Unmanned ship marine millimeter wave cloud radar and background field data maneuvering fusion method and device and medium

Abstract

The invention discloses an unmanned ship maritime millimeter wave cloud radar and background field data maneuvering fusion method and device and a medium, and relates to the technical field of meteorological detection. The method comprises the following steps: acquiring a navigation route and radar detection parameters of the unmanned ship; based on the navigation route of the unmanned ship and the radar detection parameters, the unmanned ship is controlled to navigate autonomously according to the set route; wherein a millimeter wave cloud radar system is carried on the unmanned ship; obtaining millimeter wave cloud radar data of the unmanned ship in the sailing process; wherein the millimeter wave cloud radar data are acquired by a millimeter wave cloud radar system based on radar detection parameters; performing cloud cover inversion on the millimeter wave cloud radar data based on a reflectivity and cloud cover formula to obtain cloud cover data in a navigation route process; and interpolating the cloud cover data into the three-dimensional cloud cover data of the background field data to obtain fusion data. According to the invention, accurate fusion of the radar data and the background field data can be realized, so that more comprehensive and more accurate cloud layer information can be obtained.

Description

Technical Field

[0001] The present invention relates to the field of meteorological detection technology, and more specifically, to a method, device and medium for maneuvering fusion of unmanned boat marine millimeter wave cloud radar and background field data. Background Art

[0002] At present, satellites and millimeter-wave cloud radars are commonly used to observe cloud amount, cloud shape, cloud height, etc.

[0003] Satellite Observation Technology:

[0004] Cloud cover observation: Satellites capture images of the surface and atmosphere using multispectral or high-resolution cameras. These images can show the distribution and coverage of clouds. By analyzing the pixels in the image, it is possible to determine which areas are covered by clouds and thus calculate the cloud cover. This is usually done by comparing the reflectivity or brightness of clouds to surrounding cloud-free areas.

[0005] Cloud height observation: Satellites use active or passive sensors such as Lidar or microwave radiometers to measure the height of clouds. Lidar determines the height of clouds by emitting laser pulses into the clouds and measuring the return time, while microwave radiometers estimate their height by analyzing the microwave radiation emitted by clouds. Lidar uses the speed of light and time difference to calculate the height of clouds. Microwave radiometers estimate the height of clouds based on the relationship between the intensity and frequency of microwave radiation from clouds and parameters such as temperature, humidity and height.

[0006] Cloud shape observation: mainly relies on high-resolution visible and infrared remote sensing images. These images can capture the details and textures of clouds, thus helping researchers identify different cloud shapes. (a) Cirrus: Cirrus clouds usually appear as slender filamentary structures with high albedo (i.e., the ability to reflect sunlight). On visible light images, they usually appear white or bright gray. Cirrus clouds are usually located high in the sky and have little impact on the weather, but can serve as an indicator of other weather systems. (b) Cumulus: Cumulus clouds are common low clouds that appear as fluffy, mass-like structures. On visible light images, they usually appear white or gray. Cumulus clouds are usually associated with clear weather, but sometimes they may develop into cumulonimbus clouds. (c) Stratus: Stratus clouds are evenly distributed low clouds that usually cover the entire sky. On visible light images, they appear gray or light white. Stratus clouds are usually associated with stable weather conditions and may bring continuous precipitation. (d) Cumulonimbus: Cumulonimbus is a tall cloud that is usually accompanied by heavy precipitation, thunderstorms and lightning. Cumulonimbus appears as thick white or gray clouds on visible light images. Cumulonimbus clouds usually have complex structures, including towering cloud towers and rain streamers at the bottom.

