A method for fast prediction of space target visibility to space-based platform

Abstract

The present application relates to a kind of space target to space-based platform visibility fast prediction method, belong to aerospace engineering and space target monitoring technical field, including obtaining the position sequence of space target during prediction, and the ephemeris of space-based platform is combined, and the inertial system observation vector of space-based platform and space target is obtained by interpolation at observation time;After the observation vector is corrected by light time, the observation direction of space target relative to load camera line of sight is calculated by coupling space-based platform pointing quaternion;Introduce the observation direction parameter of sun and moon under the same inertial system, moon phase parameter, determine the earth shadow blocking state of space target, and when determining that space target is not blocked by earth shadow, the constraint of solar and moon avoidance angle is superimposed, and the visibility result of target is output;Efficiently realize the visibility fast prediction of space-based platform to all-space space target, provide reliable data support for space-based observation mission planning, observation data real-time processing and false alarm signal accurate rejection.

Description

Technical Field

[0001] This invention relates to the field of aerospace engineering and space target monitoring technology, specifically to a method for rapid prediction of the visibility of space targets relative to space-based platforms. It is particularly suitable for space target observation missions based on space-based payload cameras, enabling accurate and rapid determination of the visibility of space targets relative to space-based platforms across the entire sky, and providing technical support for space target cataloging, observation mission planning, and data processing. Background Technology

[0002] With the rapid development of aerospace technology, the number of space targets such as satellites and debris in near-Earth space has surged. Real-time monitoring, orbit cataloging, and collision warning of space targets have become core requirements for ensuring the safety of aerospace missions and maintaining order in the space environment. Space-based observation platforms, with their advantages of wide coverage, lack of limitation by ground geographical conditions, and high observation timeliness, have gradually become core equipment in space target monitoring systems. Furthermore, the visibility prediction of space targets to space-based platforms is a prerequisite for achieving efficient observation by space-based platforms, rationally planning observation tasks, and improving the effectiveness of data processing.

[0003] Existing space target visibility prediction methods are mostly based on traditional orbit prediction models and coordinate system transformation strategies, which have several technical bottlenecks: First, the accuracy of coordinate system selection and transformation is insufficient. Some methods use non-inertial coordinate systems such as TEE or simplified transformation models, which are difficult to adapt to the needs of high-precision observation. As the standard inertial coordinate system for high-precision space observation, ICRF (International Celestial Reference Frame) lacks synergistic optimization with the rapid prediction of batch targets in the application of existing methods, which easily leads to an imbalance between prediction efficiency and coordinate accuracy. Second, the optical travel time correction mechanism is imperfect. The relative motion between space targets and space-based platforms and the finite speed of light will cause deviations between the observation time and the signal transmission time. Existing methods mostly use simplified correction formulas, which are difficult to achieve accurate compensation for deviations through iterative convergence, thus affecting the accuracy of observation pointing calculation. Third, the fusion of multiple factors for visibility judgment is insufficient. Existing methods often only consider the solar avoidance angle or the single factor of Earth shadow obstruction, ignoring the interference of the lunar avoidance angle and the lunar relative to the observation. Moreover, the synergistic judgment logic of various factors lacks systematic design, which easily leads to misjudgment of visibility results.

[0004] Meanwhile, space-based platform payload cameras often possess large field-of-view observation capabilities, placing higher demands on the efficiency of visibility prediction for batches of space targets across the entire sky. Existing methods lack streamlined optimization in aspects such as batch target orbit prediction, observation vector interpolation, and multi-object pointing calculation, making it difficult to simultaneously meet the dual requirements of "rapid prediction" and "high-precision determination." This hinders reliable support for real-time planning of space-based observation missions and the elimination of false alarms in observation data, thus restricting the overall operational efficiency of space-based space target monitoring systems. Therefore, developing a rapid visibility prediction method for space targets on space-based platforms that balances efficiency and accuracy, integrates multi-factor determination, and adapts to the ICRF coordinate system has become an urgent need in the field of space monitoring technology. Summary of the Invention

[0005] The purpose of this invention is to provide a method for rapid prediction of the visibility of space targets to space-based platforms, in order to solve the problems mentioned in the background art.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: a method for rapid prediction of the visibility of space targets to space-based platforms, comprising the following steps:

[0007] The position sequence of space targets during the forecast period is obtained, and combined with the ephemeris of the space-based platform, the inertial frame observation vectors of the space-based platform and space targets at the observation time are obtained by interpolation.

