An Autonomous Mission Planning Method for Near-Circular Orbit Imaging Satellites

Abstract

The present invention is an autonomous mission planning method for near-circular orbit imaging satellites. The present invention relates to the fields of satellite bus management, attitude control, and orbit determination, and solves problems such as high consumption of manpower and material resources, cumbersome planning processes, and low utilization rate of satellite resources in existing ground-based planning methods. First, the present invention uses the ground track analysis method to delimit the satellite observation range and preliminarily screen out possible imaging points within the planning period; then estimates service parameters, and more accurately estimates the imaging side-sway angle, overpass time window, and payload configuration parameters that can cover the target points; finally, plans the optimal imaging scheme through a priority-based sequence filling algorithm. The on-board autonomous planning method described in the present invention does not require the consumption of a large amount of manpower and material resources, makes full use of satellite imaging resources, inputs the target library, the current position, velocity, and orbit information of the satellite, and the corresponding UTC time into the autonomous planning program, runs the autonomous planning method, and quickly and accurately completes the autonomous imaging mission planning for multiple target points.

Description

Technical Field

[0001] The present invention relates to the technical fields of satellite mission management, attitude control, and orbit determination, and is an autonomous mission planning method for imaging satellites in near-circular orbits. Background Art

[0002] With the substantial increase in the number of imaging satellites, the shortcomings of traditional TT&C and mission planning mechanisms have gradually emerged. On-board autonomous planning can significantly reduce the human and material resources consumed by users in ground mission planning, improve the utilization efficiency of satellites, and does not require relying on foreign dedicated aerospace professional analysis software and methods. Summary of the Invention

[0003] In order to overcome the deficiencies of the prior art and solve the contradiction between existing high-value satellite imaging resources and the tense ground system, the present invention provides an autonomous mission planning method for imaging satellites in near-circular orbits.

[0004] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device.

[0005] An autonomous mission planning method for imaging satellites in near-circular orbits, the method comprising the following steps:

[0006] Step 1: Set the initial orbital information of the satellite and information such as the longitude and latitude of 4096 target points; the initial orbital information of the satellite includes the position r0 and velocity v0 of the satellite at any moment t0 of this orbit.

[0007] Step 2: According to the initial orbital position of the satellite in Step 1, use the analytical method to calculate the sub-satellite point trajectory, obtain the observation range of the satellite in this orbit, and then use the longitude comparison algorithm of the same latitude line to screen the target points that can be imaged.

[0008] Step 3: Predict the service parameters of the target points screened in Step 2, including the imaging side-sway angle, over-the-top time window, and payload configuration parameters.

[0009] Step 4: Use the priority-based sequence filling algorithm for the service parameters calculated in Step 3 to autonomously plan the optimal imaging scheme and execute it.

[0010] Preferably, Step 1 is specifically:

[0011] Step 1.1: In the TOD coordinate system, considering the J2 mean perturbation effect, the rates of change of the longitude and latitude of the sub-satellite point are expressed by the following formula:

[0012]

[0013]

[0014] where φ and λ are the geocentric latitude and geocentric longitude respectively, δ and α are the declination and right ascension respectively, i is the orbital inclination, u is the argument of latitude, Ω is the right ascension of the ascending node, w E is the angular velocity of the Earth's rotation, and w u = du / dt is the rate of change of the argument of latitude, and for a small eccentricity orbit, it is expressed by the following formula:

[0015]

[0016] The derivative expression of the geocentric longitude with respect to the geocentric latitude is derived as:

[0017]

[0018] Step 1.2: Determine the argument of latitude of the satellite corresponding to the corresponding latitude;

[0019] The maximum side-sway angle of satellite imaging is α, the geocentric angle corresponding to the line connecting the imaging point and the target point on the trajectory is β, and the longitude and latitude coordinates of the trajectory point are M = (A1, A2). Then the coordinates N = (B1, B2) of the imaging point after the maximum side-sway maneuver are:

[0020]

[0021]

[0022] Step 1.3: When the maximum side-sway angle is 40°, calculate according to the orbital conditions to obtain the maximum side-sway imaging range corresponding to the sub-satellite point trajectory.

[0023] Preferably, the specific content of step 2 is as follows:

[0024] Given ΔL1, ΔL2, ΔL3, first determine whether the target point is on the left or right side of the trajectory, and then use the following formula as a condition for judgment:

[0025]

[0026] If any of the above formulas is satisfied, it is determined that the point is imaged; otherwise, it cannot be imaged. The imaging determination is performed on all target points in turn;

[0027] For a small section of the trajectory with the highest latitude, the longitude error of the discrete points of the trajectory and the imaging range line is relatively large, and the error of the result obtained by comparing longitudes is relatively large.

[0028] Preferably, it is applicable within the latitude range of ±70°.

