, square it, average it, and take the square root to obtain the standard deviation of the roll angle. S23. Calculate the deviation between each pitch angle sample value and the average value, square it, average it, and take the square root to obtain the standard deviation of the pitch angle; S24. The root mean square value of acceleration, the standard deviation of roll angle, and the standard deviation of pitch angle are compared with preset thresholds to determine the sea state level. Sea conditions are classified from calm to severe according to their degree.

[0010] By using a sliding window to statistically analyze the root mean square of acceleration and the standard deviation of attitude from the attitude sensor, we can distinguish between calm seas and rough seas, thus preventing the selection of the wrong antenna under severe shaking.

[0011] To achieve low-latency handover, the calculation of the equivalent gain of all available antennas in the buoy in step S4 includes: S41. Transform the antenna mounting direction vector from the body coordinate system to the world coordinate system using the attitude rotation matrix to obtain the antenna world coordinate direction vector; S42. Calculate the dot product of the antenna world coordinate direction vector and the satellite unit direction vector, and take the inverse cosine to obtain the included angle; S43. According to the included angle, look up the antenna pattern lookup table and obtain the ideal gain through linear interpolation; S44. Obtain the weighting factor according to the sea state level, and multiply the ideal gain by the weighting factor to obtain the equivalent gain; Among them, the weighting factor decreases as the sea state level increases.

[0012] By combining ephemeris prediction, positioning, and attitude calculation, the equivalent gain of each antenna in the satellite direction is predicted, enabling low-latency handover.

[0013] Preferably, the attitude transformation matrix is ​​obtained by transforming the roll angle, pitch angle, and yaw angle using Euler angles.

[0014] To obtain the coordinates of the buoy, the coordinate system transformation path in step S41 is as follows: Earth-centered and Earth-fixed coordinate system ECEF, local horizontal coordinate system NED, and buoy body coordinate system.

[0015] By transforming the coordinate system, subsequent calculations can better fit the conditions of the buoy.

[0016] Preferably, the antenna pattern lookup table pre-stores the gain values ​​of each antenna at different angles, and obtains the gain at any angle through linear interpolation.

[0017] To ensure uninterrupted communication, the switching logic for switching antennas in step S5 includes: Priority protection: Ensure that at least one antenna remains connected during handover; Fast switching: The switching setup time is less than a preset threshold; State maintenance: Keep the antenna connection stable during communication.

[0018] By prioritizing protection, fast switching, and maintaining state, normal communication can be maintained even during antenna switching.

[0019] To reduce invalid launches, a safe mode procedure is also included: When the collected buoy data or satellite orbit parameters are invalid, enter safe mode; In safe mode, the vertical antenna is forcibly locked and the transmit power is reduced.

[0020] When buoy data or satellite orbit parameters are invalid, it is either due to poor sea conditions or poor satellite conditions. In this case, locking the vertical antenna and reducing the transmission power can reduce the transmission inefficiency and reduce losses under poor sea conditions or poor satellite conditions.

[0021] To achieve intelligent caching, a communication scheduling step is also included, executed before switching communication antennas, including: Check whether it is within the allowed communication time window and whether the battery level is higher than the preset threshold. If the antenna is within the communication time window and the battery level is higher than the preset threshold, execute step S5; otherwise, buffer the data and wait for the next communication window.

[0022] By determining whether it is in a transmission time slot, checking the power status, and managing the transmission task queue, an intelligent buffering and delayed transmission mechanism is implemented.

[0023] A multi-source sensing-based marine buoy antenna control system, constructed based on the aforementioned multi-source sensing-based marine buoy antenna control method, includes: Sensing module: includes a positioning module, attitude sensor and ephemeris input interface, used to collect buoy position, attitude and satellite orbit data; Decision module: includes orbit predictor, sea state judgment module, antenna engine and communication scheduler, used to make antenna selection and communication scheduling decisions by integrating multi-source information; Execution module: includes a processor, RF switches, and transceiver links, used to perform antenna switching and data transmission and reception; Intelligent caching module: Used to store data to be sent, manage priority queues, and support data packet lifecycle management; Delayed transmission module: used to calculate the optimal transmission time based on orbit prediction, and delay the data transmission to the next communication window when the conditions are not met; Remote configuration module: used to receive remote configuration commands via satellite communication interface and update strategy parameters such as sea state threshold, elevation angle threshold and battery threshold; The output of the sea state judgment module is directly used as the enable condition input for the antenna selection engine, forming a closed-loop decision-making process of perception-decision-execution.