[0008] After performing optical time-of-flight correction on the observation vector, the space-based platform pointing quaternion is coupled to calculate the observation pointing of the space target relative to the line of sight of the payload camera;

[0009] By introducing solar and lunar observation pointing parameters and lunar phase parameters under the same inertial frame, the Earth shadow occlusion state of space targets is determined. When it is determined that the space targets are not occluded by the Earth shadow, the constraints of the solar and lunar avoidance angles are superimposed to output the visibility results of the targets.

[0010] Preferably, the whole-day rapid forecast of space targets is based on two rows of roots, and the batch processing scale is not less than 50,000 space targets. The forecast time step is set to 1s-60s. At the same time, the forecast position is transformed from the TEE coordinate system to the ICRF inertial coordinate system to obtain the position sequence of space targets during the forecast period.

[0011] Preferably, a cubic spline interpolation algorithm is used to construct space target position splines and space-based platform position splines respectively, and interpolation values ​​are obtained from the space target position splines and space-based platform position splines to obtain the observation vector. :

[0012] ;

[0013] ;

[0014] ;

[0015] in, and These are the position vectors of the space target and the space-based platform in the ICRF inertial frame, respectively. For interpolating the location of spatial targets, a spline function is used. For the interpolation spline function of the space-based platform position, The observation time.

[0016] Preferably, the linear completion mechanism introduced before interpolation includes:

[0017] Determine the monotonicity and continuity of time-stamped sequences:

[0018] ;

[0019] like:

[0020] or ;

[0021] Then mark it as a missing segment and record the missing interval. k and m indicate that the spatial target measurement results from frame k to frame m are missing;

[0022] For missing intervals For any time t within the range, linear extrapolation is used for completion:

[0023] ;

[0024] After completion, reconstruct the spline nodes at the target location.

[0025] Preferably, the optical travel time correction is solved using inverse iterative methods, and is based on iterative observation times at fixed points. Using the anchor point, calculate the target position at the time of launch to correct the observation vector for the time of light travel:

[0026] ;

[0027] ;

[0028] Where τ is the propagation time of the signal from the space target to the space-based platform.

[0029] Preferably, the optical timing error after optical timing correction does not exceed [a certain value]. .

[0030] Preferably, calculating the observation direction of the space target relative to the line of sight of the payload camera includes:

[0031] The observations, corrected for optical travel time, were transferred to the space-based platform's main system, and the observation vectors of the main system were calculated using a quaternion rotation matrix; based on the installation matrix... Transform the observation vectors of this system into the payload-camera coordinate system:

[0032] ;

[0033] Where T represents the transpose operation. This is the observation vector for this system;

[0034] With the camera's optical axis as the reference Z-axis, the camera system unit vector is defined as: And obtain the deviation angle of the spatial target relative to the optical axis. Azimuth and elevation angle :

[0035] ;

[0036] ;

[0037] ;

[0038] (α,δ) is used as the pointing angle of the spatial target in the camera's field of view.

[0039] Preferably, the ICRF coordinates of the Sun and Moon are obtained based on the DE planetary ephemeris of JDL, and the Sun's deviation angle relative to the optical axis is calculated by combining the observed pointing direction. and the angle of deviation of the moon relative to the optical axis Then calculate the angle between the sun, the moon, and the space-based platform, i.e., the lunar phase. The surface area of ​​the moon is expressed as:

[0040] .

[0041] Preferably, the ground shadow occlusion state of the space target includes:

[0042] The position vectors of the Sun and Moon in the ICRF inertial frame are obtained based on the planetary ephemeris, and the observation pointing of the Sun and Moon, as well as the lunar phase, are obtained after correcting the light travel time.

[0043] The distances between the sun and the Earth's center, between a space target and the Earth's center, and between a space target and the sun are calculated using the vector difference formula.

