A j4 track prediction method

Abstract

The present application relates to the technical field of orbit prediction, and particularly relates to a J4 orbit prediction method, which comprises the following steps: acquiring orbit basic information and verifying available input data; generating a second-order flattening benchmark prediction result and a fourth-order gravity sensitivity result based on the available input data; determining a fourth-order correction strategy result according to the fourth-order gravity sensitivity result, and performing correction contribution analysis on the second-order flattening benchmark prediction result according to the fourth-order correction strategy result, so as to obtain a fourth-order correction orbit prediction result and a fourth-order correction contribution result, thereby clearly showing the position, velocity, ground track and visible window changes caused by the fourth-order correction.

Description

Technical Field

[0001] This invention relates to the field of orbit prediction, and more particularly to a J4 orbit prediction method, electronic device, and storage medium. Background Technology

[0002] In short- and medium-range orbit prediction and ground station visibility window planning scenarios for low- and medium-Earth orbit satellites, the satellite's orbital state is affected by Earth's non-spherical gravity, atmospheric drag, and other perturbation factors. For ground station transit prediction, mission imaging window prediction, and pre-orbit control prediction, orbit prediction not only needs to provide the future position and velocity but also needs to minimize prediction errors with limited computing resources. If the actual impact of the fourth-order Earth non-spherical gravitational term in the current orbital segment cannot be determined, prediction errors can easily accumulate over multiple orbits or multiple days of prediction, affecting the ground station's acquisition, imaging timing, and orbit control plan.

[0003] Currently, existing technologies typically first obtain the satellite's initial position, velocity, or orbital elements, and then perform orbit extrapolation using a second-order Earth oblateness perturbation model, a fourth-order Earth non-spherical gravitational perturbation model, or a high-precision numerical propagation model. For prediction methods that need to consider the fourth-order Earth non-spherical gravitational term, the corresponding perturbation term is usually directly added to the orbital dynamics model, and the future position, velocity, and orbital elements are obtained through analytical calculation or numerical integration. This result is then used for ground station visibility windows, mission planning, or orbit control analysis.

[0004] However, existing technologies typically treat the fourth-order Earth non-spherical gravitational term as a fixed model term in calculations, lacking sensitivity assessments specific to particular orbital segments. The impact of this perturbation term on orbital phase and ground trajectory varies depending on orbital altitude, inclination, eccentricity, and forecast duration. Applying the same fourth-order perturbation treatment to all orbital segments makes it difficult to identify which forecast periods truly require fourth-order corrections, and also increases unnecessary computational burden, leading to a trade-off between forecast accuracy and efficiency. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing orbit prediction methods that fix the fourth-order non-spherical Earth gravitational term in the calculation and lack a mechanism to determine its necessity based on orbital segments. This increases the computational burden and makes it difficult to simultaneously explain the correction contribution, error source, and result reliability, thus affecting the stable use of the prediction results. Therefore, this invention proposes a J4 orbit prediction method, electronic device, and storage medium.

[0006] To at least solve some of the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0007] Firstly, this invention provides a method for predicting the J4 orbit, including:

[0008] Obtain basic track information and perform consistency checks to obtain usable input data;

[0009] Perform second-order flattening extrapolation on the available input data to obtain the second-order flattening baseline prediction result;

[0010] A fourth-order gravitational sensitivity analysis was performed on the available input data to obtain the fourth-order gravitational sensitivity results;

[0011] The results of the fourth-order correction strategy are determined based on the fourth-order gravitational sensitivity results.

[0012] Using the results of the fourth-order correction strategy as constraints, a correction contribution analysis is performed on the second-order oblateness baseline prediction results to obtain the fourth-order corrected orbit prediction results and the fourth-order correction contribution results.

[0013] Preferably, after obtaining the fourth-order corrected orbit prediction results and the fourth-order corrected contribution results, the method further includes:

[0014] Perform residual verification on the fourth-order corrected trajectory prediction results to obtain the prediction residual results;

[0015] Based on the fourth-order correction contribution results and the forecast residual results, a forecast reliability attribution analysis was performed to obtain the forecast confidence results and error source results.

[0016] Based on the forecast reliability results and error source results, model adjustment matching is performed to obtain model adjustment suggestion results;

[0017] By integrating the fourth-order corrected orbit prediction results, fourth-order corrected contribution results, prediction confidence results, error source results, and model adjustment suggestion results, a comprehensive orbit prediction result is obtained.

[0018] Preferably, a fourth-order gravitational sensitivity analysis is performed on the available input data to obtain fourth-order gravitational sensitivity results, including:

[0019] Sensitive input construction is performed on the available input data to generate sensitive analysis input quantities;

[0020] The sensitivity analysis input values ​​are normalized to obtain a set of sensitivity input values;

[0021] A weighted calculation is performed on the set of sensitive input values ​​to obtain the sensitivity values;

[0022] The sensitivity value is compared with a preset sensitivity threshold to obtain a fourth-order gravitational sensitivity result, which includes one of a low-sensitivity state, a medium-sensitivity state, and a high-sensitivity state.

[0023] Preferably, the determination of the fourth-order correction strategy result based on the fourth-order gravitational sensitivity result includes:

[0024] Strategy determination data is obtained by organizing the available input data and the second-order flattening baseline forecast results;

[0025] Based on the strategy determination data, a correction strategy determination is performed on different fourth-order gravitational sensitivity results to determine at least one of the target correction period, fourth-order correction calculation time, correction step size, and non-correction reason marker.

