Marine flare event prediction method and device based on satellite orbit simulation

Abstract

The invention provides a marine flare event prediction method and device based on satellite orbit simulation, and the method comprises the steps: inputting two lines of orbit element data into a satellite orbit prediction model for orbit parameter calculation, and obtaining the instantaneous orbit parameters of a satellite; constructing an initial observation vector under a sensor coordinate system based on the initial state parameter of the sensor, and performing coverage view field calculation based on the instantaneous orbit parameter and the initial observation vector to obtain an instantaneous coverage view field of the sensor; preprocessing the instantaneous coverage view field, and performing flare angle calculation on the preprocessed instantaneous coverage view field to obtain a corresponding instantaneous flare angle; and taking a set of the instantaneous coverage view fields corresponding to the instantaneous flare angles meeting the preset conditions as an ocean flare area and performing visual output. By simulating the satellite observation task, the ocean flare event in the satellite operation and observation process can be accurately predicted.

Description

Technical Field

[0001] The present invention relates to the field of satellite remote sensing technology, and in particular to a method and device for predicting ocean flare events based on satellite orbit simulation. Background Art

[0002] Sun glint refers to a specular reflection phenomenon caused by sunlight incident on the ocean or inland water. When satellites conduct detection over the ocean, the glittering blocks caused by sunlight irradiating the sea surface observed at a specific position and angle are ocean glints. Remote sensing satellites use flares to observe ocean areas, which has developed into an important means of ocean remote sensing.

[0003] The identification of ocean flares mainly relies on satellite transit observations. Traditional methods use satellite space observation data and positioning data in orbit. Although different satellites can provide time-continuous and high-spatial-resolution images, this method cannot provide real-time, large-scale, and space-free observation data. It cannot meet the need to predict the global distribution of ocean flares in advance in the future.

[0004] It can be seen that the ocean flare observation method in the relevant technology is to utilize the space observation data and positioning data of the satellite in orbit, and process the received data through specific algorithms inside the satellite to calculate and generate ocean flares. There is a technical problem that it is difficult to provide real-time and high-precision distribution of ocean flares. Summary of the invention

[0005] The present invention provides a method for predicting ocean flare events based on satellite orbit simulation, which is used to solve the problem that the ocean flare observation method in the prior art uses the space observation data and positioning data of the satellite in orbit, processes the received data through a specific algorithm inside the satellite to calculate and generate ocean flares, and is difficult to provide real-time and high-precision ocean flare distribution information. By simulating the satellite's orbit and the sensor's instantaneous coverage field of view, the occurrence location of the ocean flare can be predicted more accurately.

[0006] The present invention provides a method for predicting ocean flare events based on satellite orbit simulation, comprising the following steps.

[0007] Respectively obtaining initial state parameters of the satellite and the sensor, and two rows of orbital element data of the satellite; Inputting the two rows of orbital element data into a satellite orbit prediction model to calculate orbital parameters, thereby obtaining instantaneous orbital parameters of the satellite; An initial observation vector in a sensor coordinate system is constructed based on the initial state parameters of the sensor, and a coverage field calculation is performed based on the instantaneous orbit parameters and the initial observation vector to obtain an instantaneous coverage field of the sensor; Preprocessing the instantaneous covered field of view, and calculating the flare angle of the preprocessed instantaneous covered field of view to obtain a corresponding instantaneous flare angle; The set of instantaneous coverage fields corresponding to the instantaneous flare angles that meet preset conditions is taken as the ocean flare area and is visualized and output.

[0008] According to a method for predicting ocean flare events based on satellite orbit simulation provided by the present invention, the satellite orbit prediction model includes a constant simplified perturbation model, and the two rows of orbital element data are input into the satellite orbit prediction model to calculate orbital parameters to obtain instantaneous orbital parameters of the satellite, including: Decoding the two lines of orbital element data to obtain six orbital element numbers of the satellite; A conventional simplified perturbation model is called to calculate the instantaneous position data of the satellite based on the six orbital elements, and the instantaneous position data is used as the instantaneous orbital parameters.

[0009] According to a method for predicting ocean flare events based on satellite orbit simulation provided by the present invention, the coverage field calculation is performed based on the instantaneous orbit parameters and the initial observation vector to obtain the instantaneous coverage field of the sensor, including: Performing coordinate system conversion processing on the initial observation vector in the sensor coordinate system to obtain a target observation vector in the earth coordinate system; The coordinates corresponding to each pixel of the sensor are calculated based on the target observation vector and the instantaneous orbit parameter, and the set of coordinates corresponding to all the pixels is used as the instantaneous coverage field of view of the sensor.

[0010] According to a method for predicting ocean flare events based on satellite orbit simulation provided by the present invention, the initial state parameters of the sensor include the inclination angle of the sensor, the instantaneous orbit parameters include the orbit inclination angle, the right ascension of the ascending node, the argument of perigee and the true anomaly of the satellite, and the initial observation vector in the sensor coordinate system is subjected to coordinate system conversion processing to obtain a target observation vector in the geodetic coordinate system, including: Constructing a first conversion matrix based on the sensor tilt angle, and performing a coordinate system conversion on the initial observation vector in the sensor coordinate system based on the first conversion matrix to obtain a first observation vector in the satellite body coordinate system; Constructing a second transformation matrix based on the Euler angles between the satellite body coordinate system and the satellite orbit coordinate system, and performing a coordinate system transformation on the first observation vector in the satellite body coordinate system based on the second transformation matrix to obtain a second observation vector in the satellite orbit coordinate system; Constructing a third transformation matrix based on the orbital inclination, the right ascension of the ascending node, the argument of perigee, and the true anomaly of the satellite, and performing a coordinate system transformation on the second observation vector in the satellite orbit coordinate system based on the third transformation matrix to obtain a third observation vector in the geocentric inertial coordinate system; Calculate the earth rotation matrix based on Greenwich sidereal time, calculate the precession matrix based on the Julian day corresponding to the universal time and the current running time, and construct a fourth conversion matrix based on the earth rotation matrix and the precession matrix; Performing a coordinate system transformation on the third observation vector in the geocentric inertial coordinate system based on the fourth transformation matrix to obtain a fourth observation vector in the geocentric fixed coordinate system; The fourth observation vector in the geocentric fixed coordinate system is subjected to a coordinate system transformation to obtain a target observation vector in the geodetic coordinate system.

[0011] According to a method for predicting ocean flare events based on satellite orbit simulation provided by the present invention, the preprocessing of the instantaneous coverage field of view includes: The ocean area recognition model is called to filter the land area in the instantaneous covered field of view to obtain an ocean area, and the ocean area is used as the preprocessed instantaneous covered field of view.

[0012] According to a method for predicting ocean flare events based on satellite orbit simulation provided by the present invention, the flare angle calculation is performed on the preprocessed instantaneous coverage field of view to obtain the corresponding instantaneous flare angle, including: Performing numerical calculation of observation geometry on the instantaneous coverage field after preprocessing to obtain the solar zenith angle, the solar azimuth angle, the observation zenith angle and the observation azimuth angle; The instantaneous flare angle is calculated based on the solar zenith angle, the solar azimuth angle, the observation zenith angle and the observation azimuth angle.

[0013] According to a method for predicting ocean flare events based on satellite orbit simulation provided by the present invention, the initial state parameters of the satellite include the inclination angle of the satellite, the orbital altitude and the current operating time of the satellite; the initial state parameters of the sensor include the field of view angle of the sensor and the geometric shape of the sensor field of view.