[0024] A device for controlling a marine buoy antenna based on multi-source sensing, as the core component of the aforementioned marine buoy antenna control system based on multi-source sensing, comprises a sensing module, a decision-making module, and an execution module, specifically including: The antenna array includes a vertically mounted antenna and at least one tilted antenna, the tilted antennas being spaced apart in the azimuth angle to cover different elevation angle regions; A single transceiver link, including a power amplifier, a low-noise amplifier, and the transceiver link; A single-pole multi-throw radio frequency switch, the common terminal of which is connected to the single transceiver link, and multiple switching terminals are respectively connected to each antenna in the antenna array; Attitude sensor: used to collect the buoy's acceleration and attitude angle data; Controller: Used to determine the sea state level based on the attitude sensor data, and control the radio frequency switch to switch the antenna according to the sea state level and satellite elevation angle; The controller is configured to: when the sea state level reaches or exceeds a preset threshold and the satellite elevation angle is lower than a preset threshold, control the radio frequency switch to connect only the vertical antenna and disable all tilt antennas.

[0025] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. Sea state hard enablement mechanism Using sea state level as a hard condition for enabling low elevation antennas replaces the traditional passive response based on signal strength, fundamentally avoiding invalid transmissions and improving communication success rate. 2. Low-cost multi-antenna diversity architecture By using a multi-antenna layout in conjunction with RF switches to achieve multiplexing of a single transceiver link, it is possible to improve the success rate of low-elevation communication at a low cost, resulting in high cost-effectiveness. 3. Low-latency predictive handover A predictive algorithm based on ephemeris prediction and attitude awareness enables low-latency handover, which is superior to the handover latency of existing systems and improves the success rate of first-time access. 4. Intelligent scheduling and energy-saving optimization Intelligent caching and delayed launch mechanisms avoid unnecessary energy consumption and extend the buoy's endurance. 5. Continuously optimized adaptive capability It supports remote updates of strategy parameters, enabling secondary deployment and continuous optimization. Parameters can be adjusted according to actual sea conditions to improve system adaptability and maintainability. 6. Decision-making closed loop based on full-dimensional perception By integrating multi-dimensional information such as satellite orbit, attitude perception, sea state assessment, and time slot scheduling, a closed loop of perception, decision-making, and execution is formed, enhancing the system's robustness. 7. Modular design Each functional module is independent, which facilitates maintenance and upgrades, supports hardware customization, and can adapt to different application scenarios. Attached Figure Description

[0026] The accompanying drawings are for illustrative purposes only and should not be construed as limiting the invention. To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0027] Figure 1 This is an antenna enable constraint diagram for a marine buoy antenna control method based on multi-source sensing according to the present invention.

[0028] Figure 2 This is a coordinate transformation path diagram for a multi-source sensing-based marine buoy antenna control method according to the present invention.

[0029] Figure 3 This is a three-layer architecture diagram of a marine buoy antenna control system based on multi-source sensing according to the present invention.

[0030] Figure 4 This is a flowchart of a multi-source sensing-based marine buoy antenna control system for judging sea conditions according to the present invention.

[0031] Figure 5 This is a flowchart illustrating the antenna selection process of a marine buoy antenna control system based on multi-source sensing, according to the present invention.

[0032] Figure 6 This is a communication scheduling flowchart of a marine buoy antenna control system based on multi-source sensing according to the present invention.

[0033] Figure 7 This is a flowchart illustrating the operation of a marine buoy antenna control system based on multi-source sensing according to the present invention.

[0034] Figure 8 This is a schematic diagram of the antenna layout of a marine buoy antenna control device based on multi-source sensing according to the present invention.

[0035] Figure 9 This is a schematic diagram of an antenna for a marine buoy antenna control device based on multi-source sensing according to the present invention. Detailed Implementation

[0036] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0038] Example 1 This proposal suggests a multi-source sensing-based method for controlling marine buoy antennas, comprising the following steps: S1. Collect buoy data and satellite orbit parameters; S11. Collect the buoy's position, acceleration data, and attitude angle data, and calculate the buoy's roll angle, pitch angle, and yaw angle; S12. Based on the satellite orbital parameters and buoy position, the SGP4 orbital prediction model is used to calculate the satellite's azimuth and elevation angles at future moments, generating the satellite trajectory.

[0039] The SGP4 orbit prediction model takes TLE orbital elements and prediction time as inputs and outputs the satellite's position and velocity in the geocentric-geofixed coordinate system.

[0040] When the collected buoy data or satellite orbit parameters are invalid, enter safe mode. In safe mode, forcibly lock the vertical antenna and reduce the transmission power. At the same time, perform anomaly handling: return to the default antenna, which is the vertical antenna, and log the error.

[0041] S2. Calculate the current sea state level based on buoy data; That is, the sea state is classified by statistically analyzing the root mean square of the buoy's acceleration and the standard deviation of its attitude using a sliding window; the duration of the sliding window is a configurable parameter that is adjusted according to the characteristics of sea state changes, specifically: S21. Square the vertical acceleration sample values ​​of the buoy within the sliding window, average the squared values, and then take the square root of the average value to obtain the root mean square of the acceleration. S22. Within the sliding window, calculate the deviation between each roll angle sample value and the average value, square the deviation, average the squared values, and then take the square root of the average value to obtain the standard deviation of the roll angle. S23. Within the sliding window, calculate the deviation between each pitch angle sample value and the average value, square the deviation, average the squared values, and then take the square root of the average value to obtain the standard deviation of the pitch angle. S24. Compare the root mean square value of acceleration, standard deviation of roll angle, and standard deviation of pitch angle with preset thresholds to determine the sea state level.