[0026] The result of the fourth-order correction strategy is determined based on the target correction period, the fourth-order correction calculation time, the correction step size, and the flag indicating the reason for not correcting.

[0027] Preferably, the second-order oblateness baseline prediction result is subjected to a correction contribution analysis based on the fourth-order correction strategy result as a constraint to obtain the fourth-order corrected orbit prediction result and the fourth-order correction contribution result, including:

[0028] Based on the results of the fourth-order correction strategy, data extraction is performed on the second-order oblateness baseline prediction results to determine the baseline orbit data;

[0029] Based on the aforementioned baseline orbit data and pre-stored Earth gravity model data, calculate the fourth-order correction sequence;

[0030] The fourth-order correction sequence is added to the reference orbit data at the same prediction time in the second-order flattening reference prediction result time by time to obtain the fourth-order corrected orbit prediction result.

[0031] The fourth-order corrected orbit prediction result and the second-order oblateness baseline prediction result are compared at the same prediction time to obtain the fourth-order corrected contribution result.

[0032] Preferably, residual verification is performed on the fourth-order corrected orbit prediction results to obtain prediction residual results, including:

[0033] Obtain the verification reference data and mark the reference source identifier for each verification reference data;

[0034] The verification reference data is compared with the second-order flattening baseline prediction result and the fourth-order corrected orbit prediction result by performing synchronous residual statistics to obtain the baseline residual and the corrected residual.

[0035] Subtract the corrected residual from the baseline residual to obtain the residual improvement.

[0036] The baseline residual, the corrected residual, the residual improvement, and the reference source identifier are written into the forecast residual results.

[0037] Preferably, a forecast reliability attribution analysis is performed based on the fourth-order correction contribution results and the forecast residual results to obtain forecast confidence results and error source results, including:

[0038] The available input data and the pre-stored task error configuration table are processed to generate trustworthy judgment data by organizing the trustworthy parameters.

[0039] Based on the fourth-order corrected contribution results and the predicted residual results, contribution matching calculations are performed to determine the contribution matching score;

[0040] Based on the aforementioned credibility determination data, a credibility state determination is performed to generate a forecast credibility result;

[0041] Based on the predicted residual results and reliable judgment data, the error source determination is performed, and the error source results are generated.

[0042] Preferably, model adjustment matching is performed based on forecast confidence results and error source results to obtain model adjustment suggestion results, including:

[0043] The triggering criteria for generating the model are adjusted based on the forecast credibility results, error source results, and credibility determination data.

[0044] The model adjustment trigger is used to perform model adjustment matching and determine the suggestion type;

[0045] Based on the suggested type and the triggering criteria for model adjustment, model adjustment suggested results are generated.

[0046] Preferably, based on the strategy determination data, a correction strategy determination is performed on different fourth-order gravitational sensitivity results to determine at least one of the following: target correction period, fourth-order correction calculation time, correction step size, and non-correction reason marker, including:

[0047] When the fourth-order gravitational sensitivity result is in a moderately sensitive state, the correction period near the task window and the correction period at the visible window boundary are generated according to the strategy determination data.

[0048] The target correction period is obtained by merging the correction period near the task window and the correction period at the visible window boundary.

[0049] Each forecast time within the target correction period is determined as a fourth-order correction calculation time, and the correction step size is determined based on the forecast step size in the available input data.

[0050] Preferably, the model adjustment trigger is used to perform model adjustment matching and determine the suggestion type, including:

[0051] The forecast confidence result, error source marker, and window boundary proximity marker are determined from the model adjustment trigger criteria.

[0052] Based on the forecast confidence results, error source markers, and window boundary proximity markers, a suggestion type matching process is performed to obtain the suggestion type.

[0053] In a second aspect, the present invention provides an electronic device including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method in the first aspect.

[0054] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method in the first aspect.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] I. This invention performs fourth-order gravitational sensitivity analysis on available input data to first determine whether the current orbital segment is easily affected by fourth-order gravity, and then decides whether fourth-order correction is needed. This helps to avoid repeated calculations for insensitive orbital segments and also helps to reduce prediction deviations caused by uncorrected sensitive orbital segments.

[0057] Second, this invention determines the fourth-order correction strategy results based on the fourth-order gravitational sensitivity results, so that the high-sensitivity orbit segment is corrected in its entirety, the medium-sensitivity orbit segment is corrected in its focus on the vicinity of the task window and the visible window boundary, and the low-sensitivity orbit segment is not corrected indiscriminately. This is beneficial to concentrate computing resources on the time period that is more likely to affect task judgment and reduce unnecessary computing burden.

[0058] Third, this invention performs correction contribution analysis on the second-order flattening baseline prediction results to obtain the fourth-order corrected orbit prediction results and the fourth-order correction contribution results. This is beneficial to directly see how much the fourth-order correction has changed the satellite position, velocity, ground trajectory and visible window, and avoids the problem of having only correction results but not being able to see the correction magnitude and correction location.

[0059] Fourth, by performing residual verification on the fourth-order corrected orbit prediction results, this invention obtains the errors of the second-order flattening baseline prediction results and the fourth-order corrected orbit prediction results, and calculates the residual improvement between the two. This helps to clearly determine whether the error has decreased after the fourth-order correction and by how much, and confirms the actual improvement effect of the fourth-order corrected orbit prediction results.

[0060] Fifth, this invention performs forecast reliability attribution analysis based on the fourth-order correction contribution results and forecast residual results, and performs model adjustment and matching based on forecast credibility results and error source results. This helps to transform forecast credibility and error sources into actionable usage suggestions, and promptly prompts for verification, supplementary observations or model replacement when forecast results are unstable, reducing the burden of manual judgment. Attached Figure Description

[0061] Figure 1 This is a flowchart of the J4 orbit prediction method of the present invention.

