Unmanned aerial vehicle-mounted radar wave measurement method suitable for ship motion forecast

Abstract

The invention relates to an unmanned aerial vehicle-mounted radar wave measurement method suitable for ship motion forecast, and the method achieves the integration of stable wave measurement, data processing and signal transmission in an offshore stormy wave environment through the mutual cooperation of wave signal collection, data processing and wireless transmission. The established method can realize accurate testing of waves and provide accurate input for ship motion forecast, thereby providing a basis for sailors to optimize routes and early warn disasters and ensuring the safety of ships and personnel.

Description

Technical Field

[0001] The present invention relates to the technical field of ship navigation safety and ocean monitoring, and in particular to a drone-borne radar wave measurement method suitable for ship motion prediction. Background Art

[0002] Waves are a significant factor influencing key performance indicators such as ship operational safety, navigation safety, and fuel efficiency. Accurate measurement of wave height, period, and direction is crucial for predicting ship motion. Traditional wave measurement methods, such as buoy wave measurement, shore-based radar wave measurement, and shipborne radar wave measurement, suffer from limitations such as limited observation range, insufficient real-time and continuity, and limited accuracy and reliability. Airborne radar wave measurement combines the flexibility and stability of drones with the wide-range, high-resolution imaging of radar. It offers significant advantages in efficiency, accuracy, and real-time performance, providing input for real-time ship motion forecasts.

[0003] However, when the drone-borne radar wave measurement method is applied to ship motion prediction, it is necessary to ensure high data acquisition accuracy, high-efficiency preprocessing, stable signal transmission, and good compatibility with the ship motion model. According to the investigation and analysis of the technical status of each link, there are still some technologies that need to be studied. For example, the movement posture of the drone itself will affect the radar's wave measurement accuracy; in dynamic and long-distance environments, traditional wireless transmission methods have major disadvantages, mainly manifested in signal attenuation, frequent interruptions, transmission rate that is difficult to meet requirements, and high bit error rate. These problems seriously affect the integrity and accuracy of the wave measurement data, and it is difficult to meet the actual needs of ship navigation safety. Therefore, it is necessary to ensure the reliability of each link of the wave measurement method. Summary of the Invention

[0004] In response to the shortcomings of the above-mentioned existing production technology, the applicant provides a drone-mounted radar wave measurement method suitable for ship motion forecasting, which can conveniently realize the integrated integration of wave stability measurement, data processing, and signal transmission in offshore wind and wave environments.

[0005] The technical solutions adopted in the present invention are as follows:

[0006] A UAV-borne radar wave measurement method suitable for ship motion prediction includes the following process:

[0007] S1. Equipment selection and commissioning:

[0008] S1.1. Drones:

[0009] Use an industrial-grade, long-flight multi-rotor drone with a payload capacity sufficient to carry millimeter-wave radar and related equipment, and a flight time greater than 50 minutes;

[0010] S1.2, millimeter wave radar:

[0011] Select millimeter-wave radars operating in the 30-300 GHz frequency band, which have high resolution and strong anti-interference capabilities;

[0012] S1.3, Data transmission module:

[0013] Adopt 5G communication module to achieve high-speed real-time data transmission;

[0014] S1.4, Data processing terminal:

[0015] Use high-performance portable computers as data processing terminals;

[0016] S2. Measurement area and environmental assessment:

[0017] S2.1. Measurement area:

[0018] Using geographic information system software, the scope of the survey area is determined according to the ship's navigation route, and the survey area is divided into multiple grids. The size of each grid is determined according to the measurement accuracy requirements;

[0019] S2.2 Environmental Assessment:

[0020] Before measurement, obtain weather and sea condition information of the measurement area, including wind speed, wind direction, wave height, and tide, through channels such as weather forecasts and marine environmental monitoring data;

[0021] S3. Takeoff and cruise:

[0022] S3.1 Takeoff:

[0023] Take off the drone in an open, flat area away from obstacles. Start the drone according to the drone operating procedures and perform a pre-takeoff self-check. After the self-check is complete, send the takeoff command through the ground station software. The drone will take off vertically to the initial cruising altitude, which can be set to 50-100 meters according to the wave measurement requirements.