[0042] Sea state is divided into multiple levels, with at least one level defined as severe sea state. For example, there are four sea state levels: Level 0 (calm), Level 1 (light waves), Level 2 (moderate waves), and Level 3 (large waves). The threshold for each level is determined by comparing multiple sets of thresholds. The specific number of levels can be configured according to actual needs. The preset sea state threshold and preset elevation angle threshold are configurable parameters and can be dynamically updated via a remote configuration interface.

[0043] like Figure 1 As shown, S3, based on the sea state level and satellite orbit parameters, determine whether the constraints are met. If they are met, disable all tilt antennas and keep only the vertical antennas, then proceed to step S5; if they are not met, proceed to step S4. The constraints are: the sea state level reaches or exceeds the preset sea state threshold and the satellite orbit parameters are lower than the preset satellite threshold. By judging the constraints, multipath interference of low elevation angle signals under severe sea conditions is avoided.

[0044] The reasons for setting the constraints are as follows: ① The tilted antenna is designed with a high elevation angle, such as 45°-60°. At low elevation angles, the gain itself decreases significantly. ② In rough sea conditions, the buoy sways violently, making it easier for the beam of the tilted antenna to deviate from the direction of the satellite; ③ The vertical antenna provides omnidirectional coverage, is not sensitive to changes in buoy attitude, and is more stable and reliable at low elevation angles; ④ Low elevation angle signals are inherently susceptible to multipath interference from the sea surface, and the angle of the tilted antenna will exacerbate this problem.

[0045] S4. Calculate the equivalent gain of all available antennas in the buoy, and select the antenna with the highest equivalent gain as the communication antenna. The calculation of the antenna's equivalent gain includes: S41. Transform the antenna mounting direction vector from the body coordinate system to the world coordinate system using the attitude rotation matrix to obtain the antenna world coordinate direction vector; like Figure 2 As shown, the coordinate system transformation path is: Earth-centered and Earth-fixed coordinate system ECEF → local horizontal coordinate system NED → buoy body coordinate system; the attitude rotation matrix is ​​obtained by transforming the roll angle, pitch angle and yaw angle through Euler angles.

[0046] S42. Calculate the dot product of the antenna's world coordinate direction vector and the satellite's unit direction vector, and take the inverse cosine to obtain the included angle. S43. Look up the antenna pattern table based on the included angle, and obtain the ideal gain through linear interpolation; The antenna pattern lookup table pre-stores the gain values ​​of each antenna at different angles, and can obtain the gain at any angle through linear interpolation.

[0047] S44. Obtain the weighting factor based on the sea state level, and multiply the ideal gain by the weighting factor to obtain the equivalent gain; The mapping relationship of the weighting factors is as follows: Sea state 0 corresponds to 1.0, Sea state 1 corresponds to 0.9, Sea state 2 corresponds to 0.7, and Sea state 3 corresponds to 0.5. The weighting factor decreases as the sea state level increases. The weighting factor can be configured according to specific circumstances. The equivalent gain of an available antenna is equal to its weighted gain, and the equivalent gain of a disabled antenna is set to a minimum value.

[0048] After calculating the communication antenna, first check whether the check conditions are met, and then decide whether to proceed to step S5, which is as follows: Check whether it is within the communication time window, whether the battery level is higher than the preset value, and whether there are data packets to be sent. If the antenna is within the communication time window, the battery level is higher than the preset threshold, and there are no data packets to be sent, proceed to step S5; otherwise, buffer the data and wait for the next communication window.

[0049] S5. Switch the communication antenna to the transceiver link for communication; The transmit and receive links are shared with each antenna via time-division multiplexing, switching between receive and transmit modes.

[0050] To ensure continuous communication, the switching logic for switching antennas includes: Priority protection: Ensure that at least one antenna remains connected during handover; Fast switching: The switching setup time is less than a preset threshold; State maintenance: Keep the antenna connection stable during communication.

[0051] The total delay of switching antennas = decision delay + switch setup time + communication delay.

[0052] Example 2 like Figure 3 As shown, this embodiment provides a multi-source sensing-based marine buoy antenna control system to implement the multi-source sensing-based marine buoy antenna control method described in Embodiment 1. The system supports OTA updates and can update firmware and configuration parameters via a satellite communication interface. The system has a three-layer architecture: a perception layer, a decision layer, and an execution layer, specifically: The perception layer, also known as the perception module, is used to collect buoy position, attitude, and satellite orbit data; it includes: (1) Positioning module, which supports multiple satellite positioning systems, provides accurate time information and precise buoy position, such as latitude and longitude and altitude, to provide basic data for satellite orbit prediction.