[0014] The present invention also provides an ocean flare event prediction device based on satellite orbit simulation, comprising the following modules: An acquisition module, used to respectively acquire initial state parameters of the satellite and the sensor, and two rows of orbital element data of the satellite; An orbit parameter calculation module, used for inputting the two rows of orbit element data into a satellite orbit prediction model to calculate orbit parameters, and obtain instantaneous orbit parameters of the satellite; A coverage field calculation module, used to construct an initial observation vector in a sensor coordinate system based on the initial state parameters of the sensor, and to perform coverage field calculation based on the instantaneous orbit parameters and the initial observation vector to obtain an instantaneous coverage field of the sensor; A flare angle calculation module, used to preprocess the instantaneous covered field of view, and perform flare angle calculation on the preprocessed instantaneous covered field of view to obtain a corresponding instantaneous flare angle; The result output module is used to take the set of instantaneous coverage fields corresponding to the instantaneous flare angles that meet preset conditions as the ocean flare area and output it visually.

[0015] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements any of the above-described methods for predicting ocean flare events based on satellite orbit simulation.

[0016] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for predicting ocean flare events based on satellite orbit simulation as described in any one of the above is implemented.

[0017] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned methods for predicting ocean flare events based on satellite orbit simulation.

[0018] The method and device for predicting ocean flare events based on satellite orbit simulation provided by the present invention obtain the instantaneous orbit parameters of the satellite by performing orbit parameter calculation on two rows of orbital element data of the satellite, and obtain the instantaneous coverage field of view of the sensor by performing coverage field calculation based on the instantaneous orbit parameters and the initial observation vector, thereby realizing real-time and efficient prediction of the field of view of the satellite sensor; finally, the flare angle is calculated on the preprocessed instantaneous coverage field of view to obtain the corresponding instantaneous flare angle, and the set of instantaneous coverage fields corresponding to the instantaneous flare angles that meet preset conditions is used as the ocean flare area and is output visually, thereby realizing rapid prediction and calculation of large-area ocean flare areas without the need for complex ground surveys, thereby effectively improving the efficiency of ocean flare prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced one by one below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 This is one of the flow charts of the method for predicting ocean flare events based on satellite orbit simulation provided by the present invention.

[0021] Figure 2 This is the second flow chart of the method for predicting ocean flare events based on satellite orbit simulation provided by the present invention.

[0022] Figure 3 It is a schematic diagram of a satellite orbit prediction model of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0023] Figure 4 It is a schematic diagram of a sensor coverage calculation model of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0024] Figure 5 It is a schematic diagram of the intersection of the observation vector and the earth of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0025] Figure 6 It is a schematic diagram of the initial observation vector of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0026] Figure 7 It is a schematic diagram of the observation vector coordinate system conversion process of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0027] Figure 8 It is a schematic diagram of a flare angle calculation model of an ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0028] Fig. 9 It is a schematic diagram of satellite five-hour trajectory prediction of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0029] Fig.10 It is a schematic diagram of satellite trajectory simulation of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0030] Fig.11 It is a schematic diagram of the actual satellite trajectory of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0031] Fig.12 It is a schematic diagram of the error between the sub-satellite point comparison between the satellite simulated trajectory and the actual trajectory of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0032] Fig.13 It is a schematic diagram of sensor field of view simulation of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0033] Fig.14 It is a schematic diagram of satellite field of view simulation boundary of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0034] Fig.15 It is a schematic diagram comparing the left and right boundary errors of the field of view of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0035] Fig.16 It is a schematic diagram of the distribution of simulated flare angle and actual flare angle of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0036] Fig.17 It is a schematic diagram of satellite true color image comparison of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0037] Fig.18 It is a structural schematic diagram of the ocean flare event prediction device based on satellite orbit simulation provided by the present invention.

[0038] Fig.19 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] Remote sensing satellites use flares to observe ocean areas, which has developed into an important means of ocean remote sensing. In some ocean satellite-ground synchronous observation missions, the strong reflectivity and high brightness of ocean flares will lead to reduced contrast and local information loss of satellite images, affecting image recognition and analysis, and it is necessary to avoid the areas where ocean flares occur; on the other hand, ocean flares have strong polarization characteristics, and their reflection characteristics can be accurately calculated through the sea surface reflection model. Therefore, they can be used as an effective alternative light source for satellite on-orbit polarization calibration. On-orbit polarization calibration requires a large number of flare samples to be quickly and effectively determined, and the quantity and quality must be ensured, thereby fundamentally improving the accuracy requirements of on-orbit polarization calibration. Whether it is to use ocean flares or avoid their impact, it is extremely important to accurately predict the location and occurrence time of ocean flares in advance.

[0041] However, ocean flares are instantaneous, random, and affected by factors such as clouds and atmospheric interference. Accurately observing ocean flares has become a technical challenge. The identification of ocean flare occurrence areas mainly relies on satellite transit observations. Traditional methods use satellite space observation data and positioning data in orbit, process the received data through specific algorithms inside the satellite, and calculate and visualize ocean flare image products at different time points. Users can choose ocean flare remote sensing images from different satellites according to their needs. Although different satellites can provide images with temporal continuity and high spatial resolution, this method cannot provide real-time, large-scale observation data that is not constrained by time and space. Existing methods for observing and identifying ocean flares only stay at interpreting processed remote sensing image data to calculate the flare area, which cannot meet the needs of being able to predict the global distribution of ocean flares in advance in large quantities in the future.

[0042] Combine the following Figure 1-Figure 17 The present invention describes a method for predicting ocean flare events based on satellite orbit simulation.

[0043] First, the corresponding technical concepts in the technical solution provided by the present invention are explained: (1) Two-Line Element Data: Two-Line Element (TLE) is a parameter file used to predict the orbital position of satellites. TLE is a mean element that takes into account the effects of the Earth's oblateness, the secular and periodic perturbations of the Sun and Moon's gravity, and the gravitational resonance and orbital decay generated by the atmospheric drag model. The periodic perturbation term is removed using a specific method. TLE consists of two lines of parameters. The first line of parameters includes the orbit report number, satellite number, satellite classification identifier, satellite launch year, satellite launch serial number of the year, epoch year, epoch time, first-order time derivative of mean motion, second-order time derivative of mean motion, BSTAR drag modulation coefficient, ephemeris type, ephemeris number, and checksum; the second line of parameters includes the orbit report number, satellite number, orbit inclination, right ascension of the ascending node, eccentricity, perigee angular distance, mean anomaly, the number of orbits the satellite makes around the Earth in 24 hours, orbit circle number, and checksum.

[0044] (2) Simplified General Perturbations-4 (SGP4): used for orbit prediction of near-Earth spacecraft with an orbital period less than or equal to 225 minutes. Substituting TLE into the SGP4 model, the position and velocity of the satellite at any time can be calculated. The prediction accuracy of the model within 24 hours is 1 to 3 km. Due to the influence of perturbations such as the non-spherical gravity of the earth, the gravity of the sun and the moon, the atmosphere and solar pressure, the longer the prediction period, the greater the error. Therefore, in business work, the TLE (two-line element orbit report) of the day is generally used to calculate the receiving time window and tracking point position.

[0045] (3) Six orbital parameters: six parameters that describe the orbit of a celestial body, including the semi-major axis, which determines the size of the orbit; the eccentricity, which reflects the degree to which the orbit is elliptical; the inclination, which reflects the angle between the orbital plane and the reference plane; the right ascension of the ascending node and the argument of perigee, which determine the direction of the orbit in space; and the true anomaly, which indicates the position of the celestial body in its orbit.

[0046] (4) Pixel: The pixel of a satellite sensor is the basic unit of sensor imaging. Pixels are like small squares that can sense and record electromagnetic radiation energy reflected or emitted from the earth's surface. Its size affects the resolution of the image. Smaller pixel sizes generally provide higher-resolution images, thereby presenting more detailed information such as details of surface objects.