[0007] Millimeter wave cloud radar observation technology:

[0008] Millimeter-wave cloud radar is an active microwave atmospheric remote sensing device that uses the backscattered echoes generated by the interaction between electromagnetic waves in the millimeter-wave frequency band (35GHz, 75GHz) and particles such as clouds, rain, and fog in the atmosphere to detect atmospheric meteorological information. Millimeter-wave cloud radar has the following characteristics and advantages in observing cloud amount, cloud height, and cloud shape:

[0009] Cloud cover observation: Millimeter wave cloud radar can detect the backscatter echo of clouds. By analyzing the intensity and time series changes of the echo, the coverage and cloud cover of the cloud layer can be determined. This observation method is not limited by day and night and can be carried out all day long.

[0010] Cloud height observation: Millimeter wave cloud radar estimates the height of clouds by measuring the time delay of echoes. Since the propagation speed of millimeter waves in the atmosphere is close to the speed of light, the height information of clouds can be obtained by accurately measuring the time delay.

[0011] Cloud shape observation: Millimeter wave cloud radar can infer the shape and structure of clouds by analyzing the intensity, shape and vertical structure of echoes. For example, by analyzing the echo intensity and vertical structure, different types of clouds such as cirrus, cumulus and stratus can be distinguished.

[0012] Problems with existing technologies:

[0013] (1) Using satellite cloud images to observe clouds can obtain comprehensive information on cloud amount, cloud shape, and cloud height. However, since this method is a bird's-eye view from the sky, it is only suitable for observing high clouds and is not conducive to observing medium and low clouds. In addition, since the temporal resolution (hours) and spatial resolution (1-4 kilometers) of satellite observation data are relatively low, smaller clouds are often missed.

[0014] (2) Millimeter-wave cloud radar emits electromagnetic waves with a wavelength of 3 mm from bottom to top, with a data update rate of 1 minute and a distance resolution of 30 meters. It can quickly and accurately measure the cloud base height and cloud top height of medium and low clouds; it can then be mounted on an unmanned boat and achieve fixed-point observation of smaller clouds through maneuvering. However, because millimeter-wave cloud radar obtains radial echoes one by one, it cannot cover the entire sky and cannot obtain comprehensive information on cloud amount and cloud shape. Summary of the invention

[0015] In order to solve the above technical problems, the present invention provides a method, device and medium for the mobile fusion of unmanned boat marine millimeter-wave cloud radar and background field data, combining the high temporal and spatial resolution PPI scanning data of the millimeter-wave cloud radar and the global background field analysis data (GFS data, ERA5 data, etc.), and fusing the two types of data to obtain more detailed and comprehensive cloud information.

[0016] In a first aspect, the present invention provides a method for maneuvering fusion of unmanned boat marine millimeter wave cloud radar and background field data, the method comprising:

[0017] Obtain the navigation route and radar detection parameters of the unmanned boat;

[0018] Convert the radar coordinate system based on the unmanned boat into the geodetic coordinate system;

[0019] The unmanned boat is equipped with a millimeter-wave cloud radar system and a fusion cloud data of the last time and a millimeter-wave cloud radar data of the current geodetic coordinate system are used to set a navigation route for the unmanned boat to conduct autonomous navigation.

[0020] Acquire millimeter-wave cloud radar data of the unmanned boat during navigation, such as reflectivity factor, speed, spectrum width, etc.; wherein the millimeter-wave cloud radar data is collected by the millimeter-wave cloud radar system based on the radar detection parameters;

[0021] Based on the reflectivity factor and cloud cover formula, the cloud cover data of millimeter wave cloud radar is inverted to obtain the cloud cover data during the navigation route;

[0022] The cloud amount data is interpolated into the three-dimensional cloud amount data of the background field data to obtain fused data.

[0023] Furthermore, the wavelength of the millimeter wave cloud radar system is 3 mm.

[0024] Furthermore, the information includes cloud cover, cloud base height and cloud top height.