[0053] Specific implementation: ① GPS, BeiDou, GLONASS, etc. provide high-precision positioning output; ② Provides a precise time reference for orbit prediction time synchronization; ③ Interface: Standard serial communication interface with strong anti-interference capability.

[0054] (2) Attitude sensor, which collects buoy attitude data in real time, including roll angle, pitch angle and yaw angle, and judges the current sea state level based on acceleration statistics.

[0055] Specific implementation: ① Employs a multi-axis inertial measurement unit (IMU), consisting of an accelerometer, gyroscope, and optional magnetometer; ② Sampling rate: Configurable, typical value is 100Hz; ③ Built-in temperature sensor for compensating for temperature drift; ④ Heading source: Built-in magnetometer or fusion algorithm.

[0056] Advantages of using IMU to indirectly infer sea state: a. Lower cost: The IMU is an essential sensor for attitude measurement, eliminating the need for additional sea state sensors such as anemometers and wave gauges; b. Faster response: IUM has a high sampling frequency and can reflect the buoy's motion status in real time, while environmental sensors have a slower response; c. More direct: The buoy's motion directly reflects the antenna's pointing stability and is more relevant to communication quality than wave height / wind speed; d. High reliability: Reduces the number of sensors, lowers the system failure rate, and simplifies system integration.

[0057] (3) Ephemeris input: Receive satellite orbit data and use it to calculate satellite position.

[0058] Specific implementation: ① Supports TLE (TWO-LINE ELEMENT) track element format; ②Supports remote updates of orbital data; ③ Store orbital data for multiple satellites.

[0059] like Figure 4 As shown, the decision layer, also known as the decision module, is used to make antenna selection and communication scheduling decisions by integrating information from multiple sources, including: (1) Orbit predictor: Based on satellite orbit data and buoy position, use orbit prediction models, such as SGP4, to calculate the current and future azimuth and elevation angles of the satellite and generate the satellite trajectory.

[0060] Specific implementation: ① Stores satellite orbit data and supports remote updates; ② The calculation step size is configurable, predicting the trajectory over a future period; ③ Output: Output for each satellite in the satellite list, including azimuth, elevation, distance, and visibility status.

[0061] Explanation of the orbit prediction model: Inputs: TLE orbital elements, prediction time, and buoy position; Output: The satellite's position and velocity in the Earth-centered, Earth-fixed (ECEF) coordinate system.

[0062] (2) Sea state judgment module: By using a sliding window to statistically analyze the root mean square of acceleration and the standard deviation of attitude angle, the severity of the current sea state is judged. Its output is directly used as the enable condition input for the antenna selection engine, forming a complete closed-loop decision-making process of perception-decision-execution.

[0063] Specific implementation: ① Sliding window: Configurable, typical value 5-10 seconds; ②Acceleration threshold: Configurable; ③ Attitude angle standard deviation threshold: Configurable; ④ Historical records: Stores sea state data for the most recent period; ⑤ Adaptive: The threshold is dynamically adjusted based on historical data.

[0064] Sea state classification logic:

[0065] (3) Antenna selection engine: The core decision module of the system, which integrates satellite direction, buoy attitude, sea state level and antenna layout, calculates the equivalent gain of each antenna, selects the best antenna and controls the switching of radio frequency switches.

[0066] like Figure 5As shown, the specific implementation is as follows: ①The workflow is as follows: a. Input: Satellite location, sea state level, and antenna list; b. Determine if the antenna list is empty. If it is empty, return directly to the vertical antenna and end the antenna selection. If it is not empty, determine if the elevation angle sea state is greater than or equal to the sea state threshold. If it is, disable all tilt antennas, select the vertical antenna, and end the antenna selection. If not, proceed to the next step. c. Traverse the antenna list, calculate the angle between the antenna and the satellite, look up the antenna pattern in the lookup table to obtain the ideal gain, obtain the weighting factor according to the sea state level, and multiply the ideal gain by the weighting factor to obtain the equivalent gain; d. Find the antenna with the highest equivalent gain. This antenna is the optimal antenna, and the antenna selection process is complete.

[0067] ②The algorithm includes: a. Calculate the satellite position and buoy attitude; b. Calculate the angle between each antenna direction and the satellite; c. Adjust the gain weights according to the sea state level; d. Calculate and sort the equivalent gains; ②Constraints: a. The tilt antenna is disabled when the sea state level reaches or exceeds the preset threshold and the elevation angle is below the preset threshold; b. Degrade to a vertical antenna when the power amplifier temperature is too high; c. Only the vertical antenna is retained when the battery level is below a preset threshold; d. Physical basis: - Tilt antennas are designed with a high elevation angle, typically 45°-60°, and their gain drops significantly at low elevation angles. - In rough sea conditions, the buoy sways violently, making it easier for the beam of the tilted antenna to deviate from the direction of the satellite. - The vertical antenna provides omnidirectional coverage, is insensitive to changes in buoy attitude, and is more stable and reliable at low elevation angles; - Low elevation angle signals are inherently susceptible to multipath interference from the sea surface, and the angle of the tilted antenna will exacerbate this problem.