[0062] Figure 2 This is a comparison diagram of the effects of the present invention and the prior art. Detailed Implementation

[0063] To make the technical means, creative features, objectives, and effects of this invention easier to understand, the invention is further described below with reference to specific embodiments. However, the following embodiments are merely preferred embodiments of this invention and not all of them. Other embodiments obtained by those skilled in the art based on the embodiments described herein without creative effort are all within the protection scope of this invention.

[0064] Example 1:

[0065] To at least resolve some of the above technical issues, please refer to Figure 1 This invention provides a J4 orbit prediction method, comprising:

[0066] S1. Obtain basic track information and perform consistency verification to obtain usable input data;

[0067] S2. Perform second-order flattening extrapolation on the available input data to obtain the second-order flattening baseline forecast results;

[0068] S3. Perform a fourth-order gravitational sensitivity analysis on the available input data to obtain the fourth-order gravitational sensitivity results;

[0069] S4. Determine the results of the fourth-order correction strategy based on the fourth-order gravitational sensitivity results;

[0070] S5. Using the results of the fourth-order correction strategy as constraints, perform a correction contribution analysis on the second-order oblateness baseline forecast results to obtain the fourth-order corrected orbit forecast results and the fourth-order correction contribution results.

[0071] It should be noted that this method is executed by the processing terminal. J4 is the engineering abbreviation for fourth-order non-spherical Earth gravity, which in this embodiment represents the fourth-order perturbation effect in the Earth's non-spherical gravitational field. Among them, prediction refers to calculating the possible position, speed and operating state of the satellite in the future based on the currently known satellite orbital state.

[0072] As an alternative implementation method, in the prediction of low and medium Earth orbit satellite orbits, different data usually come from different systems. If they are directly used in the calculation, it is easy to cause prediction errors. In view of this, the present invention provides the following working method:

[0073] S1. Obtain basic track information and perform consistency verification to obtain usable input data;

[0074] The processing terminal receives initial orbit information sent by the orbit determination system. The initial orbit information includes at least one of the following: satellite identifier, position and velocity data at a reference epoch, orbital elements data, and satellite physical parameters.

[0075] Then, it receives the forecast mission information sent by the mission planning system. The forecast mission information includes mission type, forecast start time, forecast end time, forecast step size, ground station location, minimum visible elevation angle, and mission window requirements.

[0076] Subsequently, the system receives observation residual information sent by the telemetry and control system. The observation residual information is data generated by the telemetry and control system after calculating the difference between recent observation data and orbit determination results, including at least one of position residual, velocity residual and angle residual.

[0077] The processing terminal aggregates the initial orbit information, forecast mission information, and observation residual information into orbital basic information.

[0078] Finally, the processing terminal uses existing orbit data preprocessing technology to perform consistency checks on the orbital basic information. This includes checking the initial orbital information against reference epochs and performing coordinate reference transformations, as well as filtering the observation residual information within a specific time range to obtain usable input data. Data that fails the consistency check is not written into the usable input data, and an input review prompt is generated.

[0079] This reduces errors caused by mixing different reference data, ensuring that the data used in the calculation has consistent temporal and spatial meaning, which is beneficial to improving the stability of orbit prediction.

[0080] As an optional implementation, if the fourth-order corrected orbit result is directly output in the orbit prediction, it is difficult for users to determine how much the fourth-order correction changes compared to the conventional second-order oblateness prediction. In view of this, the present invention provides the following working method:

[0081] S2. Perform second-order flattening extrapolation on the available input data to obtain the second-order flattening baseline forecast results;

[0082] The processing terminal reads the forecast start time, forecast end time, and forecast step size from the available input data. Taking the forecast start time as the first time, it increments the forecast step size to the forecast end time to generate a forecast time sequence. This discretizes the continuous forecast period into calculable time points, enabling the processing terminal to calculate the orbital position, velocity, ground trajectory, and visible window at each time point.

[0083] Second-order oblateness extrapolation processing refers to using an existing second-order Earth oblateness perturbation orbit extrapolation model to recursively extrapolate the initial orbit information time-by-time. Specifically, the processing terminal reads the initial orbit information from the available input data, uses the initial orbit information as the initial extrapolation value, calculates the position and velocity time-by-time according to the forecast time sequence, and converts the orbital elements, ground trajectory, and ground station visibility window based on the position and velocity to obtain the second-order oblateness baseline forecast result. The second-order oblateness baseline forecast result includes the position data, velocity data, orbital element data, ground trajectory data, and ground station visibility window data for each forecast time.

[0084] Ground station visibility window data refers to the visible time period data calculated based on the satellite's predicted position, the ground station's position, and the lowest visible elevation angle, including at least one of the following: the time of entry into the field of view, the time of highest elevation angle, the time of exit from the field of view, and the duration of visibility.

[0085] Using the above method, the processing terminal can first obtain the second-order oblateness baseline prediction result without fourth-order gravitational correction, so that the subsequent fourth-order correction will not directly replace the original orbit extrapolation result, but will form a comparable baseline orbit at the same prediction time.