[0024] S3.2 Cruise flight:

[0025] The drone flies at a set cruising speed according to a predetermined route;

[0026] S4. Data collection:

[0027] S4.1. Millimeter-wave radar data acquisition:

[0028] The millimeter-wave radar continuously transmits millimeter-wave signals to the sea surface at a set frequency and receives the signals reflected back from the sea surface;

[0029] S4.2. Auxiliary data collection:

[0030] Utilize the drone’s built-in GPS system and inertial measurement unit to collect the drone’s position and attitude information in real time;

[0031] S5. Data processing:

[0032] S5.1. Data cleaning:

[0033] Clean the received data to remove outliers and noise data caused by electromagnetic interference, drone vibration, etc., and use the Kalman filter algorithm to smooth the original data to improve data quality;

[0034] S5.2, Data Alignment:

[0035] Since there are slight differences in the acquisition time of millimeter-wave radar data and drone position and attitude data, these data need to be time-aligned. Based on the timestamp information of the data acquisition, linear interpolation and other methods are used to unify the data from different data sources to the same time scale.

[0036] S5.3. Wave information reconstruction:

[0037] First, the wave height is calculated using geometric relationships based on the distance between the radar and the sea surface measured by the millimeter-wave radar, combined with the drone's attitude data. Second, a fast Fourier transform is performed on the preprocessed millimeter-wave radar echo signal to convert the time domain signal into a frequency domain signal. By analyzing the peak position of the frequency domain signal, the main frequency components of the wave are determined, and the wave period is calculated. Furthermore, the wave information obtained from the millimeter-wave radar measurement is used to calculate the wave propagation direction using phase difference and cross-correlation methods.

[0038] S6. Wireless data transmission:

[0039] S6.1. Real-time transmission:

[0040] The data collected by the millimeter-wave radar, as well as the drone’s position, attitude, and processed wave reconstruction data, are transmitted in real time to the ship’s data processing terminal via the 5G data transmission module.

[0041] S6.2, Transmission Monitoring:

[0042] At the data processing terminal, the data transmission status is monitored in real time, including data transmission rate and packet loss rate. If any transmission abnormality is found, the 5G module, communication line, and network signal are checked in time, and corresponding solutions are taken.

[0043] Its further technical solution is:

[0044] In S1.1, before using the drone, the flight control system, power system, and communication system of the drone should be fully inspected to ensure that all components are operating normally.

[0045] In S1.2, when installing the millimeter-wave radar, use a bracket to firmly install the millimeter-wave radar at the center of the bottom of the drone, ensuring that the initial radar beam points vertically downward toward the sea surface.

[0046] The installation structure of the millimeter-wave radar is as follows: it includes a fixed bracket fixed to the drone by fasteners, a swing bracket hinged at one end of the fixed bracket, a screw rod installed between the swing bracket and the fixed bracket, the swing bracket has a thread matching the screw rod, and a nut for fixing is installed at the bottom of the swing bracket, a servo electric cylinder for driving the screw rod to rotate is installed on the top surface of the fixed bracket, and the millimeter-wave radar is installed at the bottom of the swing bracket.

[0047] The swing bracket can be adjusted from 10° to 90°.

[0048] After the millimeter-wave radar is installed, it is calibrated. Standard reflectors are used to simulate reflective targets at different distances and angles, and the radar parameters are adjusted so that its measurement accuracy meets the design requirements.

[0049] In S1.3, the 5G module is connected and debugged with the millimeter-wave radar and data processing terminal respectively to ensure the stability and reliability of data transmission.

[0050] The beneficial effects of the present invention are as follows:

[0051] The present invention boasts a compact, rational structure and easy operation. By integrating wave signal acquisition, data processing, and wireless transmission, it achieves integrated wave measurement, data processing, and signal transmission in windy and choppy conditions at sea. The developed method enables accurate wave measurement, providing precise input for ship motion forecasts, thereby providing a basis for optimizing routes, providing disaster warnings, and ensuring the safety of ships and personnel.

[0052] This invention focuses on the input requirements of ship motion forecasts for wave environments, and carries out real-time wave data collection, processing, and wireless transmission using drone-mounted radar sensors, providing ships with high-precision, low-latency real-sea wave environment information to improve the real-time and accuracy of ship motion forecasts.

[0053] The present invention uses drones equipped with radar equipment to accurately obtain ocean wave data, provide reliable environmental input for ship motion forecasts, and improve the safety and stability of ship navigation.