[0068] (4) Communication scheduling module: Determine whether it is in a transmission time slot, check the power status, manage the transmission task queue, implement intelligent caching and delayed transmission mechanism, and optimize transmission efficiency.

[0069] like Figure 6 As shown, the specific implementation is as follows: ①Time slot management: Synchronized with satellite transit time, a communication window is reserved for each transit; if in a transmission time slot, power status is checked; if not in a transmission time slot, wait for the next time slot and check for remote updates; ② Power Management: Check if the battery level is greater than the battery threshold. If the battery level is less than or equal to the battery threshold, enter power saving mode and reduce the sensor sampling rate; if the battery level is greater than the battery threshold, enter the transmission queue. ③ Sending Task Queue Management: Check the sending task queue and the data priority. The priority queue is: Urgent > Data > Status. If the priority is urgent, send the command immediately. After sending, turn off the power amplifier and restore the low-power state. If the priority is other, check if the queue is full. If the queue is not full, enqueue the data and wait to send. After sending, turn off the power amplifier and restore the low-power state. If the queue is full, discard the low-priority data and enqueue the current data and wait to send. After sending, turn off the power amplifier and restore the low-power state.

[0070] ④ Caching strategy: First-in, first-out queue, data packet retention time is configurable; ⑤ Power amplifier control: soft start to avoid current surge; dynamic power adjustment; temperature protection mechanism.

[0071] (5) Remote configuration interface: Supports remote updating of system parameters, such as antenna selection strategy parameters, sea state threshold, power amplifier control strategy, etc., to achieve continuous system optimization; Specific implementation: ① Communication protocol: The original communication interface of the sampling satellite communication; ② Encryption: Supports data encryption; ③Updated content: Sea state threshold, elevation angle threshold, battery threshold, power amplifier curve parameters; ④ Security mechanisms: identity verification, rollback protection, and data verification.

[0072] Execution layer: also known as the execution module, is used to perform antenna switching and data transmission and reception; it includes: (1) Processor: The core control unit, which runs the antenna selection algorithm, controls the radio frequency switch, manages and schedules communication, and coordinates the work of each module.

[0073] Specific implementation: ① High-performance processor; ②Multiple interfaces: serial interface, parallel interface, timer, etc.; ③Task scheduling: main loop, sensor sampling, communication scheduling and power management.

[0074] (2) Radio frequency switch, which switches between multiple antennas and a single transceiver link to achieve time division multiplexing.

[0075] Specific implementation: ① Single-pole multi-throw RF switch, such as SP4T; ②Low insertion loss and high isolation; ③ Fast switching speed; ④ Control logic: Multiple control lines, priority protection.

[0076] Switches, such as SP4T control logic: - Four switching terminals are distributed and connected to: vertical antenna, first tilt antenna, second tilt antenna, and third tilt antenna; -The public terminal connects to a single set of transceiver links; - Control signals: 2-bit digital signals, such as 00 = vertical antenna, 01 = first tilt antenna, 10 = second tilt antenna, 11 = third tilt antenna; - Priority protection: Ensure that at least one antenna remains connected during handover; -Fast Switching: Switching setup time is less than a preset threshold; -State maintenance: Keep the antenna connection stable during communication.

[0077] (3) Transceiver link: Shared transceiver link, including power amplifier, low noise amplifier and transceiver, responsible for signal modulation, demodulation, amplification and filtering.

[0078] Specific implementation: ① Transceiver: Supports multiple frequency bands and multiple modulation methods; ② Power amplifier: The output power is adjustable and has a protection mechanism; ③ Low-noise amplifier: low noise figure, high linearity; ④ Power consumption: Multi-mode reception / transmission / sleep.

[0079] The system also includes an intelligent caching module, a delayed emission module, a remote configuration module, a power management module, and a filtering preprocessing module, as detailed below: Intelligent caching module: Used to store data to be sent, manage priority queues, and support data packet lifecycle management; includes: ① Priority queue: Supports hierarchical storage of urgent data, regular data, and status data.

[0080] ②First-In-First-Out (FIFO) strategy: Data packets are processed in the order they arrive.

[0081] ③Lifecycle Management: Data packets are configurable in terms of retention time and are automatically discarded after the timeout period.

[0082] Delayed transmission module: Used to calculate the optimal transmission timing based on orbit prediction, and to delay data transmission to the next communication window if the conditions are not met; includes: ①Time slot management: Synchronized with satellite transit time, a communication window is reserved for each transit.

[0083] ② Condition check: Check the transmission conditions such as time slot, power, and data queue.

[0084] ③ Window prediction: Calculate the next available communication window time based on trajectory prediction.

