Satellite simulation motion planning method based on unmanned aerial vehicle platform

Abstract

The invention provides a satellite simulation motion planning method based on an unmanned aerial vehicle platform. The satellite simulation motion planning method comprises the steps of calculating an azimuth angle and a pitch angle of a satellite under a ground observation station coordinate system; the azimuth angles and pitch angles of the unmanned aerial vehicle and the satellite relative to the ground observation station are consistent, the fixed flight height of the unmanned aerial vehicle is calculated according to the maximum flight speed constraint of the unmanned aerial vehicle based on the projection relation of the unmanned aerial vehicle and the satellite under the ground observation station coordinate system, and the position information of the unmanned aerial vehicle under the ground observation station coordinate system is obtained; calculating flight path parameters of the unmanned aerial vehicle according to coordinate conversion; and calculating a homogeneous rotation matrix from the unmanned aerial vehicle body coordinate system to the ground observation station coordinate system, and calculating the unmanned aerial vehicle platform load direction based on the principle that the unmanned aerial vehicle load direction is consistent with the satellite load direction. According to the invention, orbital motion of a satellite platform can be simulated, motion of a satellite load can be simulated, and requirements of a satellite simulation training task can be effectively met; the speed overload condition of the unmanned aerial vehicle can be avoided, and effective simulation of the unmanned aerial vehicle to the satellite platform is realized.

Description

Technical Field

[0001] The invention belongs to the technical field of satellite simulation, and in particular relates to a satellite simulation motion planning method based on an unmanned aerial vehicle platform. Background Art

[0002] With the development of the aerospace industry, the number and types of satellites in orbit have gradually increased, which has put forward new requirements for aerospace operation and maintenance, satellite data application, etc., and it is urgent to carry out relevant training to improve the actual effectiveness of satellites. However, due to the characteristics of complex technology, high value, limited number, and limited transit time, major international impact, and high security risks, satellites in orbit are not suitable as training targets. Therefore, satellite simulation training has become an important means to solve this problem.

[0003] Satellite simulation training is to simulate satellites on the ground using satellite simulation platforms equipped with simulated payloads. Satellite simulation training based on UAV platforms is to use UAVs to simulate satellite platforms, and by carrying different payloads, conduct relevant training near the ground to achieve equivalent simulation of satellites. Satellite simulation payloads carried on UAV platforms are not limited by time, and are flexible, low-cost, and easy to use and maintain. By using satellite simulation systems and rationally planning the flight trajectory of UAVs and payload movements, a realistic training environment can be created in the training field, and it also has a significant driving effect on satellite data applications, satellite measurement, control, and maintenance, etc.

[0004] The Chinese patent application number 202210493570.3 proposes a method and system for simulating satellite transit by a UAV. The method proposes that the UAV fly at a fixed altitude h, and based on the consistency between the fixed altitude of the UAV and the satellite azimuth A and pitch angle E, the station system coordinates (A, E, h / sin(E)) of the UAV relative to the ground tracking and control station are obtained. Then, the longitude, latitude, and altitude data of the UAV's route are calculated through coordinate conversion and injected into the UAV to complete the simulation of the satellite track.

[0005] This method has two problems. On the one hand, although the motion planning of the UAV platform is proposed, in actual applications, UAVs must carry corresponding mission payloads. If the motion planning of the payload is not carried out, and only the platform motion is simulated, the application scenarios are very limited; and there will be a situation where the UAV platform payload pointing is far away from the satellite payload pointing, which is difficult to meet the mission requirements. On the other hand, this method does not consider the maximum speed constraint of the UAV platform, and there may be a speed overload of the UAV. Summary of the invention

[0006] The purpose of the present invention is to solve the problem that the satellite simulation training based on the UAV platform in the prior art does not take into account the load simulation requirements and the maximum speed constraints of the UAV platform, and to provide a satellite simulation motion planning method based on the UAV platform.