[0025] Furthermore, in the feature fusion sharing layer, the cloud cover data is interpolated into the three-dimensional cloud cover data of the background field data by the following formula to obtain fused data:

[0026]

[0027] In the formula, w g Represents the weight coefficient of the radar data sampling point;

[0028] R O ,θ O ,Φ o represents the spherical coordinates of the interpolated radar data point P, which are the radial distance, azimuth and elevation of the data point;

[0029] R g ,θ g ,Φ g represents the spherical coordinates of the original radar data points, where g = 1, 2, ..., N;

[0030] 2 represents the smoothing parameter;

[0031] f g Represents the reflectivity value of the original radar data point;

[0032] f o Represents the reflectivity value of the interpolated data point;

[0033] N stands for R g ,θ g ,Φ g The reflectivity value affects the number of distance bins in the area.

[0034] Furthermore, the background field data include EC reanalysis data or GFS global forecast field data.

[0035] Furthermore, after interpolating the cloud amount data into the three-dimensional cloud amount data of the background field data to obtain fused data, the method further includes:

[0036] Based on the fused data, secondary meteorological products such as cloud amount, cloud base height, cloud top height, and cloud shape are generated.

[0037] In a second aspect, the present invention provides a device for maneuvering fusion of millimeter-wave cloud radar and background field data of an unmanned boat at sea, the device comprising:

[0038] The unmanned boat navigation attitude and route parameter acquisition unit is configured to obtain the navigation route and radar detection parameters of the unmanned boat;

[0039] The unmanned boat control unit is configured to convert the radar coordinate system based on the unmanned boat into the geodetic coordinate system; comprehensively integrate the fused cloud data of the previous time and the millimeter wave cloud radar data of the current geodetic coordinate system to set the navigation route of the unmanned boat for autonomous navigation; wherein the unmanned boat is equipped with a millimeter wave cloud radar system;

[0040] A millimeter wave cloud radar parameter data acquisition unit is configured to acquire millimeter wave cloud radar data of the unmanned boat during navigation; wherein the millimeter wave cloud radar data is acquired by the millimeter wave cloud radar system based on the radar detection parameters;

[0041] A cloud parameter inversion unit is configured to perform cloud inversion on millimeter wave cloud radar data based on a reflectivity and cloud amount formula to obtain cloud amount data during the navigation route;

[0042] The millimeter wave cloud radar and background field data fusion unit is configured to interpolate the cloud amount data into the three-dimensional cloud amount data of the background field data to obtain fused data.

[0043] Furthermore, the millimeter wave cloud radar and background field data fusion unit is further configured as follows:

[0044]

[0045] In the formula, w g Represents the weight coefficient of the radar data sampling point;

[0046] R O ,θ O ,Φ o represents the spherical coordinates of the interpolated radar data point P, which are the radial distance, azimuth and elevation of the data point;

[0047] R g ,θ g ,Φ g represents the spherical coordinates of the original radar data points, where g = 1, 2, ..., N;

[0048] 2 represents the smoothing parameter;

[0049] f g Represents the reflectivity value of the original radar data point;

[0050] f o Represents the reflectivity value of the interpolated data point;

[0051] N stands for R g ,θ g ,Φ g The reflectivity value affects the number of distance bins in the area.

[0052] In a third aspect, the present invention provides a readable storage medium, wherein the readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the method as described above.

[0053] The present invention has at least the following beneficial effects:

[0054] The present invention has broad application prospects and market demand, and can provide important support for the fields of meteorology, marine environment, etc.; specifically, it can be widely used in meteorological observation, marine environmental research, ship navigation safety and other fields. With the rapid development of global climate change and marine economy, the demand for marine meteorological and environmental information will continue to grow. Therefore, the present invention has broad market prospects and huge commercial value. At the same time, the technology can also provide decision-making support for relevant departments and help the rational development and utilization of marine resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A flow chart of a method for maneuvering fusion of unmanned boat marine millimeter-wave cloud radar and background field data according to an embodiment of the present invention is shown.

[0056] Figure 2A schematic diagram showing the principle of interpolating cloud cover data into three-dimensional cloud cover data of background field data according to an embodiment of the present invention is shown.