[0047] (5) POSP payload: A position and orientation system for payloads (POSP) that can accurately obtain the position information and attitude data of sensors. It plays a key role in aerospace remote sensing and other fields. By providing high-precision spatial position (such as three-dimensional coordinates) and attitude (such as roll, pitch, yaw) parameters, the data obtained by the onboard imaging equipment can be more accurately geolocated and image registered, effectively improving the quality and application value of remote sensing data.

[0048] Optionally, the ocean flare event prediction method based on satellite orbit simulation of an embodiment of the present application can be executed by a server, or by a terminal device, or jointly by a server and a terminal device, taking the example of the ocean flare event prediction method based on satellite orbit simulation in this embodiment being executed by a server.

[0049] Figure 1 This is one of the flow charts of the method for predicting ocean flare events based on satellite orbit simulation provided by the present invention, such as Figure 1 As shown, the method includes the following steps 101 to 105.

[0050] Step 101: respectively obtain initial state parameters of the satellite and the sensor, and two rows of orbital element data of the satellite.

[0051] In some embodiments, the initial state parameters of the satellite include the satellite's inclination, orbital altitude, and current operating time of the satellite; the initial state parameters of the sensor include the sensor's field of view angle and the geometry of the sensor's field of view.

[0052] Specifically, the simulation of different on-orbit satellite movements and the implementation of the working process carried on the satellite payload are all designed based on the actual factory parameters and working principles of the satellite and payload. Therefore, for the initial operation of the entire ocean flare prediction system, it is first necessary to establish the initial state parameters of the satellite and payload (i.e., sensor), such as the satellite's orbital parameters (such as inclination i), the payload field of view (FOV), the adopted through-track scanning method and the satellite's TLE orbit report data, etc., and set the initial state of the satellite according to the satellite's specification parameters, including the current operating time, the operating orbit altitude, and the number of six orbits. In the present invention, the parameter input modules of the satellite and the payload correspond to two different working blocks respectively, so it is necessary to design two different ports to access and output to the corresponding numerical model, and at the same time facilitate the result feedback to find problems that occur during the input process.

[0053] In the embodiment of the present invention, by respectively acquiring the initial state parameters of the satellite and the sensor, and designing two different ports to access and output to the corresponding numerical model, it is convenient to perform subsequent related calculations according to the initial state parameters, thereby improving the subsequent calculation efficiency.

[0054] Step 102: Input the two rows of orbital element data into a satellite orbit prediction model to calculate orbital parameters, and obtain instantaneous orbital parameters of the satellite.

[0055] In some embodiments, the satellite orbit prediction model includes a simplified conventional perturbation model, and step 102 can be specifically implemented in the following manner: interpreting and processing the two lines of orbital element data to obtain the six orbital elements of the satellite; calling the simplified conventional perturbation model to calculate the instantaneous position data of the satellite based on the six orbital elements, and using the instantaneous position data as the instantaneous orbital parameters.

[0056] Specifically, see Figure 3 , Figure 3 Schematic diagram of a satellite orbit prediction model of an ocean flare event prediction method based on satellite orbit simulation provided by the present invention, such as Figure 3 As shown in the figure, the satellite orbit prediction model includes the orbit parameter interpretation layer, the SGP4 model algorithm layer and the result output layer. The main functions of these three parts are connected by direct sequence transfer.

[0057] First, the two lines of orbital element data are interpreted and processed through the orbital parameter interpretation layer, and converted into the six orbital elements of the satellite, that is, the orbital inclination, right ascension of the ascending node, orbital eccentricity, perigee argument, mean anomaly and semi-major axis are obtained according to the fields. In addition, the orbital parameter interpretation layer also needs to realize the conversion between the mean anomaly and the true anomaly. The calculation method is as follows: Among them, M represents the mean anomaly angle, E represents the eccentric anomaly angle, represents the true anomaly angle, e It represents the eccentricity of the satellite orbit and is used to indicate the degree of eccentricity of the elliptical orbit.

[0058] The orbital model algorithm layer (i.e., SGP4 model algorithm layer) includes the mathematical model of the conventional simplified perturbation model. The orbital model algorithm layer constructs the satellite's motion orbit parameters and calculates the satellite's position by considering the main influencing factors such as the earth's gravitational field, atmospheric drag, and the earth's perturbation force.

[0059] The orbit model algorithm layer includes three main parts: the first part is used to realize the calculation of perturbation terms. The perturbation terms are used to represent the influence of factors such as the earth's gravity, the sun's gravity, the moon's gravity and atmospheric friction on the satellite orbit in the satellite orbit prediction. The specific calculation method is as follows: in, , , represents the coordinates of the perturbation term; , , , , , are the coefficients of the perturbation terms.

[0060] The second part of the orbit model algorithm layer is used to calculate the first-order derivative of the perturbation term, that is, to calculate the rate of change of the perturbation term over time and obtain the velocity of the perturbation term: in, is the inclination of the satellite orbit, , , express , , The first derivative of .

[0061] The third part of the orbit model algorithm layer is used to output the instantaneous position data and instantaneous velocity data of the satellite. The position and velocity of the satellite are usually expressed as the position vector in the spatial rectangular coordinate system. and the velocity vector To describe: in, is the right ascension of the ascending node, , , Indicates the direction of a vector.

[0062] Continue to see Figure 3 , Figure 3 The result output layer shown is mainly used to output the calculation results of the SGP4 model algorithm layer, such as the output of instantaneous orbital parameters such as instantaneous position data and instantaneous velocity data, for verification or viewing. The most important thing is to output the calculation results of the satellite's instantaneous position. The output is set in the form of a chart, and the calling function of the sensor coverage calculation model is also set.

[0063] In an embodiment of the present invention, the orbital parameters of the satellite are predicted and visualized through a satellite orbit prediction model, which facilitates the subsequent calculation of the flare angle in combination with the payload visual field, thereby improving the computational efficiency of ocean flare prediction.

[0064] Step 103: construct an initial observation vector in the sensor coordinate system based on the initial state parameters of the sensor, and calculate the coverage field of view based on the instantaneous orbit parameters and the initial observation vector to obtain the instantaneous coverage field of view of the sensor.

[0065] In some embodiments, see Figure 4 , Figure 4 It is a schematic diagram of the sensor coverage calculation model of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention. Step 103 is mainly completed by the sensor coverage calculation model to achieve accurate positioning of pixels at different positions in the satellite observation field of view. The sensor coverage calculation model includes a triangle vector algorithm model, a satellite position data call control layer, a coordinate system conversion algorithm compilation library and a pixel position output layer, wherein the triangle vector algorithm model, the satellite position data call control layer and the coordinate system conversion algorithm compilation library are mainly used for coverage calculation compilation control.

[0066] The sensor coverage calculation model first constructs the initial observation vector in the sensor coordinate system based on the geometric shape of the sensor field of view and the sensor parameters, and calls the control layer through the satellite position data to call the satellite orbit prediction data (i.e., the satellite instantaneous orbit parameters) as input, and calls the coordinate system conversion algorithm compilation library to convert the initial observation vector in different celestial coordinate systems, and calculates the satellite's target observation vector and position vector. Finally, the triangle vector method is used to calculate the intersection of the satellite's observation field of view and the earth model, and the triangular geometric relationship between the satellite observation vector, the earth intersection and the center of the earth is constructed. The intersection of the sensor's target observation vector on the earth is solved, thereby calculating the instantaneous coverage field of view of the satellite sensor, and batch calculating and covering the pixels in the field of view, and outputting the calculation results through the pixel position output layer. See Figure 5 , Figure 5Schematic diagram of the intersection of the observation vector and the earth of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention, Figure 5 The application method of the triangle vector method is shown in Indicates the center of the earth. represents the radius of the Earth, Indicates the satellite inclination.