[0007] To achieve the above purpose, the technical solution provided by the present invention is:

[0008] A satellite simulation motion planning method based on an unmanned aerial vehicle platform is provided, comprising the following steps:

[0009] Step 1, according to the geodetic coordinates of the ground station and the double-row roots of the satellite, calculate the azimuth and elevation angle of the satellite in the effective simulation arc in the ground station coordinate system;

[0010] Step 2: The azimuth and pitch angles of the UAV and the satellite relative to the ground station are consistent. Based on the projection relationship between the UAV and its projection in the ground station coordinate system and the maximum flight speed constraint of the UAV, the fixed flight altitude of the UAV is calculated, and the position information of the UAV in the ground station coordinate system is obtained according to the projection relationship;

[0011] Step 3, based on the obtained position information of the UAV at the ground station, calculate the track parameters of the UAV according to coordinate conversion, and the track parameters include flight longitude, latitude and altitude;

[0012] Step 4: Calculate the homogeneous rotation matrix from the UAV body coordinate system to the ground station coordinate system based on the mutual homogeneous transformation matrices between the UAV body coordinate system, the inertial coordinate system and the ground station coordinate system. Calculate the UAV platform load pointing direction based on the calculated homogeneous rotation matrix and the principle that the UAV load pointing direction is consistent with the satellite load pointing direction.

[0013] Furthermore, in step 1, according to the constraint relationship between the antenna motion range of the ground station and the minimum working elevation angle, the satellite simulation arc is determined by integrating the calculation results of the azimuth and elevation angle of the satellite relative to the ground station.

[0014] Furthermore, step 2 includes:

[0015] Step 2.1, calculate the projection relationship between the drone and its projection in the ground station coordinate system:

[0016] d=h·cot E

[0017] d 2x =d·sin A

[0018] d 2y =d·cosA

[0019] Where A is the azimuth, E is the pitch angle, h is the flight altitude of the drone, and d is the vertical position of the drone to the measuring station XO. 1 The distance from the projection point on the Y plane to the ground station, d 2x For d in O 1 Projection in the X direction, d 2y For d in O 1 Projection in the Y direction;

[0020] Step 2.2, calculate the fixed flight altitude of the drone according to the maximum flight speed constraint of the drone:

[0021] v 2 ≤v 2max

[0022]

[0023] In the formula, v 2 is the flight speed of the drone, v 2max is the maximum flight speed of the UAV, A' is the derivative of the azimuth angle, and E' is the derivative of the pitch angle;

[0024] Step 2.3, calculate the coordinates of the drone at the ground station based on the projection relationship:

[0025]

[0026] Furthermore, in step 2.2, the flight speed of the drone v 2 Calculated by the following formula:

[0027]

[0028] v 2x =d(d 2x ) / dt=d(h·cot E·sin A) / dt=h[(-1 / sin 2 E)E'·(sin A)+cot E·cos A·A']

[0029] v 2y =d(d 2y ) / dt=d(h·cot E·cos A) / dt=h·[(-1 / sin 2 E)·E'·cos A+cot E(-sin A)·A']

[0030] v 2z =0

[0031] In the formula, v 2x 、v 2y and v 2z The drone is in O 1 X, O1 Y and O 1 The velocity component in the Z direction.

[0032] Further, step 3 includes:

[0033] Step 3.1: Set the geodetic coordinates (lat 1 ,lon 1 ,alt 1 ) is converted to geocentric coordinates (x 1 ,y 1 ,z 1 ):

[0034]

[0035] Where a and b are the lengths of the Earth's major and minor axes, respectively, and e is the first eccentricity of the Earth's ellipsoid;

[0036] Step 3.2: The coordinates of the drone at the ground station (x 21 ,y 21 ,z 21 ) to geocentric coordinates (x, y, z):

[0037]

[0038] Step 3.3, convert the drone's geocentric coordinates (x, y, z) to geodetic coordinates (lat, lon, alt):

[0039]

[0040] Further, step 4 includes:

[0041] Step 4.1, calculate the mutual homogeneous transformation matrix between the drone body coordinate system, the inertial coordinate system and the ground station coordinate system, including the following sub-steps:

[0042] Step 4.1.1, calculate the homogeneous transformation matrix R from the drone body coordinate system to the drone inertial coordinate system 2'2 :

[0043]

[0044] Where ψ is the rotation angle of the drone around the Z axis of the inertial coordinate system;

[0045] Step 4.1.2, calculate the homogeneous transformation matrix R from the UAV inertial coordinate system to the ground station coordinate system 21 :

[0046]

[0047] Step 4.2, calculating the UAV platform load pointing, includes the following sub-steps:

[0048] Step 4.2.1, calculate the coordinates of a ground point P in the coordinate system of the drone, including:

[0049] Step 4.2.1.1, calculate the homogeneous rotation matrix from the drone body coordinate system to the ground station coordinate system

[0051] R 2'1 =R 2'2 ×R 21

[0052] Step 4.2.1.2, calculate the homogeneous transformation matrix R of the ground station coordinate system relative to the drone body coordinate system 12' :