[0044] Calculate the angle between the sun, the space target, and the Earth's center, using the space target as the vertex. ;

[0045] The arcsine formula was used to calculate the angles subtended by the Earth and the Sun relative to the space target. and ;

[0046] Compare the included angle θ with the difference between the two angles, and set the occlusion flag ishadow:

[0047] ;

[0048] When ishadow=0, it is determined that the target is not occluded by the ground shadow. When ishadow=1, it is determined that the target is in the ground shadow umbra.

[0049] Preferably, the target visibility results include: the target's number, the target's shadow occlusion indicator, and the angle of deviation of the sun relative to the optical axis. Angle between the moon and the line of sight Lunar phase The azimuth and elevation angles of the target relative to the camera's line of sight to the payload.

[0050] Beneficial Effects: This invention corrects the observation vector for optical travel time and couples it with the quaternion of the space-based platform to calculate the target observation direction. Simultaneously, it introduces multi-dimensional parameters such as the observation direction of the sun and moon, lunar phase, and Earth shadow occlusion for visibility determination. Through multi-step collaborative optimization, it not only effectively solves the technical pain points of insufficient coordinate accuracy, simplified optical travel time correction, and single visibility determination factors in traditional methods, but also significantly improves the accuracy and reliability of space target visibility prediction. It can also realize rapid prediction processing of batch space targets across the entire sky, taking into account both prediction efficiency and observation accuracy. It is perfectly adapted to the observation mission scenarios of space-based payload cameras and can provide accurate and efficient data support for space-based platform observation mission planning, space target cataloging and updating, false alarm elimination of observation data, and real-time processing. It greatly improves the overall operational efficiency and mission safety of the space-based space target monitoring system and has extremely strong engineering application value and practicality. Attached Figure Description

[0051] Figure 1 A flowchart for inventing a method for rapid prediction of the visibility of space targets to space-based platforms;

[0052] Figure 2 This is a flowchart of the optical travel time iteration in an embodiment of the present invention;

[0053] Figure 3 This is a schematic diagram showing the azimuth and elevation angles of the target relative to the line of sight of the payload camera in an embodiment of the present invention;

[0054] Figure 4 This is a diagram showing the verification results of target visibility prediction based on STK software in an embodiment of the present invention. Detailed Implementation

[0055] To make the objectives and advantages of this invention clearer, the invention will be specifically described below with reference to embodiments. It should be understood that the following text is merely used to describe one or more specific embodiments of the invention and does not strictly limit the scope of protection specifically claimed by the invention.

[0056] Example, reference Figure 1 As shown, a method for rapid prediction of the visibility of space targets to space-based platforms includes the following steps:

[0057] S1. Target inertial frame position and velocity prediction, specifically:

[0058] Rapid batch forecasting of all-day space targets based on two-row roots, while transforming the forecast positions from the TME (TrueEquator Mean Equinox) coordinate system to the ICRF inertial coordinate system, to obtain the position sequence of space targets during the forecast period;

[0059] In this example, the SGP4 / SDP4 orbit prediction model and a two-row root database of all-sky space targets are used to make batch rapid predictions of all-sky space targets. Approximately 50,000 space targets are processed in batches, with the prediction time step set to 30 seconds. At the same time, the precession nutation matrix is ​​calculated based on the orbit epoch to complete the transformation from the TEE coordinate system to the ICRF coordinate system.

[0060] S2. Calculate the observed vector interpolation, specifically:

[0061] Based on the ephemeris data of the space-based platform and the position sequence of the space target, interpolation is used to obtain the inertial frame observation vectors (X, Y, Z) of the space-based platform and the space target at the observation time.

[0062] In one embodiment, a cubic spline interpolation algorithm is used to obtain the inertial frame observation vector at the observation time, ensuring high interpolation accuracy. Furthermore, the integrity of the space-based platform's ephemeris data is simultaneously verified during the interpolation process, and missing ephemeris data is repaired using a linear completion algorithm to ensure the continuity of the observation vector calculation. The interpolation is performed as follows:

[0063] S21. Construct the spline at the target location;

[0064] Given a discrete list of target ephemeris (predicted position) points Construct cubic splines And satisfy:

[0065] ;

[0066] S22. Construct the space-based platform position spline: Given the discrete point sequence of the space-based platform's ephemeris. Independent construction And satisfy:

[0067] ;

[0068] S23, interpolation values ​​for space targets and space-based platforms are obtained separately:

[0069] ;

[0070] ;

[0071] S24. Form the observation vector.