[0057] Figure 3 A structural diagram of a mobile fusion device for unmanned boat marine millimeter-wave cloud radar and background field data according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0058] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and specific embodiments, but are not intended to limit the present invention. For the various steps described herein, if there is no necessity for a causal relationship between each other, the order in which they are described as examples herein should not be regarded as a limitation, and those skilled in the art should know that they can be adjusted in order, as long as the logic between them is not destroyed, resulting in the inability to implement the entire process.

[0059] With the continuous development of meteorology and ocean science, cloud monitoring and data analysis are becoming more and more important. As a high-precision, high-resolution detection device, millimeter-wave cloud radar has broad application prospects in the field of cloud detection and meteorological analysis. However, due to the complexity of the cloud environment and the diversity of radar data, how to accurately integrate radar data with background field data to obtain more comprehensive and accurate cloud information is a key issue facing current technology.

[0060] In order to achieve accurate fusion of radar data and background field data, thereby obtaining more comprehensive and accurate cloud information, an embodiment of the present invention provides a method for maneuvering fusion of unmanned boat marine millimeter wave cloud radar and background field data, such as Figure 1 As shown, the method includes steps S10 to S50, which are described in detail as follows.

[0061] S10. Obtaining navigation parameters and radar detection parameters of the unmanned boat.

[0062] In this embodiment, the unmanned boat determines the location of the clouds that need to be paid attention to based on the global background field data and the detection parameters of the boat-borne millimeter-wave cloud radar, sets the navigation route, and generates the navigation parameters of the unmanned boat such as speed, roll angle, pitch angle, heading angle, current longitude, and current latitude.

[0063] (1) Identify the clouds that require attention

[0064] Different types of clouds have different precipitation intensities and properties due to their different cloud heights, cloud thicknesses, and temperatures in the clouds. For example, cumulonimbus clouds are mixed clouds with ice and water. The thickness of the clouds and the water content in the clouds are very large, and the updrafts and downdrafts in the clouds are strong, so they can produce heavy showers, snow showers, and sometimes hail. Stratus clouds can only produce drizzle, while stratocumulus clouds can produce light rain, snow, and hail.

[0065] Higher clouds are usually associated with more intense convective activity and can result in heavier precipitation. For example, convective clouds (such as cumulonimbus clouds) usually form at higher altitudes and are associated with strong convective activity, which can result in heavy precipitation. Lower clouds (such as stratus and stratocumulus clouds) can result in light to moderate precipitation.

[0066] When cloud cover increases, the number of cloud droplets or ice crystals also increases, increasing the likelihood of precipitation. Conversely, when cloud cover decreases, the likelihood of precipitation also decreases.

[0067] Therefore, this method needs to focus on higher and thicker cumulonimbus or cumulus clouds.

[0068] (2) Detection parameters of millimeter-wave cloud radar

[0069] a. Millimeter wave radar reflectivity factor

[0070] In the cloud and precipitation process, particles often do not satisfy the Rayleigh approximation. The millimeter-wave radar reflectivity η is written as follows:

[0071]

[0072] The definition of Ze is the equivalent radar reflectivity factor. The radar reflectivity factor Z is a characteristic of the cloud and precipitation particle spectrum distribution and has nothing to do with the radar wavelength. The equivalent reflectivity factor involves the scattering characteristics of clouds and precipitation particles. When electromagnetic waves of different frequency bands encounter clouds and precipitation particles, they may not meet the Rayleigh scattering conditions, and the measured equivalent reflectivity factors will have certain differences.

[0073] According to the meteorological radar equation, the radar equivalent reflectivity factor Ze can be expressed as follows:

[0074] Z e =CR 2 P r

[0075] Where R represents the distance between the antenna and the target (in meters), C is the radar constant calculated using radar parameters, and Pr is the power value returned by the target reflectivity received by the antenna.

[0076] b. Millimeter-wave radar radial velocity and spectral width

[0077] The meteorological echo signal is s(t), then the correlation function R(T) of the successive pulse echo signals in the same effective irradiation volume is:

[0078]

[0079] Where T is the time interval between successive pulses.