[0086] As an alternative implementation, different low- and medium-Earth orbit satellites have varying sensitivities to the fourth-order non-spherical gravity of the Earth. If the fourth-order correction is consistently applied to all orbital segments, unnecessary calculations will be added; if the fourth-order correction is not applied to any orbital segments, accumulated errors may occur near the mission window boundary. Therefore, this invention provides the following working method:

[0087] S3. Perform a fourth-order gravitational sensitivity analysis on the available input data to obtain the fourth-order gravitational sensitivity results;

[0088] Fourth-order gravitational sensitivity analysis refers to the process terminal calculating the degree of influence of the fourth-order non-spherical gravitational pull of the Earth on the current orbital segment based on changes in orbital altitude, orbital inclination, eccentricity, forecast duration, and observation residuals.

[0089] S3.1 Perform sensitive input construction on the available input data to generate sensitive analysis input quantities;

[0090] The sensitivity analysis inputs include perigee altitude, orbital inclination, eccentricity, forecast duration, and residual change.

[0091] Specifically, the processing terminal reads the semi-major axis and the eccentricity from the initial orbit information; then it calculates the perigee altitude using the following formula:

[0092] Perigee height = semi-major axis × (1 - eccentricity) - Earth reference radius.

[0093] The lower the perigee altitude, the easier it is for the effects of higher-order non-spherical gravity on the orbit to accumulate. Therefore, perigee altitude is used as an input for sensitivity assessment.

[0094] The processing terminal reads the track inclination and eccentricity from the initial track information.

[0095] Among them, orbital inclination affects the long-term perturbation of the right ascension of the ascending node and the argument of perigee by the Earth's non-spherical gravity, while eccentricity affects the orbital velocity and spatial position changes near perigee. Therefore, orbital inclination and eccentricity are used as inputs for sensitivity assessment.

[0096] The processing terminal reads the forecast start time and forecast end time from the forecast task information, and then subtracts the forecast start time from the forecast end time to determine the forecast duration. The longer the forecast duration, the easier it is for small perturbations to accumulate. Therefore, the forecast duration is used as an input for sensitivity judgment.

[0097] The processing terminal reads the position residuals arranged by time from the observation residual information, and then uses the least squares linear fitting method to calculate the slope of the position residuals as a function of time, thus obtaining the amount of residual change. The amount of residual change is used to reflect whether there is a continuous increasing trend in the recent residuals, which can avoid judging the necessity of fourth-order correction based solely on orbital parameters.

[0098] S3.2 Perform normalization processing on the sensitivity analysis input values ​​to obtain the set of sensitivity input values;

[0099] Specifically, the processing terminal normalizes the perigee altitude, orbital inclination, eccentricity, forecast duration, and residual variation to obtain a set of sensitive input values. This set includes altitude-sensitive input values, inclination-sensitive input values, eccentricity-sensitive input values, forecast duration-sensitive input values, and residual-sensitive input values. Normalization can employ range normalization to convert input data with different dimensions to a uniform value range, preventing any single type of value from dominating the judgment due to its large unit.

[0100] S3.3 Perform a weighted calculation on the set of sensitive input values ​​to obtain the sensitivity values;

[0101] Initially, the sensitivity values ​​are calculated by weighting the highly sensitive input values, tilt angle sensitive input values, eccentricity sensitive input values, duration sensitive input values, and residual sensitive input values ​​with equal weights.

[0102] Equal weighting is used because there is usually a lack of sufficiently stable historical samples of similar satellites during the initial operation phase of the system. Equal weighting can prevent the sensitivity judgment from being biased towards a single factor too early. As the trial operation samples accumulate, the weights can also be calibrated and updated. For example, when no less than 30 historical orbit prediction samples of similar satellites have been accumulated, the processing terminal uses the existing least squares fitting method, with each sensitive input value as the independent variable and the improvement in prediction error before and after the fourth-order correction as the dependent variable, to fit and obtain the calibrated weights. The weight update cycle can be set to update once after every 10 short- and medium-term orbit predictions are completed. If the number of samples is insufficient, the weights before the update will continue to be used.

[0103] S3.4. Compare the sensitivity value with the preset sensitivity judgment limit to obtain the fourth-order gravitational sensitivity result. The fourth-order gravitational sensitivity result includes one of the low-sensitivity state, medium-sensitivity state, and high-sensitivity state.

[0104] The processing terminal compares the sensitivity values ​​with the sensitivity thresholds to generate fourth-order gravitational sensitivity results. These results include low-sensitivity, medium-sensitivity, and high-sensitivity states, used to distinguish the necessity of fourth-order corrections for the current orbital segment.

[0105] Sensitivity thresholds can be determined based on the error improvement before and after fourth-order correction in historical forecast samples from similar satellites. When samples are insufficient, simulated orbit samples are used to determine the initial boundaries. For example, a sensitivity value less than 0.4 generates a low-sensitivity state, indicating that the necessity of fourth-order correction for the current orbit segment is low; a sensitivity value greater than or equal to 0.4 and less than 0.7 generates a medium-sensitivity state, indicating that the current orbit segment only needs fourth-order correction near the mission window or the boundary of the visible window; a sensitivity value greater than or equal to 0.7 generates a high-sensitivity state, indicating that the current orbit segment needs fourth-order correction for the entire forecast segment.

[0106] This implementation method can first determine whether the current orbital segment is susceptible to fourth-order gravitational influence, and then decide whether to perform fourth-order correction. This helps to avoid repeated calculations for insensitive orbital segments and also helps to reduce prediction deviations caused by the lack of correction for sensitive orbital segments.