[0072] .

[0073] in, and These are the position vectors of the space target and the space-based platform in the ICRF inertial frame, respectively. For interpolating the location of spatial targets, a spline function is used. For the interpolation spline function of the space-based platform position, The observation time;

[0074] In one embodiment, a linear completion mechanism is introduced before interpolation, including:

[0075] Determine the monotonicity and continuity of time-stamped sequences:

[0076] (Equal step size);

[0077] like:

[0078] or ;

[0079] Then mark it as a missing segment and record the missing interval. k and m indicate that the spatial target measurement results from frame k to frame m are missing;

[0080] For missing intervals For any time t within the range, linear extrapolation is used for completion:

[0081] ;

[0082] After completion, the spline nodes at the target location are reconstructed to ensure that the interpolation function is continuous and second-differentiable throughout the entire observation window.

[0083] S3, Optical Travel Time Correction, Reference Figure 2 As shown, using observation time t as the anchor point, the inverse iterative solution is employed to determine the emission time of the space target signal, correcting the target's inertial frame position and ensuring consistency between the target-platform geometric distance and the speed of light, thus completing the optical travel time correction; specifically:

[0084] S31. Establish the optical travel time equation; taking the observation time t as the reference, let the propagation time of the signal from the space target to the space-based platform be τ, then:

[0085] ;

[0086] in and τ and c are the position vectors of the space target and the space-based platform in the ICRF inertial frame, respectively. They can be obtained by interpolation from the predicted position sequence of the target and the ephemeris of the space-based platform at time t. c is the speed of light, and τ is the propagation time of the signal from the space target to the space-based platform.

[0087] S32. Iteratively solve for the launch time; using fixed-point iteration:

[0088] ;

[0089] Initial value Convergence threshold set For LEO-LEO geometry, the final optical travel time can be obtained by 3-5 iterations. ;

[0090] S33. Correct the observation vector; based on the observation time. Using the anchor point, the target position at the "launch time" is obtained:

[0091] ;

[0092] The platform-to-target unit vector calculated in this way is the observation direction after the correction of the light travel time, which can be directly used for subsequent visibility calculations.

[0093] .

[0094] Wherein, the iterative convergence threshold is The corrected optical travel time error does not exceed .

[0095] In one embodiment, the iteration step size is dynamically adjusted during the iteration process in conjunction with the orbital eccentricity of the space target.

[0096] S4. Observation Pointing Calculation: Based on the observation vector coupled to the space-based platform pointing quaternion after optical travel time correction, calculate the observation pointing (azimuth and elevation angles) of the target relative to the payload camera's line of sight. Figure 3 As shown); specifically:

[0097] S41. Corrected observation vector and space-based platform quaternion input; the space-based platform quaternion is... Describes the rotation of the platform body → ICRF;

[0098] S42. Transfer the observation vector to the platform's own system; use the quaternion rotation matrix:

[0099] ;

[0100] The observed vectors of this system are obtained as follows:

[0101] ;

[0102] This refers to the observation vector in the ICRF (International Celestial Reference Frame, ICRF being a concrete implementation of ICRS).

[0103] S43. Switch to the load camera coordinate system; according to the installation matrix... Perform the following calculations:

[0104] ;

[0105] S44. Calculate the right ascension and declination of the camera's optical axis relative to the load; with the camera's optical axis as the reference Z-axis, let the unit vector of the camera system be:

[0106] ;

[0107] The target's deviation angle relative to the optical axis is:

[0108] ;

[0109] Azimuth:

[0110] ;

[0111] Angle of elevation:

[0112] ;

[0113] The obtained (α,δ) is the relative pointing angle of the target in the camera's field of view, which can be directly used for subsequent visibility calculation and analysis.

[0114] S5. Calculation of Sun and Moon Observation Angles: Based on the planetary ephemeris, the position vectors of the Sun and Moon in the ICRF inertial frame are obtained, and the optical time is corrected to complete the calculation of the observation pointing of the Sun and Moon, as well as the lunar phase. In this embodiment, the ICRF coordinates of the Sun and Moon are obtained based on the DE planetary ephemeris of JDP to calculate the observation angles of the Sun and Moon. Based on the observation pointing calculation method described in S4, the deviation angle of the Sun relative to the optical axis is obtained. and the angle of deviation of the moon relative to the optical axis Then calculate the angle between the sun, the moon, and the space-based platform, i.e., the lunar phase. The surface area of ​​the moon is expressed as:

[0115] ;

[0116] Used to assess the extent to which the payload is affected by moonlight.