[0085] Remote configuration module: Used to receive remote configuration commands via satellite communication interface and update strategy parameters such as sea state threshold, elevation angle threshold, and battery threshold; including: ①Authentication: Authenticate remote configuration commands.

[0086] ② Data encryption: Configure data to support encrypted transmission.

[0087] ③ Rollback protection: Automatically roll back to the previous version when the update fails.

[0088] ④ Data verification: Verify and validate the integrity of the data.

[0089] Power management module: used to dynamically adjust system power consumption based on battery level and temperature; Filtering preprocessing module: Used to perform Kalman filtering or complementary filtering on the raw data acquired by the attitude sensor to remove high-frequency noise.

[0090] like Figure 7 As shown, the system's workflow is as follows: Data Acquisition and Preprocessing Steps: After system startup, the system first acquires the position, time, and satellite orbit data from the positioning module. The positioning module data is used to determine the buoy's position, and the satellite orbit data is used to determine the satellite's position. If either the positioning module data or the satellite orbit data is invalid, the system enters a safe mode, where the vertical antenna is forcibly locked and the transmission power is reduced.

[0091] Orbit prediction steps: Use the orbit prediction model to calculate the real-time azimuth and elevation angles of the satellite relative to the buoy.

[0092] Attitude perception steps: The attitude sensor collects buoy attitude data at a configurable frequency, reads the attitude sensor data at high frequency, and calculates the buoy's real-time attitude, including roll angle, pitch angle and yaw angle.

[0093] Sea state assessment steps: By using a sliding window to statistically analyze the root mean square value of acceleration and the standard deviation of attitude angles from the attitude sensors, the current sea state level is determined. The purpose of sea state classification is to distinguish between calm seas and rough seas, preventing the selection of the wrong antenna under severe turbulence.

[0094] Smart antenna selection steps: The antenna selection engine integrates satellite orientation, buoy attitude, and sea state information to calculate the equivalent gain of each antenna. Antenna selection constraints: When the satellite elevation angle is below a preset threshold and the sea state level is above a preset threshold, all tilt antennas are automatically disabled, retaining only the vertical antenna to avoid multipath interference of low-elevation signals in adverse sea conditions. Under normal circumstances, the system selects the antenna with the highest gain and connects it to the transceiver link via an RF switch.

[0095] Communication scheduling and transmission steps: The communication scheduling module checks the transmission conditions, including time slots, battery level, and data queue. If the conditions are met, the power amplifier starts transmitting data; if the conditions are not met, the data enters the buffer and waits for the next window.

[0096] Power management and remote maintenance steps, including anomaly handling and remote updates, low-power strategies and loops, are as follows: Error handling and remote update: Error handling: Returns the default antenna, which is the vertical antenna, and logs the error. Remote update: While waiting for the cache, the system checks the remote configuration and supports updating the sea state threshold or antenna policy. Low-power strategy: The power amplifier is turned off immediately after transmission is completed, and the low-power mode is restored; Cycle: After completing one cycle, the next cycle begins, enabling continuous monitoring.

[0097] The total delay of switching antennas = decision delay + switch setup time + communication delay.

[0098] The system supports remote updates of strategy parameters to achieve adaptive optimization. All key system parameters are configurable, including: Sea state threshold: The sea state level threshold used to determine whether to disable low elevation antennas; it can be adjusted according to the actual sea state environment. Elevation threshold: The satellite elevation threshold used to determine whether to disable low-elevation antennas; it can be adjusted according to satellite orbit characteristics. Battery threshold: The minimum battery level required to allow data transmission, which can be adjusted according to power management policies; Sensor sampling frequency: The data sampling rate of the attitude sensor, which can be adjusted according to real-time requirements and power consumption constraints; Sliding window duration: The size of the sliding window used for sea state assessment, which can be adjusted according to the characteristics of sea state changes; Cache queue size: The maximum length of the data cache queue, which can be adjusted according to storage capacity and latency requirements; Remote update cycle: The cycle for checking and updating policy parameters, which can be adjusted according to operation and maintenance needs; the specific values ​​of the above parameters can be configured according to the actual application scenario and performance requirements, and the protection scope is not limited to any specific value.

[0099] Example 3 This embodiment provides a device for controlling a marine buoy antenna based on multi-source sensing. As the core component of the device for controlling a marine buoy antenna based on multi-source sensing described in Embodiment 2, it consists of a sensing module, a decision module, and an execution module. Specifically, it includes an antenna array, a single transceiver link, a single-pole multi-throw RF switch, an attitude sensor, and a controller, as detailed below: like Figure 8 As shown, the antenna array includes a vertically mounted antenna and multiple tilted antennas. The tilted antennas are spaced apart in the azimuth angle to cover different elevation angle regions. When there are three tilted antennas, they are distributed at azimuth angle intervals of 120°.