[0067] Specifically, the satellite's attitude is first predefined, taking into account attitude factors such as satellite rotation, tilt and field of view angle, to reduce the impact of satellite attitude on satellite sensor field of view simulation, and then construct the initial observation vector in the sensor coordinate system. Figure 6 , Figure 6 It is a schematic diagram of the initial observation vector of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention, wherein a coordinate system is established with the center of the sensor surface as the origin O, wherein the Z axis points to the center of the earth, the X axis corresponds to the flight direction of the satellite, and the Y axis is perpendicular to the flight direction and represents the scanning direction. In this sensor coordinate system, the sensor focus is represented as F, any point on the circular boundary is N, and the point located on the circular boundary and on the axis is M. An observation vector FN is defined, which represents the vector from the sensor focus F to any point N on the circular boundary, which can be obtained by rotating the angle θ from point M to point N along the Z axis. The initial observation vector of the sensor is represented as , assuming |OF|=f is the focal length, and the radius of the conic section circle |OM|=r. Then the initial observation vector The definition is as follows: Normalize formula (6): in, represents the half field of view of the sensor, Indicates the middle angle within the sensor, ranging from 0 to 2π, in radians.

[0068] These values ​​are related to the number of sampling points n selected. When n=2, it is a linear observation, and when n=4, it is a frame observation. Using the position parameters of the earth and the satellite, define the initial observation vector of the satellite , which expresses the observation position of the satellite relative to the earth. This initial observation vector covers the observation direction and position information, and can effectively describe the satellite's observation field of view.

[0069] In some embodiments, the coverage field of view is calculated based on the instantaneous orbit parameters and the initial observation vector to obtain the instantaneous coverage field of view of the sensor, which can be specifically achieved in the following ways: the initial observation vector in the sensor coordinate system is converted into a coordinate system to obtain a target observation vector in the earth coordinate system; the coordinates corresponding to each pixel of the sensor are calculated based on the target observation vector and the instantaneous orbit parameters, and the set of coordinates corresponding to all pixels is used as the instantaneous coverage field of view of the sensor.

[0070] In some embodiments, the initial state parameters of the sensor include the inclination angle of the sensor, and the instantaneous orbit parameters include the orbital inclination angle of the satellite, the right ascension of the ascending node, the argument of perigee and the true anomaly angle. The initial observation vector in the sensor coordinate system is subjected to coordinate system conversion processing to obtain the target observation vector in the geodetic coordinate system. This can be achieved in the following ways: constructing a first conversion matrix based on the sensor inclination angle, and performing coordinate system conversion on the initial observation vector in the sensor coordinate system based on the first conversion matrix to obtain the first observation vector in the satellite body coordinate system; constructing a second conversion matrix based on the Euler angle between the satellite body coordinate system and the satellite orbit coordinate system, and performing coordinate system conversion on the first observation vector in the satellite body coordinate system based on the second conversion matrix to obtain the satellite orbit coordinate system. a second observation vector in the geocentric inertial coordinate system; a third conversion matrix is ​​constructed based on the satellite's orbital inclination, right ascension of the ascending node, argument of perigee and true anomaly, and the second observation vector in the satellite orbital coordinate system is converted into a coordinate system based on the third conversion matrix to obtain the third observation vector in the geocentric inertial coordinate system; the earth rotation matrix is ​​calculated based on Greenwich sidereal time, the precession matrix is ​​calculated based on the Julian day corresponding to the world standard time and the current operating time, and a fourth conversion matrix is ​​constructed based on the earth rotation matrix and the precession matrix; the third observation vector in the geocentric inertial coordinate system is converted into a coordinate system based on the fourth conversion matrix to obtain the fourth observation vector in the geocentric fixed coordinate system; the fourth observation vector in the geocentric fixed coordinate system is converted into a coordinate system to obtain the target observation vector in the geodetic coordinate system.

[0071] Specifically, after obtaining the initial observation vector, it is necessary to establish the initial observation vector in different coordinate systems. The final goal is to convert the observation vector of the satellite body coordinate system into the target observation vector of the geocentric coordinate system. Figure 7 , Figure 7 It is a schematic diagram of the observation vector coordinate system conversion process of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention. The specific rotation method of the coordinate system needs to be determined according to relevant parameters, including sensor parameters, satellite attitude, satellite ephemeris, hour angle, etc.

[0072] First, the satellite sensor center coordinate system is converted to the satellite body coordinate system, and the inclination angle of the sensor in the satellite orbit plane is recorded as , with the vertical direction as the axis; the inclination angle of the sensor relative to the satellite orbit is recorded as , then the first transformation matrix that transforms the sensor coordinate system to the satellite body coordinate system is It can be expressed by the following relationship: Based on the first transformation matrix By performing coordinate system transformation on the initial observation vector in the sensor coordinate system, the first observation vector in the satellite body coordinate system can be obtained.

[0073] Then the satellite body coordinate system is converted to the satellite orbit coordinate system. According to the definition of the satellite body coordinate system and the orbit coordinate system, the relationship between angular displacements can be described by rotation. In the satellite body coordinate system, the three parameters are the satellite roll angle (roll), pitch angle (pitch), and yaw angle (yaw). The three together define the attitude of the satellite. The general conversion process is as follows: first rotate the pitch around the Y axis, then rotate the roll around the Y axis, and finally rotate the yaw around the Z axis, so that the body coordinate system coincides with the satellite orbit coordinate system, and this conversion relationship can be described by the Euler angle. The Euler angle is a combination of three rotation angles used to describe the rotation of one coordinate system relative to another coordinate system. Therefore, the conversion from the satellite body coordinate system to the orbit coordinate system is achieved through the rotation matrix of the Euler angle, and the second conversion matrix between the two is as follows: Based on the second transformation matrix By performing coordinate system transformation on the first observation vector in the satellite body coordinate system, the second observation vector in the satellite orbit coordinate system can be obtained.

[0074] Then the satellite orbit coordinate system is converted to the geocentric inertial coordinate system. The satellite moves in space in its orbit, and this orbit can be described by different reference systems relative to the earth. Among them, the satellite orbit system is a commonly used reference system, while the geocentric inertial system is a more common global reference system. The conversion matrix of the satellite orbit coordinate system to the geocentric inertial coordinate system needs to take into account multiple factors, including the satellite orbit parameters. These orbit parameters include the orbital inclination. , right ascension of ascending node , Argument of perigee True Anomaly By calculating these orbital parameters, the conversion matrix from the satellite orbital reference system to the geocentric inertial reference system can be established, thereby achieving accurate description and analysis of satellite orbital motion in different reference systems. The third conversion matrix between the two as follows: Based on the third transformation matrix By performing coordinate system transformation on the second observation vector in the satellite orbit coordinate system, the third observation vector in the geocentric inertial coordinate system can be obtained.