[0080] Since the correlation function and the power spectrum density of the signal are Fourier transforms of each other, the power spectrum density function S(f) of the echo signal can be obtained as follows:

[0081]

[0082] Echo power P r is the integral of the power spectral density function over frequency:

[0083]

[0084] Then, the average Doppler frequency is the weighted average of the Doppler frequency f with the power spectral density function S(f) as weight:

[0085]

[0086] Spectral variance Defined as:

[0087]

[0088] According to the relationship between Doppler velocity and frequency, the average Doppler velocity and velocity spectrum width can be obtained as follows:

[0089]

[0090] (3) Inversion of cloud amount, cloud height, and cloud thickness based on the detection parameters of millimeter-wave cloud radar

[0091] This method is based on existing research and determines that the millimeter wave cloud radar reflectivity is greater than -20dBz as cloud, and then determines the points with reflectivity factor ≥ this threshold one by one according to the azimuth and distance library, and the count is N. cloud , use the binary method to calculate the connected domain, assuming that the number of PPI data points is N dot , then the cloud cover of the connected domain can be calculated as N cloud / N cloud ; Then, according to the method of judging each distance library from bottom to top, find the average lowest point (cloud base height) and the average highest point (cloud top height) at the height that meets the indicator ≥-20dBz, and the difference between the two is the cloud thickness; after meeting the above conditions, if more than 80% of the reflectivity factors in the cloud are greater than -5dBz, it is judged to be cumulonimbus cloud or cumulus cloud.

[0092] S20, converting the radar coordinates based on the unmanned boat into geodetic coordinates.

[0093] Since the global background field data is based on geodetic coordinates, it is necessary to convert the PPI data of the millimeter-wave cloud radar into geodetic coordinates in combination with the attitude parameters of the unmanned boat before the millimeter-wave radar data can be spatially interpolated into the background field data.

[0094] During the navigation of the unmanned boat, the attitude information of the inertial navigation is obtained: roll angle, pitch angle, heading angle, and the coordinate transformation model between the radar coordinate system and the geographic coordinate system is established. Figure 2 As shown, the coordinate transformation sequence from the radar coordinate system to the geographic coordinate system is performed in the order of roll angle γ-pitch angle β-heading angle α.

[0095] The transformation matrix T of the roll angle γ for:

[0096]

[0097] The conversion matrix Tα of the heading angle is:

[0098]

[0099] The transformation matrix T of the pitch angle β for:

[0100]

[0101] The transformation matrix Tradar from the geodetic coordinate system to the shipborne millimeter-wave cloud radar coordinate system is:

[0102] Tradar=T α T γ T β

[0103] The transformation matrix from the radar coordinate system to the geographic coordinate system is:

[0104] T Geo =(T radar ) T

[0105] S30, combining the fused cloud data of the previous time and the millimeter-wave cloud radar data of the current geodetic coordinate system to set the navigation route of the unmanned boat for autonomous navigation.

[0106] The navigation route of the unmanned boat is set with cumulonimbus and cumulus clouds as the target. The method for judging cumulonimbus and cumulus clouds is shown in S10(1)-(3).

[0107] An unmanned boat is an unmanned water platform that integrates advanced navigation, autonomous driving, sensor and communication technologies. Its core lies in autonomous navigation capabilities, which usually include:

[0108] Intelligent navigation: Through integrated GPS, sonar, LiDAR and other sensors, the unmanned boat can accurately obtain its own position and surrounding environment information and achieve autonomous navigation.

[0109] Path planning: The unmanned boat can autonomously plan and adjust the navigation path according to preset tasks or real-time conditions to avoid obstacles and ensure safe navigation.

[0110] Collision avoidance system: By real-time monitoring of surrounding ships and obstacles, the unmanned boat can make autonomous avoidance decisions to ensure safe navigation.