[0029] Preferably, step 3 is specifically as follows:

[0030] Step 3.1: Predict the service parameters of the target points screened in step 2, including the imaging side-sway angle, over-the-top time window, and payload configuration parameters; adopt the side-sway angle prediction method. According to the geometric relationship between the satellite and the ground target point during side-sway imaging, point S is the satellite imaging point, point P is the ground target point, point R is the projection of the satellite on the ground plane, H is the orbital altitude, θ is the satellite side-sway angle, and Re is the radius of the earth;

[0031] To determine the satellite side-sway angle θ, the coordinates (b1, l1) of the satellite imaging point obtained by using the satellite coverage range determination algorithm are required. The longitude and latitude coordinates of point R are also (b1, l1). Given the pre-stored coordinates (b2, l2) of point P, the spherical distance d between points P and R is calculated by the haversine formula PR It is expressed by the following formula:

[0032]

[0033] The straight-line distance L between points P and R PR It is calculated by the following formula:

[0034]

[0035] The satellite side-sway angle θ is derived as follows:

[0036] θ = tan -1 (L PR / H)

[0037] Step 3.2: Adopt the over-the-top time window prediction method. When not considering the front and back side-sway of the satellite, the over-the-top time window can be estimated by solving the over-the-top time of the satellite. In the geodetic coordinate system, when the distance between the over-the-top moment of the satellite in orbit and the target point is the minimum value, the distance L between the satellite and the target point SP It is expressed by the following formula:

[0038]

[0039] Since H is approximately a constant value, solving for the minimum value of L SP is to solve for the minimum value of dPR at the current orbit, and its unique solution is denoted as (b0, l0);

[0040] Given that the time when the satellite passes through the ascending node is t0, the orbital inclination is i, and the geocentric latitude φ of the near-circular orbit is calculated by the following equation:

[0041] φ’ = arcsin(sin(n(t - t0))sini)

[0042] Among them, n represents the average angular velocity of the satellite orbiting the earth. Denote μ as the geocentric gravitational constant and a as the semi-major axis of the satellite orbit. Then n can be expressed as:

[0043]

[0044] Step 3.3: Adopt the load parameter prediction method. The satellite imaging load parameters are related to the solar altitude angle at the imaging moment. According to the sine formula, the cosine formula of the side, and the first five-element formula, the calculation formula of the solar altitude angle A is derived as follows:

[0045]

[0046] Among them, b is the latitude of the target point, and (t, δ) is the position of the sun in the hour angle coordinate system at the current orbit.

[0047] According to the predicted solar altitude angle interval, autonomously configure the load parameters, including PGA gain, integration level, and row transfer time, etc. The satellite pre-stores reasonable load parameters according to the ground operation and management experience, which is an important guarantee for image quality.

[0048] Preferably, in step 3.2, to improve the calculation accuracy, considering the earth's flattening f = 1 / 298.257, the conversion relationship between the geographic latitude b and the geocentric latitude φ is:

[0049]

[0050] Substitute the latitude solution b0, and the imaging center time of the target point can be solved. According to the actual constraints such as the load width and image slice size, calculate the satellite imaging time window.

[0051] Preferably, step 4 is specifically:

[0052] The sequence filling algorithm based on priority takes the target priority as a strong constraint. At the initial stage of the algorithm execution, the target set that can be covered is classified according to the priority. First, plan the imaging sequence of the highest priority target, then insert the low-priority target sequences into the highest priority sequence in turn according to the constraint conditions, and finally select the optimal sequence from multiple feasible sequences.

[0053] A near-circular orbit imaging satellite autonomous mission planning system, the system includes:

[0054] A setting module, which sets the initial orbit information of the satellite and information such as the longitude and latitude of 4096 points of the target; the initial orbit information of the satellite includes the position r0 and velocity v0 of the satellite at any moment t0 of this orbit;

[0055] An analysis module, which calculates the sub-satellite point trajectory using the analytical method according to the initial orbital position of the satellite, obtains the observation range of the satellite for this orbit, and then uses the longitude comparison algorithm of the same latitude line to screen the target points that can be imaged;

[0056] A prediction module, which predicts the service parameters of the screened target points, including the imaging side-sway angle, the overpass time window, and the payload configuration parameters;

[0057] An execution module, which autonomously plans and executes the optimal imaging scheme for the calculated service parameters through a priority-based sequence filling algorithm.

[0058] A computer-readable storage medium, on which a computer program is stored, and the program is executed by a processor to implement an autonomous mission planning method for a near-circular orbit imaging satellite.

[0059] A computer device, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor runs the computer program stored in the memory, the processor executes an autonomous mission planning method for a near-circular orbit imaging satellite.

[0060] The present invention has the following beneficial effects:

[0061] The present invention is an autonomous mission planning method for a near-circular orbit imaging satellite, which calculates through the sub-satellite point trajectory and the satellite observation range, uses the longitude comparison algorithm of the same latitude line to screen the target points that can be imaged, predicts the satellite imaging parameters, and uses a priority-based sequence filling algorithm to plan the optimal imaging scheme.