[0107] As an optional implementation, if the fourth-order gravitational sensitivity results are only used as display information and cannot change the fixed calculation method, the present invention provides the following working method:

[0108] S4. Determine the results of the fourth-order correction strategy based on the fourth-order gravitational sensitivity results;

[0109] The fourth-order correction strategy results are correction rule data generated by the processing terminal based on the fourth-order gravity sensitivity results. These data are used to determine which forecast times to execute the fourth-order correction and at what step size.

[0110] S4.1. The strategy determination data is obtained by organizing the available input data and the second-order flattening baseline forecast results;

[0111] The strategy determination data includes the mission window requirements in the forecast mission information from the available input data and the ground station visible window data in the second-order flattening baseline forecast results.

[0112] The task window requires constraint data to represent the time limit for task execution and the allowable deviation, including at least one of the following: task window start time, task window end time, allowable time deviation, and allowable trajectory deviation.

[0113] S4.2 Based on the strategy determination data, perform correction strategy determination on different fourth-order gravitational sensitivity results, and determine at least one of the following: target correction period, fourth-order correction calculation time, correction step size, and non-correction reason marker;

[0114] When the fourth-order gravitational sensitivity result is in a highly sensitive state, the processing terminal determines the complete forecast time range from the forecast start time to the forecast end time as the target correction period, and determines each forecast time within the target correction period as the fourth-order correction calculation time.

[0115] When the fourth-order gravitational sensitivity result is in a moderately sensitive state, the processing terminal generates a target correction period based on the mission window requirements and the ground station's visible window data. Specifically, the processing terminal reads the mission window start time and mission window end time, extends the mission window start time forward by one prediction step, and extends the mission window end time backward by one prediction step to obtain the correction period near the mission window; then it reads the entry and exit times from the ground station's visible window data, extends the entry time forward by one prediction step, and extends the exit time backward by one prediction step to obtain the visible window boundary correction period; the processing terminal merges the correction period near the mission window and the visible window boundary correction period to obtain the target correction period, and determines each prediction time within the target correction period as the fourth-order correction calculation time.

[0116] It should be noted that the start and end times of the mission window, the time of entering the field of view, and the time of leaving the field of view are all boundary times. Small time or positional deviations in the orbit prediction may cause the judgment result to change from executable to inexecutable, or from visible to invisible. Extending the prediction step by one step to each side of the boundary can cover the adjacent calculation times before and after the boundary, so that the fourth-order correction is concentrated on the period most susceptible to error, while avoiding unnecessary corrections to the entire prediction segment.

[0117] When the fourth-order gravitational sensitivity result is in a low-sensitivity state, the processing terminal records the target correction period as an empty period, the fourth-order correction calculation time as empty, the correction step size as empty, and generates a non-correction reason flag; the non-correction reason flag is used to indicate that the fourth-order gravitational influence of the current orbit segment is low, and the fourth-order correction is not performed.

[0118] S4.3 Determine the results of the fourth-order correction strategy based on the target correction period, the fourth-order correction calculation time, the correction step size, and the marker for the reason for not correcting.

[0119] The processing terminal will write at least one of the determined target correction period, fourth-order correction calculation time, correction step size, and non-correction reason flag into the fourth-order correction strategy result.

[0120] In the low-sensitivity state, the fourth-order correction calculation time is empty, and the correction step size is empty.

[0121] Using the above method, the fourth-order gravitational sensitivity results directly change the fourth-order correction strategy results. The high-sensitivity orbital segment is corrected for the entire segment, the medium-sensitivity orbital segment is corrected mainly near the boundaries of the mission window and the visibility window, and the low-sensitivity orbital segment is not corrected indiscriminately. This is conducive to concentrating computing resources on the time period that is more likely to affect the mission judgment and reducing unnecessary computing burden.

[0122] As an optional implementation, if only the fourth-order corrected orbit result is output, the user can only see the satellite's future position, velocity, or changes in the visible window. To further determine how much of this change comes from the fourth-order gravitational correction and whether the fourth-order correction has indeed had a significant impact on the current orbital segment, this invention provides the following working method:

[0123] S5. Using the results of the fourth-order correction strategy as constraints, perform a correction contribution analysis on the second-order oblateness baseline forecast results to obtain the fourth-order corrected orbit forecast results and the fourth-order correction contribution results.

[0124] Correction contribution analysis refers to the process by which the processing terminal performs a fourth-order correction on the second-order flattening baseline forecast results within the time period defined by the fourth-order correction strategy, and calculates the difference before and after the correction at the same forecast time.

[0125] S5.1 Based on the results of the fourth-order correction strategy, perform data extraction on the second-order flattening baseline forecast results to determine the baseline orbit data;

[0126] The processing terminal reads the target correction period, the fourth-order correction calculation time, and the correction step size from the results of the fourth-order correction strategy.

[0127] The processing terminal extracts the position data, velocity data, ground trajectory data, and ground station visible window data corresponding to the forecast time from the second-order flattening baseline forecast results according to the target correction period and the fourth-order correction calculation time, to obtain the baseline orbit data.

[0128] Among them, the reference orbit data is the local orbit data in the second-order oblateness reference prediction results that needs to participate in the fourth-order correction calculation, and is used to represent the orbit state when the fourth-order correction has not been performed.

[0129] S5.2 Calculate the fourth-order correction sequence based on the reference orbit data and the pre-stored Earth gravity model data;

[0130] The processing terminal reads pre-stored Earth gravity model data, which includes the Earth's gravitational constant, Earth's reference radius, and fourth-order non-spherical gravitational parameters. The Earth gravity model data remains unchanged within the same orbit prediction mission cycle to ensure that the fourth-order correction calculation uses consistent physical constants.