[0111] Combining the autonomous navigation capability of the unmanned boat platform, and based on the fused cloud cover data from the previous time and the current data of the millimeter-wave cloud radar, after comprehensively judging the location of cumulonimbus clouds and cumulus clouds, the unmanned boat equipped with millimeter-wave cloud radar heads to the target cloud location and carries out fixed-point scanning and detection.

[0112] S40, obtaining millimeter-wave cloud radar data of the unmanned boat during navigation; wherein the millimeter-wave cloud radar data is collected by the millimeter-wave cloud radar system based on radar detection parameters.

[0113] In this embodiment, the high-resolution detection technology of the millimeter-wave cloud radar is used to improve the accuracy of obtaining the sea cloud information, that is, to obtain millimeter-wave cloud radar data with higher accuracy.

[0114] The working principle of millimeter wave cloud radar is to transmit electromagnetic wave beams to the sky and then receive the reflected echo signals from the clouds to achieve high-resolution detection of clouds. Due to its short wavelength (3mm), it can more accurately obtain information such as the structure, morphology and water content of clouds at sea. In addition, millimeter waves have high penetration ability and small scattering, which can penetrate clouds and detect parameters such as the internal structure of clouds, cloud particle phase, and water content.

[0115] The original background field data usually refers to EC reanalysis data, GFS global forecast field data, etc. The highest resolution of these data is only 0.25°X0.25°, that is, the resolution is ≥25 kilometers. The wavelength of the millimeter wave cloud radar used in this embodiment is 3mm, the detection distance is 15 kilometers, and the distance resolution is 30 meters. The interpolation algorithm is used to fuse the millimeter wave cloud radar data to increase the cloud data resolution of the background field to 500 meters. Similarly, the cloud base height and cloud top high resolution of high clouds, medium clouds, and low clouds are increased by 500 meters.

[0116] S50. Based on the reflectivity and cloud amount formula, the millimeter wave cloud radar data is used to invert cloud parameters to obtain cloud parameter data during the navigation route, such as cloud amount, cloud base height, cloud top height, cloud thickness, etc. The detailed inversion method is shown in S10(3).

[0117] S60, interpolating the cloud cover data into the three-dimensional cloud cover data of the background field data to obtain fused data.

[0118] In this embodiment, a method of interpolation in polar coordinates is adopted, such as Figure 2 As shown, the calculation formula is:

[0119]

[0120] The cloud cover value of the interpolation point is obtained according to equation (2), and the corresponding weight coefficient is obtained through equation (1).

[0121] in:

[0122] w g : Weight coefficient of radar data sampling points;

[0123] R O ,θ O ,Φ o : The spherical coordinates of the interpolated radar data point P, which refer to the radial distance, azimuth and elevation of the data point respectively;

[0124] R g ,θ g ,Φ g : spherical coordinates of the original radar data points, where g = 1, 2, ..., N, N = 18;

[0125] 2 : By adjusting it, you can get different smoothing effects;

[0126] f g : reflectivity value of the original radar data point;

[0127] f o : reflectivity value of interpolated data points;

[0128] N: Grid point R g ,θ g ,Φ g The reflectivity value affects the number of distance bins in the area.

[0129] In another embodiment, the fused data, i.e., the fused three-dimensional cloud analysis results, can generate secondary meteorological products such as cloud amount, cloud base height, cloud top height, and cloud shape based on the fused three-dimensional cloud analysis results.

[0130] The embodiment of the present invention also provides a mobile fusion device for unmanned boat marine millimeter wave cloud radar and background field data, such as Figure 3 As shown, the device comprises:

[0131] The unmanned boat navigation posture and route parameter acquisition unit 301 is configured to acquire the navigation route and radar detection parameters of the unmanned boat;

[0132] The unmanned boat control unit 302 is configured to convert the radar coordinate system based on the unmanned boat into the geodetic coordinate system; combine the fused cloud data of the previous time and the millimeter wave cloud radar data of the current geodetic coordinate system to set the navigation route of the unmanned boat for autonomous navigation; wherein the unmanned boat is equipped with a millimeter wave cloud radar system;