[0062] The present invention discloses an autonomous mission planning method for a near-circular orbit imaging satellite, which relates to the fields of satellite bus management, attitude control, and orbit determination, and solves the problems of high consumption of manpower and material resources, cumbersome planning process, and low utilization rate of satellite resources in the existing ground planning method. The present invention first applies the ground track analysis method to delimit the satellite observation range and preliminarily screen the possible imaging points within the planning period; then estimates the service parameters and more accurately estimates the imaging side-sway angle, the overpass time window, and the payload configuration parameters of the target points that can be covered; finally, plans the optimal imaging scheme through a priority-based sequence filling algorithm. The on-board autonomous planning method described in the present invention does not require a large amount of manpower and material resources, makes full use of the satellite imaging resources, inputs the target library, the current position, speed, and orbit information of the satellite, and the corresponding UTC time into the autonomous planning program, runs the autonomous planning method, and quickly and accurately completes the autonomous imaging mission planning of multiple target points. Description of the Drawings

[0063] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0064] Figure 1 It is a flowchart of an autonomous mission planning method for a near-circular orbit imaging satellite according to the present invention;

[0065] Figure 2 It is the geometric relationship between the satellite and the ground target point during side-sway imaging in the embodiment of the present invention;

[0066] Figure 3 It is a flowchart of a sequence filling algorithm based on priority in the embodiment of the present invention. Specific Embodiments

[0067] The following will clearly and completely describe the technical solutions of the present invention with reference to the drawings. Obviously, the described embodiments are some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0068] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be understood as a limitation to the present invention. In addition, the terms "first", "second", "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0069] In the description of the present invention, it should be noted that unless otherwise clearly specified and limited, the terms "installed", "connected", "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0070] In addition, the technical features involved in different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0071] The present invention is described in detail below in conjunction with specific embodiments. Specific Embodiment 1:

[0073] According to Figures 1 to 3 As shown, the specific optimized technical solution adopted by the present invention to solve the above technical problems is: The present invention relates to a method for autonomous mission planning of a near-circular orbit imaging satellite.

[0074] A method for autonomous mission planning of a near-circular orbit imaging satellite, the method comprising the following steps:

[0075] Step 1: Set the initial orbit information of the satellite and information such as the longitude and latitude of 4096 target points; the initial orbit information of the satellite includes the position r0 and velocity v0 of the satellite at any moment t0 of this orbit.

[0076] Step 2: According to the initial orbit position of the satellite in Step 1, use the analytical method to calculate the sub-satellite point trajectory, obtain the observation range of the satellite in this orbit, and then use the longitude comparison algorithm of the same latitude line to screen the target points that can be imaged.

[0077] Step 3: Predict the service parameters of the target points screened in Step 2, including the imaging side-sway angle, over-the-top time window, and payload configuration parameters.

[0078] Step 4: Through the priority-based sequence filling algorithm, autonomously plan the optimal imaging scheme for the service parameters calculated in Step 3 and execute it. Specific Embodiment 2:

[0080] The difference between Embodiment 2 and Embodiment 1 of this application is only that:

[0081] The specific content of Step 1 is:

[0082] Step 1.1: In the TOD coordinate system, considering the J2 mean perturbation effect, the change rate of the sub-satellite point longitude and latitude is expressed by the following formula:

[0083]

[0084]

[0085] where φ and λ are the geocentric latitude and geocentric longitude respectively, δ and α are the declination and right ascension respectively, i is the orbital inclination, u is the latitude argument, Ω is the right ascension of the ascending node, w E is the angular velocity of the Earth's rotation, w u = du / dt is the change rate of the latitude argument, and for a small eccentricity orbit, it is expressed by the following formula:

[0086]

[0087] The derivative expression of the geocentric longitude with respect to the geocentric latitude is derived as follows:

[0088]

[0089] Step 1.2: Determine the satellite latitude argument corresponding to the corresponding latitude;

[0090] The maximum side-sway angle of satellite imaging is α, the geocentric angle corresponding to the line connecting the imaging point and the target point on the trajectory is β, and the geodetic coordinates of the trajectory point are M = (A1, A2). Then the coordinates N = (B1, B2) of the imaging point after the maximum side-sway maneuver are:

[0091]

[0092]

[0093] Step 1.3: When the maximum side-sway angle is 40°, calculate according to the orbit conditions to obtain the maximum side-sway imaging range corresponding to the sub-satellite point trajectory. Specific Embodiment Three:

[0095] The difference between Embodiment Three and Embodiment Two of this application is only that:

[0096] The specific content of Step 2 is as follows:

[0097] Given ΔL1, ΔL2, ΔL3, first determine whether the target point is on the left or right side of the trajectory, and then use the following formula as a condition for judgment:

[0098]

[0099] If any of the above formulas is satisfied, it is determined that the point is imaged; otherwise, it cannot be imaged. The imaging determination is performed sequentially for all target points;

[0100] For a small section of the trajectory with the highest latitude, the longitude error between the discrete points of the trajectory and the imaging range line is relatively large, and the error of the result obtained by comparing longitudes is relatively large. Specific Embodiment Four:

[0102] The difference between Embodiment Four and Embodiment Three of this application is only that:

[0103] It is applicable within the latitude range of ±70°. Specific Embodiment Five:

[0105] The difference between Embodiment Five and Embodiment Four of this application is only that:

[0106] The specific content of Step 3 is as follows:

[0107] Step 3.1: Predict the service parameters of the target points screened in Step 2, including the imaging side-sway angle, over-the-top time window, and payload configuration parameters; adopt the side-sway angle prediction method. According to the geometric relationship between the satellite and the ground target point during side-sway imaging, point S is the satellite imaging point, point P is the ground target point, point R is the projection of the satellite on the ground plane, H is the orbital altitude, θ is the satellite side-sway angle, and Re is the radius of the Earth;

[0108] To determine the satellite side-sway angle θ, the coordinates (b1, l1) of the satellite imaging point obtained by using the satellite coverage range determination algorithm are required. The longitude and latitude coordinates of point R are also (b1, l1). Given the pre-stored coordinates (b2, l2) of point P, the spherical distance d between points P and R is calculated using the haversine formula PR which is expressed as follows:

[0109]

[0110] The straight-line distance L between points P and R PR is calculated as follows:

[0111]

[0112] The satellite side-sway angle θ is derived as follows:

[0113] θ = tan -1 (L PR / H)

[0114] Step 3.2: Adopt the over-the-top time window prediction method. When not considering the front and back side-sways of the satellite, the over-the-top time window can be estimated by solving the over-the-top time of the satellite. In the geodetic coordinate system, when the distance between the satellite at the over-the-top moment and the target point is at its minimum value, the distance L between the satellite and the target point SP is expressed as follows:

[0115]

[0116] Since H is approximately a constant value, solving for the minimum value of L SP is equivalent to solving for the minimum value of dPR at the current orbit, and its unique solution is denoted as (b0, l0);

[0117] Given that the time when the satellite passes through the ascending node is t0, the orbital inclination is i, and the geocentric latitude φ of the near-circular orbit is calculated by the following equation:

[0118] φ’ = arcsin(sin(n(t - t0))sini)

[0119] where n represents the average angular velocity of the satellite orbiting the Earth. Denote μ as the geocentric gravitational constant and a as the semi-major axis of the satellite orbit, then n can be expressed as:

[0120]

[0121] Step 3.3: Using the load parameter prediction method, the satellite imaging load parameters are related to the solar altitude angle at the imaging moment. According to the sine formula, the cosine formula of the side, and the first five-element formula, the calculation formula of the solar altitude angle A is derived as follows:

[0122]

[0123] Among them, b is the latitude of the target point, and (t, δ) is the position of the sun in the hour angle coordinate system at the current orbit.

[0124] According to the predicted solar altitude angle range, the autonomous configuration of load parameters includes PGA gain, integration level, and row transfer time, etc. The satellite pre-stores reasonable load parameters according to the ground operation and management experience, which is an important guarantee for image quality. Specific Embodiment Six:

[0126] The difference between Embodiment Six and Embodiment Five of this application is only that:

[0127] In step 3.2, to improve the calculation accuracy, considering the earth's flattening f = 1 / 298.257, the conversion relationship between the geographical latitude b and the geocentric latitude φ is obtained as:

[0128]

[0129] Substituting the latitude solution b0, the imaging center time of the target point can be solved, and according to the actual constraints such as the load width and image slice size, the satellite imaging time window is calculated. Specific Embodiment Seven:

[0131] The difference between Embodiment Seven and Embodiment Six of this application is only that:

[0132] Step 4 is specifically:

[0133] The sequence filling algorithm based on priority takes the target priority as a strong constraint. At the initial stage of the algorithm execution, the target set that can be covered is classified according to the priority. First, the imaging sequence of the highest priority target is planned, and then the sequences of each low priority target are inserted into the highest priority sequence according to the constraint conditions. Finally, the optimal sequence is selected from multiple feasible sequences. Specific Embodiment Eight:

[0135] The difference between Embodiment Eight and Embodiment Seven of this application is only that:

[0136] The present invention provides an autonomous mission planning system for a near-circular orbit imaging satellite, and the system includes:

[0137] A setting module that sets the initial orbital information of the satellite and information such as the target longitude and latitude of 4096 points; the initial orbital information of the satellite includes the position r0 and velocity v0 of the satellite at any moment t0 of this orbit.