[0053] R 12' =R 2'1 -1

[0054] Step 4.2.1.3, calculate the coordinates of point P in the drone body coordinate system (Px 2' ,Py 2' ,Pz 2' ):

[0055]

[0056] Where (Px, Py, Pz) is the coordinate of point P in the ground station coordinate system;

[0057] Step 4.2.2, calculate the direction of the drone load, that is, the vector direction from the origin of the drone body coordinate system to point P:

[0058] Further, step 4.1.1 includes:

[0059] Step 4.1.1.1, calculate the rotation matrices Rx, Ry and Rz of the drone around the X-axis, Y-axis and Z-axis of the inertial coordinate system respectively:

[0060]

[0061] Where θ is the rotation angle of the drone around the X-axis of the inertial coordinate system, The angle of rotation of the drone around the Y axis of the inertial coordinate system;

[0062] Step 4.1.1.2, calculate the rotation matrix R from the body coordinate system to the inertial coordinate system 2'2 :

[0063]

[0064] Step 4.1.1.3, set θ = 0 and Substituting into the above formula, we get the following homogeneous transformation matrix R 2'2 :

[0065]

[0066] Furthermore, in step 4.1.1, the angle ψ of the drone's rotation around the Z axis of the inertial coordinate system is calculated as follows:

[0067] tanψ=v 2x / v 2y .

[0068] The advantages of the present invention are:

[0069] 1. The satellite simulation motion planning method based on the UAV platform of the present invention, when using the UAV platform to simulate the motion of the satellite platform, the UAV is in real time on the connection line between the ground station and the satellite, the flight trajectory of the UAV is closer to the actual trajectory of the satellite, and the satellite payload pointing is also taken into account during the simulation to ensure that the actual pointing of the UAV platform payload antenna is consistent with the satellite payload pointing. Therefore, it can simulate the orbital motion of the satellite platform and the motion of the satellite payload, and can effectively meet the requirements of satellite simulation training tasks.

[0070] 2. The present invention also determines the fixed flight altitude of the UAV according to the maximum speed constraint of the UAV flight, and innovatively designs a UAV platform motion calculation method based on motion constraints, which can avoid the speed overload of the UAV and realize the effective simulation of the UAV to the satellite platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] The above and / or other features and advantages of the present invention will become more easily understood through the following description with reference to the accompanying drawings, which are not drawn to scale and some features are exaggerated or reduced to show details of specific components. In the accompanying drawings:

[0072] Figure 1 It is a flow chart of the satellite simulation motion planning method based on the unmanned aerial vehicle platform of the present invention;

[0073] Figure 2 It is a schematic diagram of the UAV motion simulation effect in the present invention;

[0074] Figure 3 It is a schematic diagram of the overall coordinate system in the present invention;

[0075] Figure 4 It is a schematic diagram of the calculation relationship of the UAV in the ground station coordinate system of the present invention;

[0076] Figure 5It is a schematic diagram of calculating the rotation angle of the drone around the Z axis of the inertial coordinate system in the present invention;

[0077] Figure 6 It is a schematic diagram of homogeneous transformation matrix calculation in the present invention;

[0078] Figure 7 It is a schematic diagram of load pointing calculation in the present invention;

[0079] FIG8(A) is a schematic diagram of the relative azimuth change of the satellite and the ground station in an example of the present invention;

[0080] FIG8(B) is a schematic diagram of the relative elevation angle variation of the satellite and the ground station in an example of the present invention;

[0081] FIG8(C) is a schematic diagram showing the change in the relative distance between the satellite and the ground station in an example of the present invention;

[0082] Fig. 9 is a flight altitude constraint curve diagram planned within the maneuverability range of the UAV in the example of the present invention;

[0083] Fig.10 is a track diagram of the UAV in the ground station coordinate system obtained in the example of the present invention;

[0084] Fig.11 is the geodetic coordinate track map of the UAV obtained in the example of the present invention;

[0085] Fig.12 is a coordinate diagram of the ground station obtained in the example of the present invention in the coordinate system of the drone body;

[0086] Fig.13 It is a schematic diagram of the UAV payload pointing obtained in the example of the present invention. DETAILED DESCRIPTION

[0087] The present invention will be described in detail below with reference to the accompanying drawings by means of exemplary embodiments of the present invention. It should be noted that the following detailed description of the present invention is only for the purpose of illustration, and is not intended to limit the present invention.