[0133] The millimeter wave cloud radar parameter data acquisition unit 303 is configured to acquire the millimeter wave cloud radar data of the unmanned boat during navigation; wherein the millimeter wave cloud radar data is acquired by the millimeter wave cloud radar system based on the radar detection parameters;

[0134] The cloud parameter inversion unit 304 is configured to perform cloud amount inversion on the millimeter wave cloud radar data based on the reflectivity and cloud amount formula to obtain cloud amount data during the navigation route;

[0135] The millimeter wave cloud radar and background field data fusion unit 305 is configured to interpolate the cloud amount data into the three-dimensional cloud amount data of the background field data to obtain fused data.

[0136] In some embodiments, the millimeter wave cloud radar and background field data fusion unit is further configured as follows:

[0137]

[0138] In the formula, w g Represents the weight coefficient of the radar data sampling point;

[0139] R O ,θ O ,Φ o represents the spherical coordinates of the interpolated radar data point P, which are the radial distance, azimuth and elevation of the data point;

[0140] R g ,θ g ,Φ g represents the spherical coordinates of the original radar data points, where g = 1, 2, ..., N;

[0141] 2 represents the smoothing parameter;

[0142] f g Represents the reflectivity value of the original radar data point;

[0143] f o Represents the reflectivity value of the interpolated data point;

[0144] N stands for R g ,θ g ,Φ g The reflectivity value affects the number of distance bins in the area.

[0145] It should be noted that the various device structures described in this embodiment belong to the same technical concept as the previously described method, and achieve the same technical effect through the same principle, which will not be repeated here.

[0146] An embodiment of the present invention further provides a readable storage medium, which stores one or more programs. The one or more programs can be executed by one or more processors to implement the method described in any of the above embodiments.

[0147] In addition, although exemplary embodiments have been described herein, the scope includes any and all embodiments based on the present invention with equivalent elements, modifications, omissions, combinations (e.g., various embodiments intersecting schemes), adaptations or changes. The elements in the claims will be interpreted broadly based on the language adopted in the claims, and are not limited to the examples described in this specification or during the implementation of this application, and the examples will be interpreted as non-exclusive. Therefore, this specification and examples are intended to be considered as examples only, and the true scope and spirit are indicated by the following claims and the full scope of their equivalents.

[0148] The above description is intended to be illustrative rather than restrictive. For example, the above examples (or one or more of them) can be used in combination with each other. For example, those of ordinary skill in the art can use other embodiments when reading the above description. In addition, in the above-mentioned specific embodiments, various features can be grouped together to simplify the present invention. This should not be interpreted as a feature of an invention that is not claimed for protection being necessary for any claim. On the contrary, the subject matter of the present invention may be less than all the features of the embodiments of a specific invention. Thus, the following claims are incorporated into the specific embodiments as examples or embodiments, wherein each claim is independently used as a separate embodiment, and it is considered that these embodiments can be combined with each other in various combinations or arrangements. The scope of the present invention should be determined with reference to the full scope of the equivalent forms of the attached claims and these claims.

Claims

1. A method for maneuvering fusion of unmanned boat marine millimeter wave cloud radar and background field data, characterized in that: The method comprises: Obtain the navigation route and radar detection parameters of the unmanned boat; Convert the radar coordinate system based on the unmanned boat into the geodetic coordinate system; The unmanned boat is equipped with a millimeter-wave cloud radar system and a fusion cloud data of the last time and a millimeter-wave cloud radar data of the current geodetic coordinate system are used to set a navigation route for the unmanned boat to conduct autonomous navigation. Acquire millimeter-wave cloud radar data of the unmanned boat during navigation; wherein the millimeter-wave cloud radar data is collected by the millimeter-wave cloud radar system based on the radar detection parameters; Based on the reflectivity factor and cloud cover formula, the cloud cover data of millimeter wave cloud radar is inverted to obtain the cloud cover data during the navigation route; The cloud amount data is interpolated into the three-dimensional cloud amount data of the background field data to obtain fused data.