[0138] An analysis module that calculates the sub-satellite point trajectory using the analytical method based on the initial orbital position of the satellite, obtains the observation range of the satellite for this orbit, and then uses the longitude comparison algorithm for the same latitude line to screen the target points that can be imaged.

[0139] A prediction module that predicts the service parameters of the screened target points, including the imaging side-sway angle, overpass time window, and payload configuration parameters.

[0140] An execution module that autonomously plans and executes the optimal imaging plan for the calculated service parameters through a priority-based sequence filling algorithm. Specific Embodiment Nine:

[0142] The difference between Embodiment Nine and Embodiment Eight of this application is only that:

[0143] The present invention provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, it is used to implement a method for autonomous mission planning of a near-circular orbit imaging satellite. Specific Embodiment Ten:

[0145] The difference between Embodiment Ten and Embodiment Nine of this application is only that:

[0146] The present invention provides a computer device, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor runs the computer program stored in the memory, the processor executes a method for autonomous mission planning of a near-circular orbit imaging satellite.

[0147] The specific steps of the autonomous planning method are as follows:

[0148] Step 1: Set the initial orbital information of the satellite, the longitude and latitude of 4096 points of the target, and the priority information; the initial orbital information of the satellite includes the position r0 and velocity v0 of the satellite at any moment t0 of this orbit.

[0149] The satellite maintains the longitude, latitude, and priority information of 4096 target points. When entering the earth's shadow area to start planning the imaging service for the next orbit, it only needs to obtain the position information at a certain moment through GPS or Beidou as the input for autonomous mission planning.

[0150] Step 2: According to the initial orbital position of the satellite in Step 1, calculate the sub-satellite point trajectory using the analytical method, obtain the observation range of the satellite for this orbit, and then use the longitude comparison algorithm for the same latitude line to screen the target points that can be imaged.

[0151] (1) Sub-satellite point trajectory and satellite observation range calculation

[0152] In the TOD coordinate system, considering only the J2 mean perturbation effect, the expressions for the rates of change of the sub-satellite point longitude and latitude are as follows:

[0153]

[0154]

[0155] where φ and λ are the geocentric latitude and geocentric longitude respectively, δ and α are the declination and right ascension respectively. i is the orbital inclination, u is the argument of latitude, Ω is the right ascension of the ascending node, and ω E is the angular velocity of the Earth's rotation. ω u = du / dt is the rate of change of the argument of latitude, and for a small eccentricity orbit, the following approximate formula can be used:

[0156]

[0157] The derivative expression of the geocentric longitude with respect to the geocentric latitude is derived as:

[0158]

[0159] According to the above formula, the satellite argument of latitude corresponding to the corresponding latitude can be obtained.

[0160] Assume that the maximum imaging side-sway angle of the satellite is α, the geocentric angle corresponding to the line connecting the imaging point and the target point on the trajectory is β, and the longitude and latitude coordinates of the trajectory point are M = (A1, A2). Then the coordinates of the imaging point N = (B1, B2) after the maximum side-sway maneuver are:

[0161]

[0162]

[0163] Assume that the maximum side-sway angle is 40°. Calculated according to the above orbital conditions, the maximum side-sway imaging range corresponding to the sub-satellite point trajectory (the imaging range between 70° north and south latitude) is obtained

[0164] (2) Screening target points that can be imaged by comparing longitudes on the same latitude line

[0165] Considering that the number of optional target points is large and the satellite computing power resources are limited, a simple and efficient algorithm is invented to determine whether the target point is within the observation range of the satellite for this orbit, that is, the longitude comparison algorithm on the same latitude line.

[0166] Given ΔL1, ΔL2, ΔL3, first determine whether the target point is on the left or right side of the trajectory, and then use the following formula as the condition for judgment:

[0167]

[0168] If one of the above equations is satisfied, it can be determined that imaging can be performed on this point; otherwise, imaging cannot be performed. According to the above method, imaging determination can be performed on all target points in sequence. Since the increase in computational complexity is mainly reflected in interpolation comparison, the increase in computational complexity corresponding to an increase in the number of target points is not obvious.

[0169] For a small section of the trajectory with the highest latitude, the longitude error between the trajectory and the discrete points of the imaging range line is large, and the error of the result obtained by longitude comparison is large. Therefore, this method is more applicable within the latitude range of ±70°.

[0170] Step 3: Predict the service parameters of the target points screened in Step 2, including the imaging side-sway angle, over-the-top time window, and payload configuration parameters;

[0171] (1) Side-sway angle prediction method

[0172] The geometric relationship between the satellite and the ground target point during side-sway imaging is as Figure 1 shown. Point S is the satellite imaging point, point P is the ground target point, point R is the projection of the satellite on the ground plane, H is the orbital altitude, θ is the satellite side-sway angle, and Re is the radius of the earth.