[0088] The present invention provides a satellite simulation motion planning method based on an unmanned aerial vehicle platform, which regards the unmanned aerial vehicle platform and the payload as independent rigid bodies, and realizes precise control of the motion of the unmanned aerial vehicle platform and the payload through key steps such as building a coordinate system, converting motion relationships, and generating motion parameters of a satellite simulation training system.

[0089] Reference Figure 1 , as an exemplary embodiment of the present invention, a satellite simulation motion planning method based on an unmanned aerial vehicle platform includes:

[0090] Step S1, calculating the azimuth and elevation angle of the satellite in the effective simulation arc in the ground station coordinate system according to the geodetic coordinates of the ground station and the double-row roots of the satellite;

[0091] Step S2, the azimuth and pitch angles of the UAV and the satellite relative to the ground station are consistent, based on the projection relationship between the UAV and its projection in the ground station coordinate system, according to the maximum flight speed constraint of the UAV, the fixed flight altitude of the UAV is calculated, and the position information of the UAV in the ground station coordinate system is obtained according to the projection relationship;

[0092] Step S3, based on the obtained position information of the UAV at the ground station, according to coordinate conversion, the track parameters of the UAV are calculated, and the track parameters include flight longitude, latitude and altitude;

[0093] Step S4, according to the mutual homogeneous transformation matrices between the drone body coordinate system, the inertial coordinate system and the ground station coordinate system, calculate the homogeneous rotation matrix from the drone body coordinate system to the ground station coordinate system, and calculate the drone platform load pointing based on the calculated homogeneous rotation matrix and the principle that the drone load pointing is consistent with the satellite load pointing.

[0094] The motion simulation effect schematic diagram of the present invention is as follows Figure 2 As shown in the figure, on the basis of considering the simulation of satellite motion by the UAV platform, the simulation of the motion direction of the satellite payload is also planned, so that the satellite, UAV platform and ground station can be kept in a straight line, and the position of the satellite payload pointing to the ground is consistent with the position of the UAV payload pointing to the ground.

[0095] like Figure 3 As shown, in order to make the description of the present invention more intuitive, a coordinate system is established according to the following principles.

[0096] ① Ground station coordinate system: It is established according to the ENU coordinate system (East, North, Up) rules. It takes the ground tracking station as the origin, the east direction as the X axis, the Y axis pointing to the north, and the vertical ground upward as the Z axis. Figure 2 Medium 1 -XYZ.

[0097] The UAV platform coordinate system includes the UAV platform body coordinate system and the UAV platform inertial coordinate system.

[0098] ② UAV platform body coordinate system: It is the right front upper coordinate system, that is, the center of the UAV is the origin, the X axis is perpendicular to the main symmetry plane of the aircraft and points to the right, the Y axis is consistent with the longitudinal axis of the aircraft and points to the nose, and the Z axis meets the right-hand rule, such as Figure 2 Medium 2 -X 2' Y 2' Z 2' .

[0099] ③ UAV platform inertial coordinate system: It is established according to the ENU coordinate system rules, with the center of mass of the UAV as the origin, the east direction as the X-axis, the Y-axis pointing to the north, and the vertical ground upward as the Z-axis, such as Figure 2 Medium 2 -XYZ.

[0100] Since the distance between the UAV platform and the UAV payload is negligible compared to the distance between the UAV and the ground, the actual direction of the UAV payload can be regarded as a vector pointing to the ground target with the UAV platform coordinate system as the origin.

[0101] In step S1, the geodetic coordinates of the ground control station are known to be P 1 (lat 1 ,lon 1 ,alt 1 ), the double-row element of the simulated satellite is selected as TLE, and the method of calculating the satellite azimuth, pitch and distance based on the double-row element is a mature algorithm, with f(P 1 , TLE), then the azimuth and elevation angles of the satellite relative to the ground tracking and control station are:

[0102] (A,E)=f(P 1 ,TLE) (1)

[0103] Based on the principle of equivalent simulation, the azimuth and pitch angles of the UAV platform relative to the ground station are the same as the azimuth and pitch angles of the satellite relative to the ground station.

[0104] According to the constraint relationship between the antenna motion range of the ground station and the minimum working elevation angle, the satellite simulation arc is determined by integrating the calculation results of the azimuth and elevation angle of the satellite relative to the ground station.