[0117] S6. Calculation of Earth's Shadow Occlusion Zone: Based on the Sun's inertial frame position vector, the Earth's size information, and the orbital positions of the space target and the space-based platform, calculate whether the space target is obscured by the Earth's shadow. Specifically, this includes:

[0118] S61. Obtain ephemeris data; read the ephemeris file from the space-based platform, obtain the Sun's ICRF coordinates based on the planetary ephemeris, and obtain the space target's position vector. With the solar position vector Both are represented with the Earth's center as the origin and in the same inertial reference frame;

[0119] S62. Calculate the lengths of the three sides: Using the vector difference formula, we can obtain:

[0120] ;

[0121] ;

[0122] ;

[0123] Where s2e is the distance between the sun and the earth's center, o2e is the distance between the space target and the earth's center, and o2s is the distance between the space target and the sun;

[0124] S63. Calculate the angle between the sun, the space target, and the Earth's center; using the space target as the vertex, calculate the angle between the sun, the space target, and the Earth's center using the following formula. :

[0125] ;

[0126] S64. Calculate the angles subtended by the Earth and the Sun relative to a space target; using the arcsine formula, the following results are obtained:

[0127] ;

[0128] ;

[0129] in, The average radius of the Earth The average radius of the sun;

[0130] S65, Earth Shadow Criterion; Comparison Set the occlusion marker ishadow based on the difference between the two corners:

[0131] ;

[0132] When ishadow=0, it is determined that the target is not occluded by the ground shadow. When ishadow=1, it is determined that the target is in the ground shadow umbra.

[0133] S7. Visibility Result Output: Constrained by the sun and moon avoidance angles, the target visibility result is output based on preset sun avoidance angles (45° in this embodiment) and moon avoidance angles (not less than 30° in the full moon state in this embodiment). The target visibility result includes: target number, target shadow occlusion indicator, and sun deviation angle relative to the optical axis. Angle between the moon and the line of sight Lunar phase The azimuth and elevation angles of the target relative to the camera's line of sight to the payload.

[0134] This application also provides a specific experiment to comprehensively analyze the effectiveness and superiority of the method provided above; the settings are as follows: the parameters of the simulation space-based platform used are:

[0135] Orbital epoch: September 9, 2025, 00:00:00.00;

[0136] The orbital parameters are: semi-major axis = 6905000.0m, eccentricity = 0.001, orbital inclination = 97°, ascending node longitude = 30°, perigee distance = 120°, and horizontal perigee angle = 100°; (Results for reference) Figure 4 As shown, this is the verification result of the target visibility forecast based on the STK software. After loading all the forecasted visible targets into the STK software, all targets are within the set load field of view, indicating that the calculation results are completely correct.

[0137] The embodiments of the present invention have been described in detail above with reference to the examples. However, the present invention is not limited to the above embodiments. For those skilled in the art, after learning the contents described in the present invention, several equivalent changes and substitutions can be made without departing from the principle of the present invention. These equivalent changes and substitutions should also be considered to fall within the protection scope of the present invention.

Claims

1. A method for rapid prediction of the visibility of space targets to space-based platforms, characterized in that: Includes the following steps: The position sequence of space targets during the forecast period is obtained, and combined with the ephemeris of the space-based platform, the inertial frame observation vectors of the space-based platform and space targets at the observation time are obtained by interpolation. After performing optical time-of-flight correction on the observation vector, the space-based platform pointing quaternion is coupled to calculate the observation pointing of the space target relative to the line of sight of the payload camera; By introducing solar and lunar observation pointing parameters and lunar phase parameters under the same inertial frame, the Earth shadow occlusion state of space targets is determined. When it is determined that the space targets are not occluded by the Earth shadow, the constraints of the solar and lunar avoidance angles are superimposed to output the visibility results of the targets.