[0173] To solve for the satellite side-sway angle θ, the coordinates (b1, l1) of the satellite imaging point obtained by using the satellite coverage range determination algorithm are required. In the following figure, point S is the satellite imaging point. According to the principle of similar triangles, the longitude and latitude coordinates of point R are also (b1, l1). Given the known coordinates (b2, l2) of point P in advance, the spherical distance d between points P and R is calculated using the haversine formula PR as follows:

[0174]

[0175] The straight-line distance L between points P and R PR is calculated by the following formula:

[0176]

[0177] On this basis, the satellite side-sway angle θ is derived as follows:

[0178] θ = tan -1 (L PR / H)

[0179] (2) Over-the-top time window prediction method

[0180] When not considering the front and back side-sway of the satellite, the over-the-top time window can be estimated by solving the over-the-top time of the satellite. In the geodetic coordinate system, the distance between the satellite and the target point is the minimum at the over-the-top moment of the satellite in orbit. Still taking Figure 2 as an example, the distance L between the satellite and the target pointSP It can be expressed as:

[0181]

[0182] Since H is approximately a constant value, solve for L SP The minimum value of is to solve for the minimum value of the track d PR The only solution is denoted as (b0, l0).

[0183] Given that the satellite passes through the ascending node at time t0, the orbital inclination is i, and the geocentric latitude φ of the near-circular orbit is calculated by the following equation:

[0184] φ’ = arcsin(sin(n(t - t0))sini)

[0185] Where n represents the average angular velocity of the satellite orbiting the Earth, μ is denoted as the geocentric gravitational constant, and a is the semi-major axis of the satellite orbit, then n can be expressed as:

[0186]

[0187] To improve the calculation accuracy, considering the Earth's flattening f = 1 / 298.257, the conversion relationship between the geographic latitude b and the geocentric latitude φ is:

[0188]

[0189] Substitute the latitude solution b0 to solve for the imaging center time of the target point. According to the actual constraints such as the payload swath width and image slice size, calculate the satellite imaging time window.

[0190] (3) Payload parameter prediction method

[0191] The satellite imaging payload parameters are related to the solar altitude angle at the imaging time. According to the sine formula, the cosine formula of the side, and the first five-element formula, the calculation formula of the solar altitude angle A is derived as follows:

[0192]

[0193] Where b is the latitude of the target point, and (t, δ) is the position of the on-track sun in the hour angle coordinate system.

[0194] According to the predicted solar altitude angle range, independently configure the payload parameters including PGA gain, integration level, and row transfer time, etc. The satellite pre-stores reasonable payload parameters based on ground operation and management experience, which is an important guarantee for image quality.

[0195] Step 4: To select the optimal imaging path from the set of target points that can be covered, first establish an imaging constraint condition model, solve all feasible paths according to the constraint conditions, then design an imaging benefit function, select the path with the imaging benefit as the optimal path, and finally generate multiple imaging services in the satellite service format and execute them independently.

[0196] The priority-based sequence filling algorithm takes the target priority as a strong constraint. At the initial stage of the algorithm execution, the set of coverable targets is classified according to the priority. First, the imaging sequence of the highest priority target is planned, and then the sequences of each low priority target are inserted into the highest priority sequence according to the constraint conditions in turn. Finally, the optimal sequence is selected from multiple feasible sequences.

[0197] The process of designing the priority-based sequence filling algorithm is as Figure 3 shown. Among them, the target priority is defined as 1 to 255. The larger the priority value, the lower the corresponding target priority. I n represents the set of targets with the nth-level priority, and I n-m represents I n the m largest independent sets that satisfy the constraint conditions in it, and I 12…n-t represents the t feasible sets obtained after inserting the n-priority sequence into the high-priority sequence, and I 12…n represents I 12…n-t the final sequence after selecting the best. Specific Example XI:

[0199] The difference between the eleventh embodiment of this application and the tenth embodiment is only that:

[0200] Specific Embodiment 2. In combination with Figure 3 this embodiment is described. This embodiment is an example of a low-earth orbit optical satellite stereo imaging autonomous planning method described in Specific Embodiment 1: This embodiment is verified on the central computer of the Jilin-1 Magic Cube flexible satellite platform SmartFushion2M2S090-1FGG676 of Changguang Satellite Technology Co., Ltd. The designed satellite orbit is a sun-synchronous orbit with a height of 470 km, the average orbital semi-major axis a is 6848.137 km, the average orbital inclination i is 97.2934°, and the longitude of the ascending node LAN is 35°.

[0201] The star time statistics occupied by the operation in Step 2 are shown in Table 1. The operation time is mainly determined by the total number of targets in the target library and is less affected by the number of output targets.

[0202] Table 1

[0203]

[0204] The comparison results of the satellite overpass time calculated by the method in Step 3 and the overpass time generated by the Satellite-Access instruction in STK under the same conditions are shown in Table 2.