[0105] For step S2, the method selects the satellite and the UAV to have the same azimuth and pitch angle relative to the ground station, and the UAV's flight altitude relative to the ground remains unchanged. Considering the movement capabilities of the UAV and the UAV payload, it is necessary to determine the relative distance between the UAV's route plane and the ground station. In this regard, Figure 4 As shown, step S2 includes: step S2.1, calculating the projection relationship between the UAV and its projection in the ground station coordinate system:

[0106] d=h·cotE (2)

[0107] d 2x =d·sinA (3)

[0108] d 2y =d·cosA (4)

[0109] Where A is the azimuth, E is the pitch angle, h is the flight altitude of the UAV, and d is the vertical position of the UAV to the measuring station XO. 1 The distance from the projection point on the Y plane to the ground station, d 2x For d in O 1 Projection in the X direction, d 2y For d in O 1 Projection in the Y direction.

[0110] Step S2 also includes step S2.2: calculating the fixed flight altitude of the drone according to the maximum flight speed constraint of the drone:

[0111] v 2 ≤v 2max (5)

[0112]

[0113] In the formula, v 2 is the flight speed of the drone, v 2max is the maximum flight speed of the UAV, A' is the derivative of the azimuth angle, which can be considered as the rate of change of the azimuth angle with time, and E' is the derivative of the pitch angle, which can be considered as the rate of change of the pitch angle with time.

[0114] Step S2 also includes: Step S2.3, calculating the coordinates (x 21 ,y 21 ,z 21 ):

[0115]

[0116] Furthermore, the flight speed of the drone v 2 It can be calculated by the following formula:

[0117]

[0118] v 2x =d(d 2x ) / dt=d(h·cot E·sin A) / dt=h·[(-1 / sin 2 E)·E'·(sin A)+cotE·cos A·A'] (9)

[0119] v 2y =d(d 2y ) / dt=d(h·cot E·cos A) / dt=h·[(-1 / sin 2 E)·E'·cos A+cot E(-sinA)·A'] (10)

[0120] v 2z=0 (11)

[0121] In the formula, v 2x 、v 2y and v 2z The drone is in O 1 X, O 1 Y and O 1 The velocity component in the Z direction.

[0122] After step S2 is completed, the coordinates of the drone in the ground station coordinate system are obtained. Since the drone track is generally in the coordinate form of the geodetic system, it is necessary to convert ENU to LLA (Latitude, Longitude, Altitude). Therefore, step S3 includes:

[0123] Step S3.1: The geodetic coordinates (lat 1 ,lon 1 ,alt 1 ) is converted to geocentric coordinates (x 1 ,y 1 ,z 1 ):

[0124]

[0125] Where a and b are the lengths of the Earth's major and minor axes, respectively, and e is the first eccentricity of the Earth's ellipsoid;

[0126] Step S3.2: The coordinates of the UAV at the ground station (x 21 ,y 21 ,z 21 ) is converted to geocentric coordinates (x, y, z). Since the ground station coordinate system is the northeast celestial coordinate system, therefore:

[0127]

[0128]

[0129] Step S3.3, convert the UAV's geocentric coordinates (x, y, z) to geodetic coordinates (lat, lon, alt):

[0130]

[0131] Next, step S4 includes: step S4.1, calculating the mutual homogeneous transformation matrix between the drone body coordinate system, the inertial coordinate system and the ground station coordinate system; and step S4.2, calculating the drone platform load orientation.

[0132] Preferably, step S4.1 includes: step S4.1.1, calculating the homogeneous transformation matrix R from the drone body coordinate system to the drone inertial coordinate system 2'2 Generally speaking, the azimuth, pitch and roll angles of the drone relative to the inertial coordinate system are used to calculate the Get the rotation matrix R from the drone body coordinate system to the drone inertial system 2'2 .

[0133]

[0134] Where ψ is the rotation angle of the drone around the Z axis of the inertial coordinate system.

[0135] Optionally, in step S4.1.1, according to the calculation rule of the rotation matrix, the UAV rotates around the X-axis of the inertial coordinate system by an angle θ, and the calculation method of the rotation matrix is ​​shown in Rx, and the rotation angle around the Y-axis of the inertial coordinate system is The calculation method of its rotation matrix is ​​shown in Ry, and the rotation matrix is ​​calculated by the angle ψ around the Z axis of the inertial coordinate system as shown in Rz:

[0136]

[0137] The rotation order is external rotation YXZ, that is, rotation around the inertial coordinate system, R 2'2 Represents the rotation matrix from the body coordinate system to the inertial coordinate system:

[0138]

[0139] Since the drone flies at a fixed altitude in the present invention, the drone attitude change caused by air disturbance is not considered, so the drone pitch angle θ = 0, and the roll angle