[0100] Specific implementation: ①Type: Antenna suitable for satellite communication; ② Vertical antenna: Located in the center, installed vertically, providing omnidirectional coverage; ③ Tilt antenna: pointing at a specific elevation angle, with azimuth angles spaced out, such as... Figure 9 As shown: - First tilt antenna: azimuth angle 0°, designed elevation angle 45°; - Second tilt antenna: azimuth angle 120°, designed elevation angle 45°; - Third tilt antenna: azimuth angle 240°, designed elevation angle 45°.

[0101] ④ Protection level: Adapted to marine environment.

[0102] A single transceiver link, including a power amplifier, a low-noise amplifier, and the transceiver link itself, is shared with each antenna via time-division multiplexing, switching between receive and transmit modes. The transceiver link supports multiple frequency bands and modulation schemes.

[0103] Attitude sensor: used to collect acceleration and attitude angle data of the buoy; the data sampling rate of the attitude sensor is a configurable parameter that can be adjusted according to real-time requirements and power consumption constraints.

[0104] Controller: Used to determine the sea state level based on attitude sensor data, and control the RF switch to switch antennas according to the sea state level and satellite elevation angle; The controller is configured to: when the sea state level reaches or exceeds a preset threshold and the satellite elevation angle is lower than a preset threshold, control the RF switch to connect only the vertical antenna and disable all tilt antennas.

[0105] This device employs a power amplifier temperature protection mechanism and a battery protection mechanism. When the power amplifier temperature is too high, it degrades to using only the vertical antenna and reduces the transmission power. When the battery power is below a preset threshold, it retains only the vertical antenna and reduces the transmission power.

[0106] Example 4 A marine meteorological monitoring buoy system, with the same architecture as the marine buoy antenna control system based on multi-source sensing described in Example 2, is applied to meteorological monitoring buoys in the South China Sea and deployed 50 nautical miles offshore to transmit meteorological data, sea state information and positioning data in real time.

[0107] The system's hardware configuration is as follows: (1) Main control processor: high-performance embedded processor; (2) Positioning module: Supports GPS / BeiDou dual-mode; (3) Attitude sensor: 9-axis IMU, including accelerometer, gyroscope and magnetometer; (4) Communication unit: Supports satellite communication; (5) Power amplifier: Output power adjustable; (6) Radio frequency switch: multi-channel switching; (7) Antenna: Multi-antenna array, such as a combination of one vertical antenna and three tilting antennas; (8) Power supply: lithium battery pack, solar panel, charging management.

[0108] Workflow: 1. Power on and initialize the system, configuring the parameters of each module; 2. Activate the positioning module and attitude sensor to begin data acquisition; 3. Periodically execute the main loop: (1) Read the location and time of the positioning module; (2) Read the attitude sensor data and preprocess it using complementary filtering or Kalman filtering to remove high-frequency noise; (3) Calculate satellite position and orbit prediction; (4) Determine the sea state level; (5) Select the best antenna; (6) Check transmission conditions: If a remote update instruction is received, verify the signature, update the sea state threshold or antenna strategy parameters, and restart configuration loading; execute transmission or cache.

[0109] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to specific implementation methods. Clearly, many modifications and variations can be made based on the content of this specification. The selection and specific description of these embodiments in this specification are intended to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for controlling a marine buoy antenna based on multi-source sensing, characterized in that, Includes the following steps: S1. Collect and process buoy data and satellite orbit parameters; S2. Calculate the current sea state level based on the buoy data; S3. Based on the sea state level and the satellite orbit parameters, determine whether the sea state level reaches or exceeds the preset sea state threshold and the satellite orbit parameters are lower than the preset satellite threshold. If yes, disable all tilt antennas and retain only the vertical antennas, and proceed to step S5; otherwise, proceed to step S4. S4. Calculate the equivalent gain of all available antennas in the buoy, and select the antenna with the highest equivalent gain as the communication antenna. S5. Switch the communication antenna to the transceiver link for communication.

2. The method for controlling a marine buoy antenna based on multi-source sensing according to claim 1, characterized in that, The specific steps of collecting buoy data and satellite orbit data in step S1 are as follows: S11. Collect the buoy's position, acceleration data, and attitude angle data, and calculate the buoy's roll angle, pitch angle, and yaw angle; S12. Based on the satellite orbital parameters and buoy position, the SGP4 orbital prediction model is used to calculate the azimuth and elevation angles of the satellite at future times, generating the satellite trajectory. The inputs of the SGP4 orbital prediction model include the TLE orbital elements and the prediction time, and the output is the position and velocity of the satellite in the geocentric coordinate system.

3. The method for controlling a marine buoy antenna based on multi-source sensing according to claim 2, characterized in that, The specific steps of step S2, which involve calculating the current sea state level based on buoy data, are as follows: S21. Squaring, averaging, and taking the square root of the sampled vertical acceleration values ​​of the buoy to obtain the root mean square of the acceleration; S22. Calculate the deviation between each roll angle sample value and the average value, square it, average it, and take the square root to obtain the standard deviation of the roll angle. S23. Calculate the deviation between each pitch angle sample value and the average value, square it, average it, and take the square root to obtain the standard deviation of the pitch angle; S24. The root mean square value of acceleration, the standard deviation of roll angle, and the standard deviation of pitch angle are compared with preset thresholds to determine the sea state level. Sea conditions are classified from calm to severe according to their degree.