[0205] Table 2

[0206] Target point latitude 24.7°N 9.5°S 51.3°N Target point latitude 35.4°E 142.1°E 24.4°E Algorithm over-the-top moment 09:42:11 10:27:07 09:53:26 STK over-the-top moment 09:42:11 10:27:08 09:53:26 Algorithm side-sway angle +12.35° -21.67° -27.89° STK side-sway angle +11.80° -20.02° -27.19°

[0207] The deviation between the calculated satellite overpass time and the STK simulation value does not exceed 1 s; the deviation between the calculated slewing angle and the STK simulation value is within 0.9°. The above errors are all within the allowable range of actual applications. Without loss of generality, for points with small slewing angles, the calculation accuracy is equal to or higher than that in the above table, and the average error does not exceed 3.07%.

[0208] The average running duration of the priority-based sequence filling algorithm in Step 4 is shown in Table 3. Considering the autonomous planning period and the satellite imaging and data transmission capabilities, the maximum number of targets for each planned shooting is set to 20.

[0209] Table 3

[0210] Target upper limit Average running duration of the algorithm 5 7.175s 10 22.364s 15 70.553s 20 240.445s 25 802.483s

[0211] When autonomously generating services using the above method, only the service parameter format needs to be adjusted to adapt to other imaging satellites equipped with this autonomous mission planning algorithm. The operation speed and imaging effect both meet the engineering requirements, and for high-priority targets, "shoot every overpass" can be achieved.

[0212] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "examples", "specific examples", or "some examples", etc., mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples. Furthermore, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" can explicitly or implicitly include at least one of such features. In the description of the present invention, the meaning of "N" is at least two, such as two, three, etc., unless otherwise specifically and clearly defined. Any process or method description represented in the flowchart or described in other ways herein can be understood as representing a module, segment, or part of code including one or more N executable instructions for implementing a customized logical function or process, and the scope of the preferred embodiments of the present invention includes additional implementations, where the functions can be executed in a manner that is not in the order shown or discussed, including in a substantially simultaneous manner according to the functions involved or in the reverse order, which should be understood by those skilled in the art to which the embodiments of the present invention belong. The logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch instructions from the instruction execution system, apparatus, or device and execute the instructions), or in combination with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection portion (electronic device) having one or N wirings, a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM).In addition, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation or other suitable processing when necessary, and then stored in a computer memory. It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits with logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits with suitable combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0213] Those of ordinary skill in the art can understand that all or part of the steps carried by the method of the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments. In addition, in each embodiment of the present invention, the functional units can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above integrated module can be implemented in the form of hardware or in the form of a software functional module. When the above integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0214] The above is only a preferred embodiment of a method for autonomous mission planning of a near-circular orbit imaging satellite. The protection scope of a method for autonomous mission planning of a near-circular orbit imaging satellite is not limited to the above embodiments. Any technical solution within this concept belongs to the protection scope of the present invention. It should be noted that for those skilled in the art, several improvements and changes made without departing from the principle of the present invention should also be regarded as within the protection scope of the present invention.