[0140] According to the definition rule of homogeneous transformation matrix, the translation vector between the drone inertial coordinate system and the body coordinate system is [0,0,0]. Substituting into the above formula, we get the following homogeneous transformation matrix R 2'2 :

[0141]

[0142] like Figure 5 As shown, in a specific embodiment of the present invention, the angle ψ of the drone rotating around the Z axis of the inertial coordinate system is calculated by the following formula:

[0143] tanψ=v 2x / v 2y (twenty four)

[0144] Step S4.1 also includes: Step S4.1.2, calculating the homogeneous transformation matrix R from the drone inertial coordinate system to the ground station coordinate system 21 .like Figure 6 As shown, the origin of the drone inertial system is at the center of mass of the drone body, and the direction of the inertial coordinate system is consistent with the direction of the ground station coordinate system. Therefore, the homogeneous transformation matrix R from the drone inertial coordinate system to the ground station coordinate system is 21 for:

[0145]

[0146] In the formula, [x 21 y 21 z 21 ] is the origin of the UAV inertial coordinate system O 2 Coordinates in the ground station coordinate system.

[0147] Step S4.2 includes step S4.2.1: calculating the coordinates of a ground point P in the coordinate system of the drone, specifically including:

[0148] According to the calculation relationship of the homogeneous transformation matrix, the homogeneous rotation matrix R from the drone body coordinate system to the ground station coordinate system can be calculated 2'1 :

[0149] R 2'1 =R 2'2 ×R 21 (26)

[0150] Then calculate the homogeneous transformation matrix R of the ground station coordinate system relative to the drone body coordinate system 12' :

[0151] R 12' =R 2'1 -1 (27)

[0152] Assume that the UAV payload points to a point P on the ground when simulating the satellite payload. The coordinates of P in the ground station coordinate system are (Px, Py, Pz). According to the coordinate transformation relationship, the coordinates of point P in the UAV body coordinate system can be calculated (Px 2' ,Py 2' ,Pz 2' ):

[0153]

[0154] Step S4.2 also includes: Step S4.2.2, calculating the direction of the drone load. Figure 7The figure shows the projection diagram of point P in the coordinate system of the aircraft body. The load direction of the UAV is the vector direction from the origin O2 of the coordinate system of the UAV body to point P. According to the trigonometric calculation formula, it can be concluded that the load direction is related to Z 2’ The angle between the axes is With Z 2’ The angle between the axes is At this point, the present invention not only obtains the track parameters of the UAV platform, but also obtains the load pointing of the UAV platform.

[0155] Therefore, as described above, in the satellite simulation motion planning method based on the UAV platform of the present invention, when the UAV platform is used to simulate the motion of the satellite platform, the UAV is in real time on the line between the ground station and the satellite, and the flight trajectory of the UAV is closer to the actual trajectory of the satellite. The satellite payload pointing is also taken into account during the simulation to ensure that the actual pointing of the UAV platform payload antenna is consistent with the satellite payload pointing. Therefore, it can simulate the orbital motion of the satellite platform and the motion of the satellite payload, and can effectively meet the requirements of the satellite simulation training task. The present invention also determines the fixed flight altitude of the UAV according to the maximum speed constraint of the UAV flight, and innovatively designs the UAV platform motion calculation method based on motion constraints, which can avoid the speed overload of the UAV and realize the effective simulation of the satellite platform by the UAV.

[0156] Next, the satellite simulation motion planning method based on the UAV platform provided by the present invention is further illustrated by examples.

[0157] This example takes the International Space Station transit on June 4, 2024 as an example. The orbital TLE elements are:

[0159]

[0160] Firstly, the azimuth and elevation angles of the satellite platform relative to the ground station in the effective simulation arc are calculated.

[0161] The time period from 10:13 to 11:22 on June 5, 2024 is selected to calculate the azimuth and elevation angles. Since there is an over-the-top phenomenon in this example, in order to make the azimuth data smooth, the over-the-top data is processed by adding 360°. The changes in azimuth, elevation, and distance are shown in the figure below. Figure 8(A) to Figure 8(C) shown.

[0162] In this example, the minimum working elevation angle that meets the working requirements of the measuring station is 3°, and the arc segment with the ground station elevation angle range of 3°≤E≤9.3° is selected as the simulation arc segment.

[0163] Next, calculate the drone's flight altitude.