[0075] Next is to convert the geocentric inertial coordinate system to the geocentric fixed coordinate system. The complexity of the earth's motion determines that the conversion from the geocentric inertial coordinate system to the geocentric fixed coordinate system is not fixed, but changes with the rotation of the earth. The conversion relationship matrix follows the standard of the International Astronomical Union in 2000. This conversion is closely related to the earth's nutation, precession and polar drift, which are all the result of the earth's rotation. The fourth conversion matrix of the two The calculation process is as follows: Greenwich Sidereal Time : The angle between Greenwich mean sidereal time and sidereal time for: Earth rotation matrix for: Julian day corresponding to Coordinated Universal Time (UTC) (yr-mon-day-hr-min-sec) for: The Julian century number T from J2000.0 to a given moment is: The precession angle is: The precession matrix P is: The fourth transformation matrix from the geocentric inertial coordinate system to the geocentric fixed coordinate system for: Based on the fourth transformation matrix The third observation vector in the geocentric inertial coordinate system is transformed into a coordinate system to obtain a fourth observation vector in the geocentric fixed coordinate system.

[0076] Finally, the geocentric fixed coordinate system is converted to the geodetic coordinate system. The geocentric fixed coordinate system and the geodetic coordinate system are essentially two ways of expressing the same coordinate system. Therefore, when the position of the geocentric fixed coordinate system [X, Y, Z] is known, it is converted to the latitude and longitude coordinates (lat, lon, H) in the geodetic coordinate system. The calculation can be performed by the following method: in, The first eccentricity of the Earth, .

[0077] In addition, there is a simplified way to calculate geographic coordinates, which is to omit the height information of geographic coordinates. The simplified geographic coordinate system is represented by (lat, lon), while the geocentric rectangular coordinate system is represented by [X, Y, Z]. The conversion relationship between them is as follows: Finally, in the same coordinate system, the target observation vector ( , ), that is, the satellite position vector L=[ , , ], observation vector S=[ , , ]The collinear equation of the intersection point with the earth and the ellipsoid equation of the earth, solve the intersection point coordinates Similarly, the coordinates of each pixel of the sensor are calculated one by one: The output of the sensor coverage calculation model is mainly the position of ground pixels observed by satellites. The data is mainly saved in longitude and latitude format. The set of positions of all ground pixels observed by satellites is the instantaneous coverage field of view of the sensor. In addition, the sensor coverage calculation model also sets the calling function of the flare angle calculation model.

[0078] In an embodiment of the present invention, the target observation vector is obtained by transforming the coordinate system of the initial observation vector, and the instantaneous coverage field of view is calculated based on the target observation vector and the instantaneous orbit parameters to obtain the instantaneous coverage field of view of the sensor. The instantaneous coverage field of view of the sensor can be predicted in real time, effectively improving the calculation efficiency of the sensor's coverage field of view, and facilitating the subsequent calculation of the flare angle and ocean flare.

[0079] Step 104: pre-process the instantaneous coverage field of view, and calculate the flare angle of the pre-processed instantaneous coverage field of view to obtain the corresponding instantaneous flare angle.

[0080] In some embodiments, preprocessing the instantaneous coverage field of view can be specifically achieved in the following manner: calling an ocean area recognition model to filter the land area in the instantaneous coverage field of view to obtain the ocean area, and using the ocean area as the preprocessed instantaneous coverage field of view.

[0081] The flare angle of the preprocessed instantaneous coverage field of view is calculated to obtain the corresponding instantaneous flare angle, which can be specifically achieved in the following ways: numerical calculation of the observation geometry of the preprocessed instantaneous coverage field of view is performed to obtain the solar zenith angle, solar azimuth angle, observation zenith angle and observation azimuth angle; the instantaneous flare angle is calculated based on the solar zenith angle, solar azimuth angle, observation zenith angle and observation azimuth angle.

[0082] Specifically, see Figure 8 , Figure 8 is a schematic diagram of a flare angle calculation model of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention. Step 104 mainly includes: Figure 8 The flare angle calculation model implementation shown includes an input layer, an observation geometry algorithm layer, a flare angle algorithm layer and an output layer, and its core is the observation geometry algorithm and the flare angle algorithm.

[0083] The input layer mainly covers the observation range of satellite sensors at different times, which is mainly manifested as the longitude and latitude of the coverage area. In order to preliminarily screen out the ocean area, an ocean area recognition model is also compiled in the input layer to filter out the position of the land area and obtain the ocean area, that is, the instantaneous coverage field of view after preprocessing; the observation geometry algorithm layer establishes an algorithm based on the observation geometry of the sea level pixel position, including the observation zenith angle, observation azimuth angle, solar zenith angle and solar azimuth angle; the flare angle algorithm layer takes the observation geometry as input, inputs it into the compiled flare angle algorithm, and outputs the flare angle; the output layer is used to output the results after screening based on the angle threshold, and the output form can be selected, such as a distribution map or a data table.

[0084] The observation geometry algorithm layer first preprocesses the satellite and ground position data (lat, lon), including the data sorting, screening, and other processing of satellite orbit prediction and sensor field of view simulation to improve data processing efficiency and accuracy. Then, the mathematical model algorithm is used to build a numerical model for ocean flare prediction. First, the observation geometry numerical calculation model is built, and the intermediate results are output. The intermediate results include the solar zenith angle (SZA), solar azimuth angle (SAA), observation zenith angle (VZA) and observation azimuth angle (VAA): in, is the latitude of the observation point, is the declination of the sun, is the hour angle of the sun, is the latitude of the satellite, is the latitude of the ground location, is the longitude of the satellite, is the longitude of the ground location, It is the difference between the longitude of the satellite and the longitude of the observation point.

[0085] The flare angle algorithm layer is used to calculate and output the observation results during satellite operation in real time, that is, to input the preprocessed data into the flare angle numerical model and output the instantaneous flare angle in real time. : in, , , , They represent the solar geometry (zenith angle, azimuth angle) and the observation geometry (zenith angle, azimuth angle), .

[0086] In an embodiment of the present invention, the location of the land area is filtered out through the ocean area recognition model to obtain the ocean area, which can effectively reduce the interference of the land area on the ocean flare observation results and improve the accuracy of ocean flare identification.

[0087] Step 105: The set of instantaneous coverage fields corresponding to the instantaneous flare angles that meet preset conditions is taken as an ocean flare area and is output visually.

[0088] Since the reflected light from the sun is still concentrated in a small angle range, the sensor needs to be within a small flare angle range (i.e. close to the reflection direction) to capture a sufficiently strong reflected light signal. Therefore, the definition of the flare angle is derived based on the observation geometry to realize the judgment of the flare angle, that is, when the flare angle is less than a certain angle, the reflected light intensity is high and concentrated, which is suitable for satellite sensor observation. For example, when the flare angle less than 40 degrees can meet the needs of the observation task, the preset condition is set as the threshold of the flare angle, and the set of instantaneous coverage fields corresponding to the flare angle less than 40 degrees is used as the ocean flare area and visualized output, thereby controlling the output of different ocean flare area simulation results. The observation area that meets the observation requirements is screened, and the ocean flare area is visualized through simulation software such as MATLAB.

[0089] In an embodiment of the present invention, by setting preset conditions such as the flare angle threshold, the instantaneous coverage field of view corresponding to the flare angle that meets the ocean flare observation needs is screened, the ocean flare area is obtained and visualized output, thereby achieving rapid and accurate prediction of ocean flares.

[0090] In some embodiments, see Figure 2 , Figure 2 This is the second flow chart of the method for predicting ocean flare events based on satellite orbit simulation provided by the present invention, such as Figure 2 As shown, the ocean flare event prediction method based on satellite orbit simulation provided by the present invention mainly realizes the prediction of satellite orbit through the ocean flare event prediction model, and realizes the active prediction task of ocean flares by combining the simulation of satellite observation field of view. First, the initial state parameters of the model are set, and then the satellite position and the payload visual field are output through the satellite orbit prediction model and the payload coverage calculation model respectively, and then the flare angle is output through the observation geometry model, and the ocean flare judgment model is used to judge the ocean flare based on the flare angle, and finally the ocean flare judgment result is output.