[0054] The present invention can not only be used for ship motion forecasting, but also provide high-precision wave data for fields such as marine scientific research and marine environmental monitoring, which helps to gain a deeper understanding of ocean dynamics and enhance the ability in ocean monitoring and utilization. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 This is a schematic diagram of the structure of the millimeter-wave radar mounted on the UAV of the present invention.

[0056] Figure 2 This is a structural diagram of the millimeter-wave radar mounted on a UAV of the present invention from another perspective.

[0057] Figure 3 Schematic diagram of the drone-mounted radar wave measurement and wireless signal transmission method of the present invention.

[0058] Figure 4 This is the wave signal collection and processing process of the drone-borne radar of the present invention.

[0059] Figure 5 This is the wireless transmission process of the UAV-borne radar wave signal of the present invention.

[0060] Among them: 1. UAV; 2. Servo electric cylinder; 3. Fixed bracket; 4. Screw; 5. Nut; 6. Swing bracket; 7. Millimeter wave radar. DETAILED DESCRIPTION

[0061] The specific embodiments of the present invention will be described below with reference to the accompanying drawings.

[0062] like Figure 1-Figure 5 As shown, the UAV-borne radar wave measurement method applicable to ship motion prediction in this embodiment includes the following methods:

[0063] (1) Wave signal collection method:

[0064] The core hardware components were selected from a drone platform featuring high stability, long endurance, and a large payload capacity, along with a compact, high-precision, and highly anti-interference millimeter-wave radar. The millimeter-wave radar was securely mounted on a shock-absorbing bracket at the bottom of the drone to minimize interference from the drone's flight attitude on radar measurements, ensuring stable radar operation. A "servo-screw" system was used to drive the radar's measurement and echo angles, enabling radar coverage across multiple sea areas.

[0065] Based on the measurement accuracy and range requirements of wave signals in ship motion forecasts, the millimeter-wave radar's operating frequency, resolution and other parameters are carefully set to accurately identify wave details and ensure that the measurement distance and range requirements are met. Based on the wave characteristics under common sea conditions for ship navigation, the radar's signal receiving bandwidth is optimized to enhance the ability to collect wave signals of specific frequencies.

[0066] At the same time, it is equipped with a high-precision GPS module to accurately obtain the radar's position information in real time. It is paired with an inertial measurement unit (IMU) to accurately measure the drone's attitude data and accurately synchronize and store it with the radar echo data, providing accurate time and space reference input for subsequent data processing and motion compensation algorithms.

[0067] (2) Data processing methods:

[0068] First, the collected raw radar echo data is preprocessed, and an adaptive filtering algorithm is used to accurately remove noise interference in the signal, significantly improving the signal-to-noise ratio of the data. At the same time, based on the position and attitude information provided by GPS and IMU, the echo data is accurately converted into coordinates and corrected for attitude, and the radar measurement data is uniformly mapped to the geodetic coordinate system to eliminate the interference of drone attitude changes on the measurement results.

[0069] Furthermore, advanced signal processing methods such as Fourier transform are used to perform fine spectral analysis on the pre-processed radar echo data, accurately extract the frequency information of the waves, and combine with professional wave theory models to accurately calculate key parameters such as wave height, period and wave direction through optimized reconstruction algorithms.

[0070] Finally, the reconstructed wave parameters undergo a rigorous quality assessment. By setting scientific and reasonable thresholds and error ranges, anomalous data is accurately removed, further improving the accuracy and reliability of the measurement results. For ship motion prediction applications, the processed wave data undergoes format conversion and parameter matching according to the input requirements of the ship motion model, enabling the wave measurement data to be accurately integrated into the ship motion prediction model, thereby improving the accuracy of the forecast.

[0071] (3) Wireless transmission method:

[0072] A stable wireless communication link is built between the UAV and the ship control station. A wireless communication module with high bandwidth and low latency based on 5G communication is selected to establish a high-precision transmission mechanism for ship motion forecast data to ensure the accurate transmission of key wave signals and ship motion prediction data.

[0073] To significantly reduce data transmission volume and significantly improve transmission efficiency, a wavelet compression algorithm is used to deeply compress the processed wave parameters used for ship motion forecasting, converting the data into a more compact format and reducing the space required for data storage and transmission. Convolutional coding technology is also used to encode the compressed data, improving its anti-interference ability during transmission and ensuring accurate data transmission to the ship's control station.