[0164] A medium-sized rotor UAV is selected as a sample, and the maximum flight speed constraint of the UAV is:

[0165] v 2 ≤34m / s

[0166] According to formula (11), the constraint condition of h is:

[0167]

[0168] For the convenience of calculation, like Fig. 9 As shown, the flight altitude constraint can be calculated to be h≤112.85m. The selected flight altitude is 110m.

[0169] Then, according to the azimuth angle A, pitch angle E and height h of the drone relative to the ground station, the position information of the drone is obtained according to the projection relationship:

[0170]

[0171] Substituting the calculated results of azimuth and pitch angle into the above formula, we can get the track diagram of the UAV in the ground station coordinate system (three-dimensional track and projected track on the ground) as follows: Fig.10 shown.

[0172] Then calculate the track in the geodetic coordinate system. Select the WGS2000 coordinate system, with the major semi-axis a = 6378137m, the minor semi-axis b = 6356752.314m, and the flattening e = 1 / 298.257222101.

[0173] Ground control station P 1 The conversion of geodetic coordinates (110°, 19°, 100m) to geocentric coordinates is (-2063400, 5669100, 2063400).

[0174] According to formula (15), the coordinates of the UAV track in the geocentric system can be obtained. According to formula (16), the ground tracking station P can be calculated. 1 The transformation matrix S between the ENU coordinate system and the LLA coordinate system.

[0175]

[0176] According to formulas (13) and (17), the latitude and longitude coordinates of the UAV track are calculated. Its track curve is as follows: Fig.11 shown.

[0177] Then the homogeneous transformation matrix between the UAV body coordinate system and the ground station coordinate system is calculated.

[0178] This example uses the case where the UAV payload always points to the ground station to illustrate the calculation process. The homogeneous transformation matrix of the UAV carrier coordinate system relative to the inertial system is:

[0179]

[0180] Calculate according to formulas (9), (10) and (23):

[0181]

[0182] The homogeneous transformation matrix from the drone inertial system to the ground station coordinate system is calculated as follows:

[0183]

[0184] Finally, calculate the UAV platform load direction:

[0185]

[0186] The coordinates of the ground station in the coordinate system of the drone:

[0187]

[0188] The position of the ground station in the coordinates of the drone is as follows Fig.12 The calculated load direction is shown as Fig.13 As shown, this example verifies the effectiveness of the satellite simulation motion planning method based on the UAV platform provided by the present invention.

[0189] Finally, it should be noted that the features mentioned and / or shown in the above description of the exemplary embodiments of the present invention may be combined in the same or similar manner into one or more other embodiments, combined with the features in other embodiments or substituted for the corresponding features in other implementations. The technical solutions obtained by these combinations or substitutions shall also be deemed to be included in the protection scope of the present invention.

Claims

1. A satellite simulation motion planning method based on an unmanned aerial vehicle platform, characterized in that: The following steps are involved: Step 1, according to the geodetic coordinates of the ground station and the double-row roots of the satellite, calculate the azimuth and elevation angle of the satellite in the effective simulation arc in the ground station coordinate system; Step 2: The azimuth and pitch angles of the UAV and the satellite relative to the ground station are consistent. Based on the projection relationship between the UAV and its projection in the ground station coordinate system and the maximum flight speed constraint of the UAV, the fixed flight altitude of the UAV is calculated, and the position information of the UAV in the ground station coordinate system is obtained according to the projection relationship; Step 3, based on the obtained position information of the UAV at the ground station, calculate the track parameters of the UAV according to coordinate conversion, and the track parameters include flight longitude, latitude and altitude; Step 4: Calculate the homogeneous rotation matrix from the UAV body coordinate system to the ground station coordinate system based on the mutual homogeneous transformation matrices between the UAV body coordinate system, the inertial coordinate system and the ground station coordinate system. Calculate the UAV platform load pointing direction based on the calculated homogeneous rotation matrix and the principle that the UAV load pointing direction is consistent with the satellite load pointing direction.

2. The satellite simulation motion planning method based on an unmanned aerial vehicle platform according to claim 1 is characterized in that: In step 1, according to the constraint relationship between the antenna motion range of the ground station and the minimum working elevation angle, the satellite simulation arc is determined by integrating the calculation results of the azimuth and elevation angle of the satellite relative to the ground station.