[0091] The present invention simulates the observation process of different satellites and the target payloads on board to determine the positions of the satellite observation point, the sun and the satellite, and then identifies the ocean flare based on the flare observation geometric model. This includes the prediction of the satellite motion trajectory, the field of view coverage area of ​​the satellite observing the surface at the corresponding moment, and the active identification of ocean flare events.

[0092] In other embodiments, the ocean flare prediction model mainly realizes the active prediction task of ocean flares by predicting the satellite orbit and simulating the satellite observation field of view. The design of the present invention is based on the relevant parameters of my country's Gaofen-5B satellite and the POSP payload carried by the satellite to perform model design inspection, and the design method and implementation of the model are verified through real satellite observation tasks and scenarios. MATLAB is used to compare and analyze the parameters such as the sub-satellite point trajectory and the satellite field of view boundary, evaluate the error of the simulation result, and check the difference between it and the actual observation result to ensure the accuracy of the satellite observation field simulation.

[0093] The first is the satellite orbit prediction implementation and result analysis. The goal of GF-5B satellite orbit prediction is to accurately observe the position and trajectory of the satellite in the future time period, which is the key to ensure that the satellite can effectively cover the ocean area. The specific design includes: according to the satellite's specification parameters, the initial state of the satellite is set, including time, orbit altitude, six orbit numbers, etc., see Table 1 and Table 2, Table 1 is the GF-5B satellite parameter table, Table 2 is the GF-5B satellite orbit parameter table.

[0094] Table 1 GF-5B satellite parameters

[0095] Table 2 GF-5B satellite orbit parameters

[0096] When constructing the SGP4 (orbital model algorithm) numerical model, the initial orbital parameters of the GF-5B satellite were first obtained from the TLE data and used as the input of the SGP4 model. According to the mathematical model of the SGP4 model, the corresponding calculation program was written, and the main influencing factors such as the earth's gravitational field, atmospheric drag, and earth perturbation were considered to achieve the numerical solution of the GF-5B satellite orbit. According to the current satellite status and environmental factors, the satellite trajectory within 5 hours is predicted, see Fig. 9 , Fig. 9 It is a schematic diagram of satellite five-hour trajectory prediction of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0097] Through the SGP4 orbital motion model, the simulation time selects the middle period of satellite motion, as shown in Table 3.

[0098] Table 3 Simulation time (March 11, 2022)

[0099] See also Fig.10 and Fig.11 , Fig.10is a schematic diagram of satellite trajectory simulation of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention, Fig.11 It is a schematic diagram of the actual trajectory of the satellite of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention. The method for verifying the accuracy of the satellite prediction results is to compare the predicted satellite orbit data with the actual orbit data. When comparing the prediction results and actual positions of all data, some commonalities and differences can be observed. The overall trend of the satellite motion trajectory is similar. In the time series, the change trend of the predicted position and the actual position is consistent, and both show similar motion paths. Although the overall trend of the satellite motion trajectory is similar, there are some deviations between the predicted position and the actual position. These deviations are mainly due to the calculation accuracy of the numerical model and the influence of environmental factors. In high latitudes (60°~90°), due to the influence of the earth's curvature, the error between the predicted position and the actual position is large, while in mid-latitudes (30°~60°), the error is small. Therefore, when evaluating the satellite motion trajectory, it is necessary to specially consider the influence of the North and South Poles to improve the accuracy of the prediction.

[0100] According to the simulation results, in order to analyze the accuracy of satellite comparison, the absolute error calculation and analysis of the satellite's sub-satellite position is performed. The results are as follows: Fig.12 As shown, Fig.12 It is a schematic diagram of the error comparison between the satellite simulated trajectory and the actual trajectory of the sub-satellite point of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention. First of all, according to the error results, it can be found that the sub-satellite point position error is within 0.5°, and the overall error of longitude and latitude is between 0.07° and 0.5°, which has a high accuracy for satellite orbit prediction. The overall error is within a relatively small range. Overall, the difference between the simulation prediction result and the actual result is acceptable. The error may increase or decrease over time. This is due to the rotation of the earth and the movement of the satellite. The deviation will show a changing trend, but the error is between 0.3° and above.

[0101] The accuracy of the satellite orbit depends mainly on the precision of the model and the data used. If the model can predict the satellite orbit within the error range of the decimal point level, its accuracy is high. Comparison with the actual results shows that the simulation results are very close to the actual results in most cases, proving the effectiveness of the SGP4 prediction model.

[0102] In summary, this set of comparison results demonstrates the accuracy and reliability of the satellite orbit prediction simulation model, which can further demonstrate its efficiency and usability in the implementation of sensor field of view simulation.

[0103] Then comes the satellite field of view simulation and result analysis. The GF-5B satellite sensor POSP observation field of view simulation is based on the actual technical specifications and status parameters of POSP. By simulating the observation angle of POSP, the instantaneous coverage is calculated to determine the ocean area that the satellite can capture, and the actual position (lat, lon) corresponding to each pixel in the coverage is calculated. The POSP sensor adopts a simultaneous polarization measurement scheme combining aperture and amplitude, and obtains wide-width remote sensing images through cross-track scanning. Its specifications are shown in Table 4, which is the POSP sensor parameter table.

[0104] Table 4 POSP sensor parameters

[0105] See also Fig.13 , Fig.13 This is a schematic diagram of the sensor field of view simulation of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention. The sensor field of view simulation is implemented based on the triangle vector method. Based on the principle of this method, it is implemented by writing an algorithm. For different situations, appropriate adjustments and optimizations are required according to target requirements and data accuracy. The epoch time that needs to be entered in the program is set to 11 Mar 2022 00:54:00.000, and the satellite sensor POSP half field of view angle is set to 50°. The corresponding time for GF-5B is 00:54:00.000 to 01:44:00.000. The sensor field of view simulation diagram results are as follows Fig.13 shown.

[0106] See also Fig.14 , Fig.14 FIG. 1 is a schematic diagram of the satellite field of view simulation boundary of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention. The boundary result of the earth observation coverage range is as follows: Fig.14 As shown, the blue dots are simulated boundaries and the red dots are actual boundaries. In the simulated boundary data, the latitude and longitude boundary values ​​of the simulated data are usually larger than the boundary values ​​of the actual observed data. This indicates that the simulated data has a larger variation at the boundary, resulting in a larger deviation at the edge of the field of view, making the simulated boundary sparser than the actual observed boundary.

[0107] In general, combined with the actual field of view of the satellite, whether from the data analysis of the boundary points, the change trends of the simulation data and the actual observation data are consistent, and both increase or decrease with the increase of latitude or longitude. In mid-latitudes, the data is closer to consistency. The comparison of the latitude and longitude of the left and right boundaries of the satellite field of view simulation with the actual observation field of view shows a high degree of consistency, which is mainly reflected in the sparseness and change rate of the north and south poles of the boundary. However, the difference at the north and south poles is mainly based on the influence of the curvature of the earth. Because the satellite covers a large range of changes in the field of view boundaries at the North and South Poles, although the deviation of the observation angle is the same or small, the deviation at the intersection of the earth will be magnified.