[0131] The processing terminal reads the position data for each fourth-order correction calculation time from the reference orbit data. The position data is a three-dimensional position vector pointing from the Earth's center to the satellite. The distance between the satellite and the Earth's center is obtained by calculating the Euclidean length of the three-dimensional position vector. The Earth's center direction is then obtained by dividing the three-dimensional position vector by the distance between the satellite and the Earth's center.

[0132] Then, the position data, satellite geocentric distance, geocentric direction, and Earth gravity model data are input into the existing Earth gravity field perturbation calculation function to obtain the fourth-order perturbation acceleration. The Earth gravity field perturbation calculation function can be implemented based on a general Earth gravity field expansion model and is used to calculate the acceleration effect of the fourth-order non-spherical Earth gravity on the satellite's motion.

[0133] Subsequently, the fourth-order perturbation acceleration is numerically integrated according to the correction step size to obtain the position correction and velocity correction. The position correction represents the position shift caused by the fourth-order perturbation at the corresponding forecast time, and the velocity correction represents the velocity shift caused by the fourth-order perturbation at the corresponding forecast time.

[0134] After obtaining the correction amount, the position correction amount is added to the position data in the reference orbit data at each time step to obtain the first corrected position data. Then, using the existing coordinate transformation method, the first corrected position data is converted from geocentric inertial coordinates to geo-fixed coordinates and converted into ground latitude and longitude to obtain the first corrected ground trajectory data. Finally, the ground distance between the first corrected ground trajectory data and the ground trajectory data in the reference orbit data is calculated to obtain the ground trajectory correction amount.

[0135] The processing terminal recalculates the entry and exit times from the field of view using existing elevation angle calculation methods based on the first corrected position data, the ground station position, and the lowest visible elevation angle, thus obtaining the first corrected visible window data. The processing terminal then calculates the time difference between the first corrected visible window data and the ground station visible window data in the reference orbit data to obtain the visible window time correction.

[0136] The processing terminal writes the position correction, velocity correction, ground trajectory correction, and visibility window time correction into a fourth-order correction sequence.

[0137] In the low-sensitivity state, the target correction period in the result of the fourth-order correction strategy is empty, the processing terminal generates a zero correction amount sequence, and retains the label of the reason for not correcting.

[0138] S5.3 Add the fourth-order correction sequence to the reference orbit data at the same prediction time in the second-order flattening reference prediction results time by time to obtain the fourth-order corrected orbit prediction results;

[0139] Specifically, the processing terminal adds the position correction amount to the reference position data at the same forecast time to obtain the fourth-order corrected position data; it adds the velocity correction amount to the reference velocity data at the same forecast time to obtain the fourth-order corrected velocity data; it converts the fourth-order corrected position data to obtain the fourth-order corrected ground trajectory data; and it recalculates the fourth-order corrected visibility window data based on the fourth-order corrected position data, the ground station position, and the lowest visible elevation angle.

[0140] The processing terminal writes the fourth-order corrected position data, fourth-order corrected velocity data, fourth-order corrected ground trajectory data, and fourth-order corrected visible window data into the fourth-order corrected trajectory prediction results.

[0141] S5.4. The fourth-order corrected orbit prediction results and the second-order oblateness baseline prediction results are compared at the same prediction time to obtain the fourth-order corrected contribution results.

[0142] Specifically, the processing terminal subtracts the reference position data at the same forecast time from the fourth-order corrected position data to obtain the position difference vector, and calculates the Euclidean length of the position difference vector to obtain the position contribution.

[0143] The processing terminal subtracts the baseline velocity data at the same forecast time from the fourth-order corrected velocity data to obtain the velocity difference vector, and calculates the Euclidean length of the velocity difference vector to obtain the velocity contribution.

[0144] The processing terminal calculates the surface distance between the fourth-order corrected ground trajectory data and the baseline ground trajectory data at the same forecast time to obtain the ground trajectory contribution.

[0145] The processing terminal calculates the time difference between the fourth-order corrected visible window data and the visible window data of the reference ground station to obtain the visible window time contribution.

[0146] The processing terminal writes the position contribution, velocity contribution, ground trajectory contribution, and visible window time contribution into the fourth-order corrected contribution result.

[0147] In this embodiment, the processing terminal not only obtains the orbital state after fourth-order correction, but also the amount of change of this orbital state relative to the second-order oblateness baseline prediction result. It can directly show how much the fourth-order correction has changed the satellite's position, velocity, ground trajectory, and visibility window, and can also determine whether the fourth-order correction has an actual impact on the current orbital segment, avoiding the problem of only having correction results without showing the magnitude and location of the correction.

[0148] Example 2:

[0149] This embodiment 2 provides an improved solution based on embodiment 1. Embodiment 1 determines the fourth-order correction strategy results through fourth-order gravitational sensitivity results and generates fourth-order corrected orbit prediction results and fourth-order corrected contribution results. However, in ground station visibility window planning, mission window evaluation, and orbit control pre-prediction, it is still difficult to determine the reliability of the prediction, the source of the error, and whether the model needs to be adjusted based solely on the correction results and contribution amounts. This embodiment introduces residual verification, prediction reliability attribution analysis, and model adjustment matching mechanisms to further address the shortcomings of lacking a linkage between the reliability of orbit prediction results and the source of error. The specific implementation method is as follows:

[0150] To further address the aforementioned technical problems, this invention provides a J4 orbit prediction method, which, after obtaining the fourth-order corrected orbit prediction results and the fourth-order corrected contribution results, further includes:

[0151] S6. Perform residual verification on the fourth-order corrected trajectory prediction results to obtain the prediction residual results;

[0152] S7. Perform forecast reliability attribution analysis based on the fourth-order correction contribution results and forecast residual results to obtain forecast confidence results and error source results;

[0153] S8. Based on the forecast confidence results and error source results, perform model adjustment matching to obtain model adjustment suggestions;

[0154] S9. Integrate the fourth-order corrected orbit prediction results, fourth-order corrected contribution results, prediction confidence results, error source results, and model adjustment suggestion results to obtain the comprehensive orbit prediction results.