3. The satellite simulation motion planning method based on an unmanned aerial vehicle platform according to claim 2 is characterized in that: Step 2 includes: Step 2.1, calculate the projection relationship between the drone and its projection in the ground station coordinate system: d=hcotE d 2x =dsinA d 2y =dcosA Where A is the azimuth, E is the pitch angle, h is the flight altitude of the UAV, d is the distance from the projection point of the UAV perpendicular to the XO1Y plane of the measuring station to the ground measuring station, and d 2x is the projection of d in the O1X direction, d 2y is the projection of d in the O1Y direction; Step 2.2, calculate the fixed flight altitude of the drone according to the maximum flight speed constraint of the drone: v2≤v 2max In the formula, v2 is the flight speed of the drone, v 2max is the maximum flight speed of the UAV, A' is the derivative of the azimuth angle, and E' is the derivative of the pitch angle; Step 2.3, calculate the coordinates of the drone at the ground station based on the projection relationship:

4. The satellite simulation motion planning method based on an unmanned aerial vehicle platform according to claim 3 is characterized in that: In step 2.2, the UAV flight speed v2 is calculated by the following formula: v 2x =d(d 2x ) / dt=d(h·cotE·sinA) / dt=h·[(−1 / sin 2 E)·E'·(sinA)+cotE·cosA·A'] v 2y =d(d 2y ) / dt=d(h·cotE·cosA) / dt=h·[(-1 / sin 2 E)·E'·cosA+cotE(-sinA)·A'] v 2z ＝0 In the formula, v 2x 、v 2y and v 2z They are the velocity components of the drone in the O1X, O1Y and O1Z directions respectively.

5. The satellite simulation motion planning method based on an unmanned aerial vehicle platform according to claim 4 is characterized in that: Step 3 includes: Step 3.1, convert the geodetic coordinates (lat1, lon1, alt1) of the ground station into geocentric coordinates (x1, y1, z1): Where a and b are the lengths of the Earth's major and minor axes, respectively, and e is the first eccentricity of the Earth's ellipsoid; Step 3.2: The coordinates of the drone at the ground station (x 21 ,y 21 ,z 21 ) to geocentric coordinates (x, y, z): Step 3.3, convert the drone's geocentric coordinates (x, y, z) to geodetic coordinates (lat, lon, alt):

6. The satellite simulation motion planning method based on an unmanned aerial vehicle platform according to claim 5 is characterized in that: Step 4 includes: Step 4.1, calculate the mutual homogeneous transformation matrix between the drone body coordinate system, the inertial coordinate system and the ground station coordinate system, including the following sub-steps: Step 4.1.1, calculate the homogeneous transformation matrix R from the drone body coordinate system to the drone inertial coordinate system 2'2 : In the formula, ψ is the rotation angle of the drone around the Z axis of the inertial coordinate system; Step 4.1.2, calculate the homogeneous transformation matrix R from the UAV inertial coordinate system to the ground station coordinate system 21 : Step 4.2, calculating the UAV platform load pointing, includes the following sub-steps: Step 4.2.1, calculate the coordinates of a ground point P in the coordinate system of the drone, including: Step 4.2.1.1, calculate the homogeneous rotation matrix from the drone body coordinate system to the ground station coordinate system R 2'1 =R 2'2 ×R 21 Step 4.2.1.2, calculate the homogeneous transformation matrix R of the ground station coordinate system relative to the drone body coordinate system 12' : R 12' =R 2'1 -1 Step 4.2.1.3, calculate the coordinates of point P in the drone body coordinate system (Px 2' ,Py 2' ,Pz 2' ): Where (Px, Py, Pz) is the coordinate of point P in the ground station coordinate system; Step 4.2.2, calculate the direction of the drone payload, that is, the vector direction from the origin of the drone body coordinate system to point P:

7. The satellite simulation motion planning method based on an unmanned aerial vehicle platform according to claim 6 is characterized in that: Step 4.1.1 includes: Step 4.1.1.1, calculate the rotation matrices Rx, Ry and Rz of the drone around the X-axis, Y-axis and Z-axis of the inertial coordinate system respectively: Where θ is the rotation angle of the drone around the X-axis of the inertial coordinate system, The angle of rotation of the drone around the Y axis of the inertial coordinate system; Step 4.1.1.2, calculate the rotation matrix R from the body coordinate system to the inertial coordinate system 2'2 : Step 4.1.1.3, set θ = 0 and Substituting into the above formula, we get the following homogeneous transformation matrix R 2'2 :

8. The satellite simulation motion planning method based on an unmanned aerial vehicle platform according to claim 6 or 7, characterized in that: In step 4.1.1, the angle ψ of the drone's rotation around the Z axis of the inertial coordinate system is calculated as follows: tanψ=v 2x / v 2y 。

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