2. The method for rapid prediction of the visibility of space targets to space-based platforms according to claim 1, characterized in that: The system provides rapid batch forecasting of all-day space targets based on two-row roots, with a batch processing scale of no less than 50,000 space targets. The forecast time step is set to 1s-60s. At the same time, the forecast positions are transformed from the TEE coordinate system to the ICRF inertial coordinate system to obtain the position sequence of space targets during the forecast period.

3. The method for rapid prediction of the visibility of space targets to space-based platforms according to claim 2, characterized in that: A cubic spline interpolation algorithm is used to construct space target position splines and space-based platform position splines, respectively. Interpolation is then performed on these splines to obtain the observation vector. : ； ； ； in, and These are the position vectors of the space target and the space-based platform in the ICRF inertial frame, respectively. For interpolating the location of spatial targets, a spline function is used. For the interpolation spline function of the space-based platform position, The observation time.

4. The method for rapid prediction of the visibility of space targets to space-based platforms according to claim 3, characterized in that: The linear completion mechanism introduced before interpolation includes: Determine the monotonicity and continuity of time-stamped sequences: ； like: or ; Then mark it as a missing segment and record the missing interval. k and m indicate that the spatial target measurement results from frame k to frame m are missing; For missing intervals For any time t within the range, linear extrapolation is used for completion: ； After completion, reconstruct the spline nodes at the target location.

5. A method for rapid prediction of the visibility of a space target to a space-based platform according to claim 3 or 4, characterized in that: The optical travel time correction is solved using inverse iterative methods, based on iterative observation times at fixed points. Using the anchor point, calculate the target position at the time of launch to correct the observation vector for the time of light travel: ； ； Where τ is the propagation time of the signal from the space target to the space-based platform.

6. The method for rapid prediction of the visibility of space targets to space-based platforms according to claim 5, characterized in that: The optical timing error after optical timing correction does not exceed .

7. A method for rapid prediction of the visibility of space targets to space-based platforms according to claim 5, characterized in that: Calculate the observation pointing of the space target relative to the payload camera's line of sight, including: The observations, corrected for optical travel time, were transferred to the space-based platform's main system, and the observation vectors of the main system were calculated using a quaternion rotation matrix; based on the installation matrix... Transform the observation vectors of this system into the payload-camera coordinate system: ； Where T represents the transpose operation. This is the observation vector for this system; With the camera's optical axis as the reference Z-axis, the camera system unit vector is defined as: And obtain the deviation angle of the spatial target relative to the optical axis. Azimuth and elevation angle : ； ； ； (α,δ) is used as the pointing angle of the spatial target in the camera's field of view.

8. The method for rapid prediction of the visibility of space targets to space-based platforms according to claim 7, characterized in that: The ICRF coordinates of the Sun and Moon were obtained from the DE planetary ephemeris of JDL, and the Sun's offset angle relative to the optical axis was calculated by combining the observed pointing direction. and the angle of deviation of the moon relative to the optical axis Then calculate the angle between the sun, the moon, and the space-based platform, i.e., the lunar phase. The surface area of ​​the moon is expressed as: 。 9. A method for rapid prediction of the visibility of a space target to a space-based platform according to claim 8, characterized in that: The ground shadow occlusion state of the space target includes: The position vectors of the Sun and Moon in the ICRF inertial frame are obtained based on the planetary ephemeris, and the observation pointing of the Sun and Moon, as well as the lunar phase, are obtained after correcting the light travel time. The distances between the sun and the Earth's center, between a space target and the Earth's center, and between a space target and the sun are calculated using the vector difference formula. Calculate the angle between the sun, the space target, and the Earth's center, using the space target as the vertex. ; The arcsine formula was used to calculate the angles subtended by the Earth and the Sun relative to the space target. and ; Compare the included angle θ with the difference between the two angles, and set the occlusion flag ishadow: ； When ishadow=0, it is determined that the target is not occluded by the ground shadow. When ishadow=1, it is determined that the target is in the ground shadow umbra.

10. A method for rapid prediction of the visibility of a space target to a space-based platform according to claim 9, characterized in that: The target visibility results include: the target's number, the target's shadow occlusion indicator, and the angle of the sun's deviation from the optical axis. Angle between the moon and the line of sight Lunar phase The azimuth and elevation angles of the target relative to the camera's line of sight to the payload.

Images