[0074] After receiving the data, the ship control station quickly decodes and decompresses it, and connects the data to a specially constructed ship motion prediction model adapter interface, so that it can display the wave measurement results and ship motion prediction results in real time and intuitively, providing timely and accurate information to ship drivers, maritime management departments and other relevant personnel to ensure the safety of ship navigation.

[0075] The UAV-mounted radar wave measurement method applicable to ship motion prediction in this embodiment specifically includes the following detailed process:

[0076] S1. Equipment selection and commissioning:

[0077] S1.1. Drones:

[0078] Choose an industrial-grade, long-flight multi-rotor drone with a flight time of more than 50 minutes, such as the DJI Matrice 350RTK. Its payload capacity must meet the requirements for carrying millimeter-wave radar and related equipment, and its flight time must be 55 minutes. Before use, thoroughly inspect the drone's flight control system, power system, and communication system to ensure proper operation. Use the ground station software to set the drone's flight parameters, including speed, altitude limit, and return-to-home altitude.

[0079] S1.2, millimeter wave radar:

[0080] Select a millimeter-wave radar with an operating frequency in the 30-300GHz frequency band, such as the Texas Instruments AWR2243, which uses cascade technology and multiple-input multiple-output (MIMO) technology. The operating frequency is set to 76-81Hz, the azimuth angle resolution is 1.2° (3dB bandwidth), and the pitch angle resolution is 18° (3dB bandwidth). It has high resolution and strong anti-interference ability, and can be configured as needed according to the test conditions during the test. During installation, use a special shock-proof bracket to firmly install the millimeter-wave radar at the center of the bottom of the drone to ensure that the initial radar beam is vertically downward pointing to the sea surface. The radar can be driven by the "servo-screw" system to achieve an adjustable measurement / echo angle of 10° to 90° ( Figure 1 After installation, the millimeter-wave radar is calibrated, and standard reflectors are used to simulate reflective targets at different distances and angles. The radar parameters are further adjusted to ensure that the measurement accuracy meets the design requirements.

[0081] Specifically, the installation structure of the millimeter-wave radar 7 is as follows: it includes a fixed bracket 3 fixed to the drone by fasteners, one end of the fixed bracket 3 is hingedly connected to a swing bracket 6, a screw rod 4 is installed between the swing bracket 6 and the fixed bracket 3, the swing bracket 6 is provided with a thread matching the screw rod 4, and a nut 5 for fixing is installed at the bottom of the swing bracket 6, a steering gear electric cylinder 2 for driving the screw rod 4 to rotate is installed on the top surface of the fixed bracket 3, and a millimeter-wave radar 7 is installed at the bottom of the swing bracket 6.

[0082] S1.3 Data Transmission Module: Use a 5G communication module to achieve high-speed, real-time data transmission. Connect and debug the 5G module to the millimeter-wave radar and data processing terminal separately to ensure stable and reliable data transmission. Set the data transmission protocol to a custom binary protocol based on TCP / UDP. Specify the data packet format as a binary stream, the transmission rate based on a typical 5G network configuration, and the checksum as CRC32 with a sequence number retransmission mechanism.

[0083] S1.4. Data Processing Terminal: Use a high-performance portable computer as the data processing terminal and install specially developed data processing software. Perform functional testing on the software to ensure it can correctly receive, store, and process data transmitted by the millimeter-wave radar. The computer's hardware performance must meet the requirements for large data processing.

[0084] S2. Measurement area and environmental assessment:

[0085] S2.1. Survey Area: Use Geographic Information System (GIS) software to determine the survey area based on the vessel's route. Divide the survey area into multiple grids, with each grid size determined based on the required measurement accuracy, for example, 500 meters by 500 meters. Plan the drone's flight path, using a round-trip or spiral flight pattern to ensure coverage of each grid. Allow 10-20% overlap between adjacent routes.

[0086] S2.2 Environmental Assessment: Before measurement, obtain weather and sea condition information for the measurement area, including wind speed, wind direction, wave height, and tides, through weather forecasts and marine environmental monitoring data. If wind speeds exceed the drone's safe flight limit (for example, the DJI Matrice 350RTK's maximum wind resistance is 12 m / s), postpone the measurement mission to ensure drone flight safety and measurement data quality.

[0087] S3. Takeoff and cruise:

[0088] S3.1 Takeoff:

[0089] Take off the drone in an open, flat area away from obstacles. Follow the drone's operating procedures, start the drone, and perform a pre-takeoff self-check. After the self-check is complete, send the takeoff command via the ground station software. The drone will take off vertically to its initial cruising altitude, set between 50 and 100 meters based on wave measurement requirements.