[0155] As an optional implementation, the fourth-order corrected orbit prediction results provide the corrected orbit state. However, without residual verification, it is still difficult for users to determine whether the corrected results have truly improved the prediction bias. Therefore, this invention provides the following working method:

[0156] S6. Perform residual verification on the fourth-order corrected trajectory prediction results to obtain the prediction residual results;

[0157] Among them, residual verification refers to the process terminal comparing the orbit prediction results with traceable verification reference data at the same prediction time and calculating the prediction error.

[0158] S6.1 Obtain the verification reference data and mark the reference source identifier for each verification reference data;

[0159] The processing terminal receives verification reference data, which comes from at least one of the following: recent observation data, post-orbit determination results, and precise orbit reference data. Recent observation data is provided by the telemetry, tracking, and command (TT&C) system; post-orbit determination results are provided by the orbit determination system; and precise orbit reference data is provided by the precise ephemeris data configured for the mission.

[0160] The reference time, reference position data, reference velocity data, reference angle data, and reference visible window time are read from the verification reference data. If the reference visible window time is not directly recorded in the verification reference data, the processing terminal can generate the reference visible window time based on the reference position data, the ground station position, and the lowest visible elevation angle using the existing elevation angle calculation method.

[0161] The processing terminal generates a reference source identifier based on the source of the verification reference data and writes the reference source identifier into the verification reference data. The reference source identifier is used to record which type of data the verification reference data comes from: recent observation data, post-orbit determination results, and precise orbit reference data.

[0162] S6.2. Perform simultaneous residual statistics on the verification reference data with the second-order oblateness baseline prediction results and the fourth-order corrected orbit prediction results to obtain the baseline residual and the corrected residual.

[0163] Among them, the residual statistics at the same time include the comparison at the same time and the root mean square statistics;

[0164] The processing terminal first reads the second-order oblateness baseline forecast results, the fourth-order corrected orbit forecast results, and the verification reference data, and then matches the data with the same forecast time according to the reference time.

[0165] The second-order flattening baseline prediction results are then compared with the verification reference data at the same time to obtain the baseline single-time residual. Specifically, for position data and velocity data, the processing terminal calculates the three-dimensional difference vector between the two and calculates the Euclidean length of the three-dimensional difference vector to obtain the baseline position residual and the baseline velocity residual, respectively; for angle data and visible window time, the processing terminal calculates the absolute difference between the two to obtain the baseline angle residual and the baseline visible window time residual, respectively.

[0166] Simultaneously, using the same same-time comparison method, the fourth-order corrected orbit prediction results are compared with the verification reference data to obtain the corrected single-time residual; wherein, the corrected single-time residual includes at least one of the corrected position residual, corrected velocity residual, corrected angle residual, and corrected visible window time residual.

[0167] Finally, root mean square (RMS) statistics were performed on the baseline single-time residuals and corrected single-time residuals for multiple forecast times to obtain the baseline residual and corrected residual. Specifically, the RMS statistics involved squaring the single-time residuals of the same residual type at multiple forecast times, calculating the average of the squared values, and then taking the square root of the average to obtain the total error of that residual type within the verification period.

[0168] S6.3 Subtract the corrected residual from the baseline residual to obtain the residual improvement.

[0169] The residual improvement is used to represent the degree of reduction in error after the fourth-order correction relative to the second-order flattening baseline forecast result.

[0170] When the residual improvement is greater than 0, it indicates that the error of the fourth-order corrected orbit prediction result is reduced compared with the second-order oblateness baseline prediction result; when the residual improvement is equal to 0, it indicates that the error before and after the fourth-order correction is basically the same; when the residual improvement is less than 0, it indicates that the error increases after the fourth-order correction.

[0171] S6.4. Write the baseline residual, corrected residual, residual improvement, and reference source identifier into the forecast residual results.

[0172] Among them, the baseline residual is used to represent the error of the second-order flattening baseline prediction result relative to the verification reference data, the correction residual is used to represent the error of the fourth-order corrected orbit prediction result relative to the verification reference data, and the residual improvement is used to represent the error change before and after the fourth-order correction.

[0173] Using the above method, the processing terminal can obtain the errors of the second-order oblateness baseline forecast and the fourth-order corrected orbit forecast, and calculate the residual improvement between the two. This allows for a clear determination of whether the error has decreased after the fourth-order correction, and by how much, which is beneficial for confirming the actual improvement effect of the fourth-order corrected orbit forecast.

[0174] As an optional implementation, fourth-order correction contribution results alone can only indicate the extent of the correction, and forecast residual results alone can only indicate the magnitude of the error. To further combine the changes brought about by fourth-order correction with the error improvement, determine the reliability of fourth-order corrected trajectory forecast results, and identify the main sources of remaining error, this invention provides the following working method:

[0175] S7. Perform forecast reliability attribution analysis based on the fourth-order correction contribution results and forecast residual results to obtain forecast confidence results and error source results;

[0176] Forecast reliability attribution analysis refers to the process of combining the fourth-order correction contribution results and forecast residual results to determine the forecast reliability state and mark the sources of remaining errors.