[0108] See also Fig.15 , Fig.15 Figure 1 is a schematic diagram of the comparison of the left and right boundary errors of the field of view of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention. In order to specifically analyze the comparison results between the simulation and the actual data, the actual observation data of the POSP sensor is used for verification, and the errors of the boundary points of the satellite sensor are statistically analyzed. Fig.15 As shown. The data shows that the variation range of latitude and longitude errors is between 0.01 and 1.48, indicating that there are large variations in the error size at different time points or in satellite missions. The latitude error shows a trend of gradual decrease, while the longitude error shows certain fluctuations, without an obvious monotonic trend. There are differences between the latitude error and the longitude error. At certain time points, the latitude error is relatively small while the longitude error is relatively large, and vice versa. This difference reflects the influence of different parameters or factors during satellite operation. Although the data fluctuates, it shows a certain stability as a whole, indicating that the difference between the satellite field of view simulation and the actual observation is affected by certain control or stabilization mechanisms. In addition, some data points have large error values, which may represent abnormal conditions or system failures in special cases. These outliers may be due to the influence of the north and south polar regions. When the satellite observes a plane with curvature, the observation field at a large angle will cause greater errors.

[0109] In summary, based on the comparison between the simulation results and the actual observation results, it is shown that there is a position error between the satellite field of view simulation and the actual observation. Although there are error fluctuations and variation differences within a certain range, the overall comparison between the two shows the accuracy of the simulation results, which helps to improve the calculation accuracy of the observation geometry of different pixel positions within the satellite's observation field of view.

[0110] Finally, the prediction and result analysis of ocean flare events are presented. The flare angle is further calculated based on the satellite and solar observation geometry. Some of the results are shown in Table 5, which is a table of example results of flare angle prediction. Through the calculation of the flare angle, pixel matching is performed according to different pixel longitudes and latitudes to obtain the calculation results of the flare angle corresponding to each pixel, and specific data is extracted to visualize the calculation results of the flare angle. Some of the example results of the prediction are shown in Table 5, comparing the flare prediction results of the ocean observed by POSP with the actual observation results. Fig.16 and Fig.17 As shown, Fig.16 It is a schematic diagram of the distribution of simulated flare angle and actual flare angle of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention, Fig.17 It is a schematic diagram of satellite true color image comparison of the ocean flare event prediction method based on satellite orbit simulation provided by the present invention.

[0111] Table 5 Example results of flare angle prediction

[0112] Ocean flare can usually be observed under specific observation conditions. The flare angle is a parameter that describes the angle between the sun's rays and the horizontal plane. The smaller its value is, the smaller the angle between the sun's rays and the horizontal plane is, and the stronger the ocean flare is. According to known conditions, ocean flare can be observed when the ocean flare angle is less than 40°. Therefore, the locations where ocean flare has been observed can be determined by analyzing the flare angle data. From the results in the figure, it can be seen that the numerical range of the flare angle is mainly concentrated in the mid-latitude region, that is, the blue area. From the actual data, it can be seen that the range of the flare angle is at a relatively high level, between 0° and 115°; the calculation formula for the overlap rate between the simulated flare distribution area and the actual flare distribution area is as follows (used to calculate the accuracy of the simulated flare distribution area): represents the overlap ratio, is the area of ​​the overlapping region, is the area of ​​the simulated flare region, is the area of ​​the actual flare region.

[0113] The overlap rate between the simulated flare distribution area and the actual flare distribution area is 94.53%, which shows that there is a high degree of similarity between the two. In addition, the larger the flare angle, the larger the angle between the reflected light on the ocean surface and the observation direction, which means that the ocean flare is weaker. For example, ocean flares cannot be observed at the North and South Poles. This view is confirmed by comparing the true color images observed by satellites. Fig.17 As shown, a very obvious ocean flare area can be observed in the middle.

[0114] Secondly, when the ocean flare angle is less than 40°, a concentrated distribution area of ​​ocean flares can be observed. The calculation results show that the flare angle distribution gradually weakens at the edge, which indicates that the ocean flare at the concentrated location is more obvious, while the flare at other locations is weaker or not obvious. Further analysis of the result data shows that the flare angle value changes with longitude and latitude, which reflects the differences in the optical properties and reflection conditions of the ocean surface at different locations.

[0115] The ocean flare event prediction device based on satellite orbit simulation provided by the present invention is described below. The ocean flare event prediction device based on satellite orbit simulation described below and the ocean flare event prediction method based on satellite orbit simulation described above can be referenced to each other.

[0116] The ocean flare event prediction device based on satellite orbit simulation provided by the present invention comprises an acquisition module 1801, an orbit parameter calculation module 1802, a coverage field calculation module 1803, a flare angle calculation module 1804 and a result output module 1805, wherein the acquisition module 1801 is used to respectively acquire the initial state parameters of the satellite and the sensor, and two rows of orbit element data of the satellite; the orbit parameter calculation module 1802 is used to input the two rows of orbit element data into the satellite orbit prediction model to perform orbit parameter calculation, and obtain the instantaneous orbit parameters of the satellite; the coverage field calculation module 1803 is used to obtain the initial state parameters of the satellite and the sensor, and the two rows of orbit element data of the satellite; the orbit parameter calculation module 1804 is used to obtain the instantaneous orbit parameters of the satellite; the coverage field calculation module 1805 is used to obtain the initial state parameters of the satellite and the sensor, and the two rows of orbit element data of the satellite; the orbit parameter calculation module 1802 is used to obtain the instantaneous orbit parameters of the satellite; the coverage field calculation module 1803 is used to obtain the instantaneous orbit parameters of the satellite; the coverage field calculation module 1804 is used to obtain the instantaneous orbit parameters of the satellite; the coverage field calculation module 1805 ... 803 is used to construct an initial observation vector in the sensor coordinate system based on the initial state parameters of the sensor, and to calculate the coverage field of view based on the instantaneous orbit parameters and the initial observation vector to obtain the instantaneous coverage field of view of the sensor; the flare angle calculation module 1804 is used to preprocess the instantaneous coverage field of view, and to calculate the flare angle of the preprocessed instantaneous coverage field of view to obtain the corresponding instantaneous flare angle; the result output module 1805 is used to take the set of instantaneous coverage fields corresponding to the instantaneous flare angles that meet the preset conditions as the ocean flare area and perform visual output.

[0117] Specifically, the above-mentioned ocean flare event prediction device based on satellite orbit simulation provided by the present invention can implement all the method steps implemented by the above-mentioned ocean flare event prediction method embodiment based on satellite orbit simulation, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as the method embodiment will not be described in detail here.

[0118] Fig.19 An example of a physical structure diagram of an electronic device is shown in FIG. Fig.19As shown, the electronic device may include: a processor (processor) 1910 , a communication interface (Communications Interface) 1920 , a memory (memory) 1930 and a communication bus 1940 , wherein the processor 1910 , the communication interface 1920 , and the memory 1930 communicate with each other via the communication bus 1940 . Processor 1910 can call the logic instructions in memory 1930 to execute an ocean flare event prediction method based on satellite orbit simulation, the method including: respectively obtaining the initial state parameters of the satellite and the sensor, and two lines of orbital element data of the satellite; inputting the two lines of orbital element data into the satellite orbit prediction model to calculate the orbital parameters to obtain the instantaneous orbital parameters of the satellite; constructing an initial observation vector in the sensor coordinate system based on the initial state parameters of the sensor, and performing coverage field calculation based on the instantaneous orbital parameters and the initial observation vector to obtain the instantaneous coverage field of view of the sensor; preprocessing the instantaneous coverage field of view, and performing flare angle calculation on the preprocessed instantaneous coverage field of view to obtain the corresponding instantaneous flare angle; taking the set of instantaneous coverage fields corresponding to the instantaneous flare angles that meet preset conditions as the ocean flare area and outputting them visually.