Claims

1. An autonomous mission planning method for near-circular orbit imaging satellites, characterized in that: The method includes the following steps: Step 1: Set the initial orbital information of the satellite and the target longitude and latitude information of 4096 points; the initial orbital information of the satellite includes the position and velocity of the satellite at any moment in orbit. Step 2: According to the initial orbital position of the satellite in Step 1, use the analytical method to calculate the sub-satellite point trajectory, obtain the satellite's on-orbit observation range, and then use the same-latitude line comparison longitude algorithm to screen the target points that can be imaged. Specifically: Given ΔL1, ΔL2, ΔL3, first determine whether the target point is on the left or right side of the trajectory, and then use the following formula as the condition for judgment: If any of the above formulas is satisfied, it is determined that the point is imaged; otherwise, it cannot be imaged. Imaging determination is performed on all target points in turn. Step 3: Predict the service parameters of the target points screened in Step 2, including the imaging side-sway angle, over-the-top time window, and payload configuration parameters. The specific content of Step 3 is as follows: Step 3.1: Predict the business parameters of the target points screened in Step 2, including the imaging side-sway angle, the over-the-top time window, and the payload configuration parameters; adopt the side-sway angle prediction method to calculate the imaging side-sway angle according to the geometric relationship between the satellite and the ground target point during side-sway imaging. Set point S as the satellite imaging point, point P as the ground target point, point R as the projection of the satellite on the ground plane, H as the orbital altitude, θ as the satellite side-sway angle, and R e is the radius of the earth; The satellite imaging point coordinates (b1, l1) needed to determine the satellite side-sway angle θ are the same as the longitude and latitude coordinates of point R, which are also (b1, l1). Given that the coordinates (b2, l2) of the pre-stored point P are known, the spherical distance d between points P and R is calculated using the haversine formula PR It is expressed by the following formula: The straight-line distance L between two points PR PR It is calculated by the following formula: Derive the satellite side-sway angle θ as follows: θ = tan -1 (L PR / H) Step 3.2: Adopt the over-the-top time window prediction method. When not considering the lateral swing of the satellite, estimate the over-the-top time window by solving the over-the-top time of the satellite. In the geodetic coordinate system, the distance between the on-orbit satellite at the over-the-top moment and the target point is the minimum, and the distance L between the satellite and the target point SP is expressed by the following formula: Since H is approximately a constant value, solve for L SP The minimum value of SP is to solve for the minimum value of d in orbit PR The unique solution is denoted as (b0, l0); Given that the time when the satellite passes through the ascending node is t0, the orbital inclination is i, and the geocentric latitude φ' of the nearly circular orbit is calculated by the following equation: φ' = arcsin(sin(n(t - t0))sini) Where, n represents the average angular velocity of the satellite orbiting the earth. Denote μ as the geocentric gravitational constant and a as the semi-major axis of the satellite orbit, then n is expressed as: Step 3.3: Adopt the payload parameter prediction method. The satellite imaging payload parameters are related to the solar altitude angle at the imaging moment. According to the sine formula, the cosine formula of the side, and the first five-element formula, derive the calculation formula of the solar altitude angle A as follows: Where, b is the latitude of the target point, and (t', δ') is the position of the sun in the hour angle coordinate system in orbit. According to the predicted solar altitude angle range, autonomously configure the payload parameters including PGA gain, integration level, and row transfer time. In Step 3.2, to improve the calculation accuracy, considering the earth's flattening f = 1 / 298.257, the conversion relationship between the geodetic latitude b' and the geocentric latitude φ is: Substitute the latitude solution b0, solve the imaging center moment of the target point, and calculate the satellite imaging time window according to the actual constraints of the payload swath width and image slice size. Step 4: Use the priority-based sequence filling algorithm to autonomously plan and execute the optimal imaging scheme for the service parameters calculated in Step 3. The specific content of Step 4 is as follows: The priority-based sequence filling algorithm takes the target priority as a strong constraint. At the initial stage of the algorithm execution, the target set that can be covered is classified according to the priority. First, plan the imaging sequence of the highest-priority target, and then insert the low-priority target sequences into the highest-priority sequence in turn according to the constraint conditions. Finally, select the optimal sequence from multiple feasible sequences.

2. The autonomous mission planning method for a near-circular orbit imaging satellite according to claim 1, wherein: The specific content of Step 2 is as follows: Step 2.1: In the TOD coordinate system, considering the J2 mean perturbation effect, the change rate of the sub-satellite point longitude and latitude is expressed by the following formula: where φ and λ are the geocentric latitude and longitude respectively, δ and α are the declination and right ascension respectively, i is the orbital inclination, u is the argument of latitude, Ω is the right ascension of the ascending node, w E is the angular velocity of the Earth's rotation, w u = du / dt is the rate of change of the argument of latitude, which for a low eccentricity orbit is expressed by the following formula: Derive the derivative expression of the geocentric longitude with respect to the geocentric latitude: Step 2.2: Determine the satellite latitude argument corresponding to the corresponding latitude. The geocentric angle corresponding to the line connecting the imaging point and the target point on the trajectory is β. The longitude and latitude coordinates of the trajectory point are M = (A1, A2), then the coordinates of the imaging point N = (B1, B2) after the maximum side-sway maneuver are: Step 2.3: At a maximum lateral swing angle of 40°, calculate according to the orbit conditions to obtain the maximum lateral swing imaging range corresponding to the sub-satellite track.

3. A method for autonomous mission planning of a near-circular orbit imaging satellite according to claim 2, characterized in that: Applicable within the latitude range of ±70°.

4. A near-circular orbit imaging satellite autonomous mission planning system, which operates based on a near-circular orbit imaging satellite autonomous mission planning method as claimed in claim 1, and is characterized in that: The system includes: A setting module that sets the initial orbit information of the satellite and the longitude and latitude information of 4096 target points; the initial orbit information of the satellite includes the position and velocity of the satellite at any moment in orbit. An analysis module that calculates the sub-satellite track using the analytical method based on the initial orbit position of the satellite, obtains the on-orbit observation range of the satellite, and then uses the same latitude line comparison longitude algorithm to screen the target points that can be imaged. A prediction module that predicts the service parameters of the screened target points, including the imaging lateral swing angle, overhead time window, and payload configuration parameters. An execution module that autonomously plans and executes the optimal imaging plan for the calculated service parameters through a priority-based sequence filling algorithm.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that, This program is executed by a processor to implement a method for autonomous mission planning of a near-circular orbit imaging satellite as described in any one of claims 1-3.

6. A computer device, characterized in that, It includes a memory and a processor. A computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes a method for autonomous mission planning of a near-circular orbit imaging satellite as described in any one of claims 1-3.

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