[0090] S3.2 Cruise flight:

[0091] The drone flies along a predetermined route at a set cruising speed. During flight, the drone's flight status, including position, attitude, battery level, and communication signal strength, is monitored in real time. If an abnormality occurs, such as signal loss or low battery, the drone will follow pre-set emergency procedures and perform the appropriate emergency actions, which can be set to automatically return home or hover and wait.

[0092] S4. Data collection:

[0093] S4.1. Millimeter-wave radar data acquisition:

[0094] The millimeter-wave radar continuously transmits millimeter-wave signals to the sea surface at a set frequency (e.g., 70 Hz) and receives the signals reflected from the sea surface. During the acquisition process, the radar's operating parameters, including transmit power, receive gain, and pulse repetition frequency, are simultaneously recorded.

[0095] S4.2. Auxiliary data collection:

[0096] The drone's built-in GPS system and inertial measurement unit (IMU) collect real-time information about the drone's position (longitude, latitude, altitude) and attitude (pitch, roll, and yaw). This information is used to calibrate millimeter-wave radar measurement data and reconstruct ocean wave parameters.

[0097] S5. Data processing:

[0098] S5.1. Data cleaning:

[0099] The received data is cleaned to remove outliers and noise data caused by electromagnetic interference, drone vibration, etc. The Kalman filter algorithm is used to smooth the raw data to improve data quality.

[0100] S5.2, Data Alignment:

[0101] Because the millimeter-wave radar data and the drone's position and attitude data are collected at slightly different times, these data need to be time-aligned. Using methods such as linear interpolation based on the timestamp information, the data from different sources are aligned to the same time scale.

[0102] S5.3. Wave information reconstruction:

[0103] First, based on the distance information between the millimeter-wave radar and the sea surface measured by the radar and the drone's attitude data, the wave height is calculated using geometric relationships. Specifically, by measuring the distance difference between the radar and the sea surface at different times, considering the influence of the drone's pitch and roll angles on the distance measurement, the wave height is obtained using the least squares fitting method. Secondly, a fast Fourier transform (FFT) is performed on the preprocessed millimeter-wave radar echo signal to convert the time domain signal into a frequency domain signal. By analyzing the peak position in the frequency domain signal, the main frequency components of the wave are determined, and the wave period of the wave is calculated. Simultaneously, using the wave information measured by the millimeter-wave radar, the wave propagation direction is calculated using the phase difference method and cross-correlation method.

[0104] S6. Wireless data transmission:

[0105] S6.1. Real-time transmission:

[0106] Data collected by the millimeter-wave radar, along with the drone's position and attitude, and processed wave reconstruction data, are transmitted in real time to the ship's data processing terminal via a 5G data transmission module. During transmission, the data is encrypted to prevent theft or tampering.

[0107] S6.2, Transmission Monitoring:

[0108] At the data processing terminal, real-time monitoring of data transmission status, including data transmission rate, packet loss rate, etc. If any transmission anomalies are found, timely inspection of the 5G module, communication lines, and network signals will be carried out, and appropriate remedial measures will be taken.

[0109] The above description is an explanation of the present invention, not a limitation of the present invention. The scope of the present invention is defined in the claims. Any modifications may be made within the scope of protection of the present invention.

Claims

1. A drone-borne radar wave measurement method suitable for ship motion forecasting, characterized by: The process includes the following: S1. Equipment selection and commissioning: S1.

1. Drones: Use an industrial-grade long-flight multi-rotor drone with a payload capacity sufficient to carry millimeter-wave radar and related equipment, and a flight time of at least 1 hour; S1.2, millimeter wave radar: Select millimeter-wave radars operating in the 30-300 GHz frequency band, which have high resolution and strong anti-interference capabilities; S1.3, Data transmission module: Adopt 5G communication module to achieve high-speed real-time data transmission; S1.4, Data processing terminal: Use high-performance portable computers as data processing terminals; S2. Measurement area and environmental assessment: S2.