2. The method for maneuvering fusion of unmanned boat marine millimeter wave cloud radar and background field data according to claim 1 is characterized in that: The wavelength of the millimeter wave cloud radar system is 3mm.

3. The method for maneuvering fusion of unmanned boat marine millimeter wave cloud radar and background field data according to claim 1 is characterized in that: The information includes cloud amount, cloud base height and cloud top height.

4. The method for maneuvering fusion of unmanned boat marine millimeter wave cloud radar and background field data according to claim 3 is characterized in that: In the feature fusion sharing layer, the cloud cover data is interpolated into the three-dimensional cloud cover data of the background field data by the following formula to obtain the fused data: In the formula, w g Represents the weight coefficient of the radar data sampling point; R O ,θ O ,Φ o represents the spherical coordinates of the interpolated radar data point P, which are the radial distance, azimuth and elevation of the data point; R g ,θ g ,Φ g represents the spherical coordinates of the original radar data points, where g = 1, 2, ..., N; 2 represents the smoothing parameter; f g Represents the reflectivity value of the original radar data point; f o Represents the reflectivity value of the interpolated data point; N stands for R g ,θ g ,Φ g The reflectivity value affects the number of distance bins in the area.

5. The method for maneuvering fusion of unmanned boat marine millimeter wave cloud radar and background field data according to claim 1 is characterized in that: The background field data include EC reanalysis data and / or GFS global forecast field data.

6. The method for maneuvering fusion of unmanned boat marine millimeter wave cloud radar and background field data according to claim 1 is characterized in that: After interpolating the cloud amount data into the three-dimensional cloud amount data of the background field data to obtain fused data, the method further includes: Based on the fused data, secondary meteorological products such as cloud amount, cloud base height, cloud top height, and cloud shape are generated.

7. A mobile fusion device for unmanned boat marine millimeter wave cloud radar and background field data, characterized in that: The device comprises: The unmanned boat navigation attitude and route parameter acquisition unit is configured to obtain the navigation route and radar detection parameters of the unmanned boat; The unmanned boat control unit is configured to convert the radar coordinate system based on the unmanned boat into the geodetic coordinate system; comprehensively integrate the fused cloud data of the previous time and the millimeter wave cloud radar data of the current geodetic coordinate system to set the navigation route of the unmanned boat for autonomous navigation; wherein the unmanned boat is equipped with a millimeter wave cloud radar system; A millimeter wave cloud radar parameter data acquisition unit is configured to acquire millimeter wave cloud radar data of the unmanned boat during navigation; wherein the millimeter wave cloud radar data is acquired by the millimeter wave cloud radar system based on the radar detection parameters; A cloud parameter inversion unit is configured to perform cloud inversion on millimeter wave cloud radar data based on a reflectivity and cloud amount formula to obtain cloud amount data during the navigation route; The millimeter wave cloud radar and background field data fusion unit is configured to interpolate the cloud amount data into the three-dimensional cloud amount data of the background field data to obtain fused data.

8. The mobile fusion device for unmanned boat marine millimeter wave cloud radar and background field data according to claim 7 is characterized in that: The millimeter wave cloud radar and background field data fusion unit is further configured as follows: In the formula, w g Represents the weight coefficient of the radar data sampling point; R O ,θ O ,Φ o represents the spherical coordinates of the interpolated radar data point P, which are the radial distance, azimuth and elevation of the data point; R g ,θ g ,Φ g represents the spherical coordinates of the original radar data points, where g = 1, 2, ..., N; 2 represents the smoothing parameter; f g Represents the reflectivity value of the original radar data point; f o Represents the reflectivity value of the interpolated data point; N stands for R g ,θ g ,Φ g The reflectivity value affects the number of distance bins in the area.

9. A non-temporary computer-readable storage medium storing instructions, which, when executed by a processor, executes the method for maneuvering fusion of unmanned boat marine millimeter-wave cloud radar and background field data according to any one of claims 1 to 7.

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