4. The method for controlling a marine buoy antenna based on multi-source sensing according to claim 1, characterized in that, The calculation of the equivalent gain of all available antennas in the buoy in step S4 includes: S41. Transform the antenna mounting direction vector from the body coordinate system to the world coordinate system using the attitude rotation matrix to obtain the antenna world coordinate direction vector; S42. Calculate the dot product of the antenna world coordinate direction vector and the satellite unit direction vector, and take the inverse cosine to obtain the included angle; S43. According to the included angle, look up the antenna pattern lookup table and obtain the ideal gain through linear interpolation; S44. Obtain the weighting factor according to the sea state level, and multiply the ideal gain by the weighting factor to obtain the equivalent gain; Among them, the weighting factor decreases as the sea state level increases.

5. The method for controlling a marine buoy antenna based on multi-source sensing according to claim 4, characterized in that, The attitude transformation matrix is ​​obtained by transforming the roll angle, pitch angle, and yaw angle using Euler angles.

6. The method for controlling a marine buoy antenna based on multi-source sensing according to claim 4, characterized in that, The coordinate system transformation paths in step S41 are as follows: Earth-centered and Earth-fixed coordinate system ECEF, local horizontal coordinate system NED, and buoy body coordinate system.

7. The method for controlling a marine buoy antenna based on multi-source sensing according to claim 4, characterized in that, The antenna pattern lookup table pre-stores the gain values ​​of each antenna at different angles, and obtains the gain at any angle through linear interpolation.

8. The method for controlling a marine buoy antenna based on multi-source sensing according to claim 1, characterized in that, The switching logic for switching antennas in step S5 includes: Priority protection: Ensure that at least one antenna remains connected during handover; Fast switching: The switching setup time is less than a preset threshold; State maintenance: Keep the antenna connection stable during communication.

9. A method for controlling a marine buoy antenna based on multi-source sensing according to claim 1, characterized in that, It also includes safe mode steps: When the collected buoy data or satellite orbit parameters are invalid, enter safe mode; In safe mode, the vertical antenna is forcibly locked and the transmit power is reduced.

10. A method for controlling a marine buoy antenna based on multi-source sensing according to claim 1, characterized in that, It also includes a communication scheduling step, executed before switching communication antennas, including: Check whether it is within the allowed communication time window and whether the battery level is higher than the preset threshold. If the antenna is within the communication time window and the battery level is higher than the preset threshold, execute step S5; otherwise, buffer the data and wait for the next communication window.

11. A marine buoy antenna control system based on multi-source sensing, characterized in that, The method for controlling a marine buoy antenna based on multi-source sensing, as described in claim 1, comprises: Sensing module: includes a positioning module, attitude sensor and ephemeris input interface, used to collect buoy position, attitude and satellite orbit data; Decision module: includes orbit predictor, sea state judgment module, antenna engine and communication scheduler, used to make antenna selection and communication scheduling decisions by integrating multi-source information; Execution module: includes a processor, RF switches, and transceiver links, used to perform antenna switching and data transmission and reception; Intelligent caching module: Used to store data to be sent, manage priority queues, and support data packet lifecycle management; Delayed transmission module: used to calculate the optimal transmission time based on orbit prediction, and delay the data transmission to the next communication window when the conditions are not met; Remote configuration module: used to receive remote configuration commands via satellite communication interface and update strategy parameters such as sea state threshold, elevation angle threshold and battery threshold; The output of the sea state judgment module is directly used as the enable condition input for the antenna selection engine, forming a complete closed-loop decision-making process of perception, decision-making, and execution.

12. A device for controlling a marine buoy antenna based on multi-source sensing, characterized in that, As the core component of the multi-source sensing-based marine buoy antenna control system described in claim 11, it comprises a sensing module, a decision-making module, and an execution module, specifically including: The antenna array includes a vertically mounted antenna and at least one tilted antenna, the tilted antennas being spaced apart in the azimuth angle to cover different elevation angle regions; A single transceiver link, including a power amplifier, a low-noise amplifier, and the transceiver link; A single-pole multi-throw radio frequency switch, the common terminal of which is connected to the single transceiver link, and multiple switching terminals are respectively connected to each antenna in the antenna array; Attitude sensor: used to collect the buoy's acceleration and attitude angle data; Controller: Used to determine the sea state level based on the attitude sensor data, and control the radio frequency switch to switch the antenna according to the sea state level and satellite elevation angle; The controller is configured to: when the sea state level reaches or exceeds a preset threshold and the satellite elevation angle is lower than a preset threshold, control the radio frequency switch to connect only the vertical antenna and disable all tilt antennas.

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