[0119] In addition, the logic instructions in the above-mentioned memory 1930 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0120] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the ocean flare event prediction method based on satellite orbit simulation provided by the above methods, the method including: respectively obtaining the initial state parameters of the satellite and the sensor, and two rows of orbital element data of the satellite; inputting the two rows of orbital element data into a satellite orbit prediction model to calculate the orbital parameters, and obtain the instantaneous orbital parameters of the satellite; constructing an initial observation vector in a sensor coordinate system based on the initial state parameters of the sensor, and performing coverage field calculation based on the instantaneous orbital parameters and the initial observation vector to obtain the instantaneous coverage field of view of the sensor; preprocessing the instantaneous coverage field of view, and performing flare angle calculation on the preprocessed instantaneous coverage field of view to obtain the corresponding instantaneous flare angle; taking the set of instantaneous coverage fields corresponding to the instantaneous flare angles that meet preset conditions as the ocean flare area and outputting them visually.

[0121] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the ocean flare event prediction method based on satellite orbit simulation provided by the above-mentioned methods, the method comprising: respectively obtaining the initial state parameters of the satellite and the sensor, and two rows of orbital element data of the satellite; inputting the two rows of orbital element data into a satellite orbit prediction model to perform orbital parameter calculations to obtain instantaneous orbital parameters of the satellite; constructing an initial observation vector in a sensor coordinate system based on the initial state parameters of the sensor, and performing coverage field calculation based on the instantaneous orbital parameters and the initial observation vector to obtain the instantaneous coverage field of view of the sensor; preprocessing the instantaneous coverage field of view, and performing flare angle calculation on the preprocessed instantaneous coverage field of view to obtain the corresponding instantaneous flare angle; taking the set of instantaneous coverage fields corresponding to the instantaneous flare angles that meet preset conditions as the ocean flare area and outputting them visually.

[0122] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative effort.

[0123] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0124] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting ocean flare events based on satellite orbit simulation, characterized in that: include: Respectively obtaining initial state parameters of the satellite and the sensor, and two rows of orbital element data of the satellite; Inputting the two rows of orbital element data into a satellite orbit prediction model to calculate orbital parameters, thereby obtaining instantaneous orbital parameters of the satellite; An initial observation vector in a sensor coordinate system is constructed based on the initial state parameters of the sensor, and a coverage field calculation is performed based on the instantaneous orbit parameters and the initial observation vector to obtain an instantaneous coverage field of the sensor; Preprocessing the instantaneous covered field of view, and calculating the flare angle of the preprocessed instantaneous covered field of view to obtain a corresponding instantaneous flare angle; The set of instantaneous coverage fields corresponding to the instantaneous flare angles that meet preset conditions is taken as the ocean flare area and is visualized and output.

2. The method for predicting ocean flare events based on satellite orbit simulation according to claim 1, characterized in that: The satellite orbit prediction model includes a simplified conventional perturbation model, and the two rows of orbit element data are input into the satellite orbit prediction model to calculate orbit parameters to obtain the instantaneous orbit parameters of the satellite, including: Decoding the two lines of orbital element data to obtain six orbital element numbers of the satellite; The simplified conventional perturbation model is called to calculate the instantaneous position data of the satellite based on the six orbital elements, and the instantaneous position data is used as the instantaneous orbital parameters.

3. The method for predicting ocean flare events based on satellite orbit simulation according to claim 1, characterized in that: The calculating the coverage field of view based on the instantaneous orbit parameter and the initial observation vector to obtain the instantaneous coverage field of view of the sensor includes: Performing coordinate system conversion processing on the initial observation vector in the sensor coordinate system to obtain a target observation vector in the earth coordinate system; The coordinates corresponding to each pixel of the sensor are calculated based on the target observation vector and the instantaneous orbit parameter, and the set of coordinates corresponding to all the pixels is used as the instantaneous coverage field of view of the sensor.

4. The method for predicting ocean flare events based on satellite orbit simulation according to claim 3 is characterized in that: The initial state parameters of the sensor include the inclination angle of the sensor, the instantaneous orbit parameters include the orbit inclination angle, the right ascension of the ascending node, the argument of perigee and the true anomaly of the satellite, and the coordinate system conversion processing is performed on the initial observation vector in the sensor coordinate system to obtain the target observation vector in the geodetic coordinate system, including: Constructing a first conversion matrix based on the sensor tilt angle, and performing a coordinate system conversion on the initial observation vector in the sensor coordinate system based on the first conversion matrix to obtain a first observation vector in the satellite body coordinate system; Constructing a second transformation matrix based on the Euler angles between the satellite body coordinate system and the satellite orbit coordinate system, and performing a coordinate system transformation on the first observation vector in the satellite body coordinate system based on the second transformation matrix to obtain a second observation vector in the satellite orbit coordinate system; Constructing a third transformation matrix based on the orbital inclination, the right ascension of the ascending node, the argument of perigee, and the true anomaly of the satellite, and performing a coordinate system transformation on the second observation vector in the satellite orbit coordinate system based on the third transformation matrix to obtain a third observation vector in the geocentric inertial coordinate system; Calculate the earth rotation matrix based on Greenwich sidereal time, calculate the precession matrix based on the Julian day corresponding to the universal time and the current running time, and construct a fourth conversion matrix based on the earth rotation matrix and the precession matrix; Performing a coordinate system transformation on the third observation vector in the geocentric inertial coordinate system based on the fourth transformation matrix to obtain a fourth observation vector in the geocentric fixed coordinate system; The fourth observation vector in the geocentric fixed coordinate system is subjected to a coordinate system transformation to obtain a target observation vector in the geodetic coordinate system.

5. The method for predicting ocean flare events based on satellite orbit simulation according to claim 1, characterized in that: The preprocessing of the instantaneous coverage field of view includes: The ocean area recognition model is called to filter the land area in the instantaneous covered field of view to obtain an ocean area, and the ocean area is used as the preprocessed instantaneous covered field of view.

6. The method for predicting ocean flare events based on satellite orbit simulation according to claim 1, characterized in that: The flare angle calculation is performed on the preprocessed instantaneous coverage field of view to obtain the corresponding instantaneous flare angle, including: Performing numerical calculation of observation geometry on the instantaneous coverage field after preprocessing to obtain the solar zenith angle, the solar azimuth angle, the observation zenith angle and the observation azimuth angle; The instantaneous flare angle is calculated based on the solar zenith angle, the solar azimuth angle, the observation zenith angle and the observation azimuth angle.

7. The method for predicting ocean flare events based on satellite orbit simulation according to claim 1, characterized in that: The initial state parameters of the satellite include the inclination angle, orbital altitude and current operating time of the satellite; the initial state parameters of the sensor include the field of view angle of the sensor and the geometric shape of the field of view of the sensor.

8. A device for predicting ocean flare events based on satellite orbit simulation, characterized in that: include: An acquisition module, used to respectively acquire initial state parameters of the satellite and the sensor, and two rows of orbital element data of the satellite; An orbit parameter calculation module, used for inputting the two rows of orbit element data into a satellite orbit prediction model to calculate orbit parameters, and obtain instantaneous orbit parameters of the satellite; A coverage field calculation module, used to construct an initial observation vector in a sensor coordinate system based on the initial state parameters of the sensor, and perform coverage field calculation based on the instantaneous orbit parameters and the initial observation vector to obtain the instantaneous coverage field of the sensor; A flare angle calculation module, used to preprocess the instantaneous covered field of view, and perform flare angle calculation on the preprocessed instantaneous covered field of view to obtain a corresponding instantaneous flare angle; The result output module is used to take the set of instantaneous coverage fields corresponding to the instantaneous flare angles that meet preset conditions as the ocean flare area and output it visually.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the method for predicting ocean flare events based on satellite orbit simulation as described in any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the method for predicting ocean flare events based on satellite orbit simulation as described in any one of claims 1 to 7.

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