1. Measurement area: Using geographic information system software, the scope of the survey area is determined according to the ship's navigation route, and the survey area is divided into multiple grids. The size of each grid is determined according to the measurement accuracy requirements; S2.2 Environmental Assessment: Before measurement, obtain weather and sea condition information of the measurement area, including wind speed, wind direction, wave height, and tide, through channels such as weather forecasts and marine environmental monitoring data; S3. Takeoff and cruise: S3.1 Takeoff: Take off the drone in an open, flat area away from obstacles. Start the drone according to the drone operating procedures and perform a pre-takeoff self-check. After the self-check is complete, send the takeoff command through the ground station software. The drone will take off vertically to the initial cruising altitude, which can be set to 50-100 meters according to the wave measurement requirements. S3.2 Cruise flight: The drone flies at a set cruising speed according to a predetermined route; S4. Data collection: S4.

1. Millimeter-wave radar data acquisition: The millimeter-wave radar continuously transmits millimeter-wave signals to the sea surface at a set frequency and receives the signals reflected back from the sea surface; S4.

2. Auxiliary data collection: Utilize the drone’s built-in GPS system and inertial measurement unit to collect the drone’s position and attitude information in real time; S5. Data processing: S5.

1. Data cleaning: Clean the received data to remove outliers and noise data caused by electromagnetic interference, drone vibration, etc., and use the Kalman filter algorithm to smooth the original data to improve data quality; S5.2, Data Alignment: Since there are slight differences in the acquisition time of millimeter-wave radar data and drone position and attitude data, these data need to be time-aligned. Based on the timestamp information of the data acquisition, linear interpolation and other methods are used to unify the data from different data sources to the same time scale. S5.

3. Wave information reconstruction: First, the wave height is calculated using geometric relationships based on the distance between the radar and the sea surface measured by the millimeter-wave radar, combined with the drone's attitude data. Second, a fast Fourier transform is performed on the preprocessed millimeter-wave radar echo signal to convert the time domain signal into a frequency domain signal. By analyzing the peak position of the frequency domain signal, the main frequency components of the wave are determined, and the wave period is calculated. Furthermore, the wave information obtained from the millimeter-wave radar measurement is used to calculate the wave propagation direction using phase difference and cross-correlation methods. S6. Wireless data transmission: S6.

1. Real-time transmission: The data collected by the millimeter-wave radar, as well as the drone’s position, attitude, and processed wave reconstruction data, are transmitted in real time to the ship’s data processing terminal via the 5G data transmission module. S6.2, Transmission Monitoring: At the data processing terminal, real-time monitoring of data transmission status, including data transmission rate and packet loss rate; If any transmission abnormality is found, check the 5G module, communication lines, network signals, etc. in a timely manner and take appropriate solutions.

2. The UAV-mounted radar wave measurement method for ship motion prediction according to claim 1, characterized in that: In S1.1, before using the drone, the flight control system, power system, and communication system of the drone should be fully inspected to ensure that all components are operating normally.

3. The UAV-mounted radar wave measurement method for ship motion prediction according to claim 1, characterized in that: In S1.2, when installing the millimeter-wave radar, use a bracket to firmly install the millimeter-wave radar at the center of the bottom of the drone, ensuring that the initial radar beam points vertically downward toward the sea surface.

4. The UAV-mounted radar wave measurement method for ship motion prediction according to claim 3, characterized in that: The installation structure of the millimeter wave radar comprises: a fixed bracket (3) fixed to the unmanned aerial vehicle through a fastener, a swing bracket (6) hinged at one end of the fixed bracket (3), a screw rod (4) installed between the swing bracket (6) and the fixed bracket (3), a thread matching the screw rod (4) is opened on the swing bracket (6), and a nut (5) for fixing is installed at the bottom of the swing bracket (6), a steering gear electric cylinder (2) for driving the screw rod (4) to rotate is installed on the top surface of the fixed bracket (3), and a millimeter wave radar (7) is installed at the bottom of the swing bracket (6).

5. The UAV-borne radar wave measurement method for ship motion prediction according to claim 4, characterized in that: The swing bracket (6) can be adjusted from 10° to 90°.

6. The UAV-borne radar wave measurement method for ship motion prediction according to claim 5, characterized in that: After the millimeter wave radar (7) is installed, the millimeter wave radar (7) is calibrated, and a standard reflector is used to simulate reflective targets at different distances and angles, and the radar parameters are adjusted so that its measurement accuracy meets the design requirements.

7. The UAV-borne radar wave measurement method for ship motion prediction according to claim 1, characterized in that: In S1.3, the 5G module is connected and debugged with the millimeter-wave radar and data processing terminal respectively to ensure the stability and reliability of data transmission.

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