[0177] S7.1. Organize the available input data and the pre-stored task error configuration table into reliable parameters and generate reliable judgment data;

[0178] The processing terminal reads the mission window requirements from the available input data within the forecast mission information. The mission window requirements record the allowable time deviation and allowable trajectory deviation. The processing terminal writes the allowable time deviation as the allowable window time error into the confidence judgment data, and writes the allowable trajectory deviation as the allowable trajectory error into the confidence judgment data.

[0179] The processing terminal reads the pre-stored task error configuration table. The task error configuration table records the correspondence between task type and allowable error, scoring limit and type weight, including at least one of task type, allowable position error, allowable speed error, first scoring limit, second scoring limit and type weight.

[0180] The processing terminal reads the allowed position error, allowed speed error, first score limit, second score limit, and type weight corresponding to the current task type from the task error configuration table, and writes the allowed position error, allowed speed error, allowed trajectory error, allowed window time error, first score limit, second score limit, and type weight into the trusted judgment data.

[0181] The first and second scoring limits are used to distinguish the degree of contribution matching. They can be calculated by reading historical verification samples, calculating the contribution matching score for each sample, and determining whether the residual improvement of the sample is greater than 0. Then, the distribution of contribution matching scores among samples with residual improvement greater than 0 is statistically analyzed, and the 30th percentile is used as the first scoring limit and the 70th percentile is used as the second scoring limit. When the sample is insufficient, the first scoring limit can be 0.3 and the second scoring limit can be 0.7.

[0182] S7.2. Perform contribution matching calculations based on the fourth-order corrected contribution results and the forecast residual results to determine the contribution matching score;

[0183] The processing terminal reads the position contribution, velocity contribution, ground trajectory contribution, and visible window time contribution from the fourth-order correction contribution results; and then reads the corresponding type of residual improvement from the forecast residual results.

[0184] Taking location data as an example, the location contribution is divided by the allowable location error to obtain the normalized value of the location contribution; the improvement in location residuals is divided by the allowable location error to obtain the normalized value of the location improvement; then, the absolute value of the difference between the normalized value of the location contribution and the normalized value of the location improvement is calculated. When this absolute value is not greater than 1, the location contribution matching value is obtained by subtracting this absolute value from 1; when this absolute value is greater than 1, the location contribution matching value is recorded as 0. The closer the location contribution matching value is to 1, the more consistent the location contribution and the improvement in location residuals are, that is, the location change caused by the fourth-order correction is close to the reduction in location error; the closer the location contribution matching value is to 0, the greater the difference between the two, indicating that the reduction in location error may not be mainly caused by the fourth-order correction.

[0185] The processing terminal calculates the velocity contribution matching value, ground trajectory contribution matching value, and visible window time contribution matching value in the same way.

[0186] Subsequently, the processing terminal performs a weighted average of each contribution matching value according to the type weight to obtain the contribution matching score.

[0187] By default, position, velocity, ground trajectory, and visibility window time are weighted equally. If the task error configuration table records the priority corresponding to the task type, the processing terminal updates the type weights according to the task type; for example, if the task type is imaging, the type weights corresponding to the position contribution matching value and the ground trajectory contribution matching value are both 0.35, and the type weights corresponding to the velocity contribution matching value and the visibility window time contribution matching value are both 0.15; if the task type is telemetry and control, the type weight corresponding to the visibility window time contribution matching value is 0.40, and the weights of the other types are each 0.20. The sum of all type weights is 1.

[0188] S7.3. Perform a confidence status determination based on the confidence determination data and generate a forecast confidence result;

[0189] The processing terminal compares the corrected residuals with the corresponding permissible errors in the confidence judgment data, and compares the contribution matching score with the first and second scoring limits to generate a forecast confidence result. Specifically, the comparison conditions are as follows: when all corrected residuals involved in the judgment are no greater than the corresponding permissible error, and the contribution matching score is no lower than the second scoring limit, a high-confidence forecast result is generated, indicating that the error of the fourth-order corrected orbit forecast result is within the mission's permissible range, and the fourth-order correction contribution matches the residual improvement; when at least one type of corrected residual is greater than the corresponding permissible error but not more than 1.2 times the corresponding permissible error, and the contribution matching score is no lower than the first scoring limit, a medium-confidence forecast result is generated, indicating that the fourth-order corrected orbit forecast result is close to the mission's permissible range, but still needs to be verified in conjunction with the mission window boundaries; when the corrected residual exceeds 1.2 times the corresponding permissible error, or the contribution matching score is lower than the first scoring limit, a low-confidence forecast result is generated, indicating that the error of the fourth-order corrected orbit forecast result is too large, or the fourth-order correction contribution does not match the residual improvement.

[0190] S7.4. Based on the forecast residual results and reliable judgment data, perform error source determination and generate error source results;

[0191] The processing terminal reads the corrected single-time residuals from the forecast residual results. Each corrected single-time residual corresponds to a forecast time and represents the positional deviation between the fourth-order corrected orbit forecast result and the verification reference data at that forecast time. Using existing radial, tangential, and normal orbit coordinate decomposition methods, the corrected positional residuals at each forecast time are decomposed into radial, tangential, and normal residuals, respectively, and arranged in the order of the forecast times to obtain radial, tangential, and normal residual sequences. The radial, tangential, and normal residuals are all numerical sequences, representing positional deviations in different directions.

[0192] The processing terminal uses the least squares linear fitting method to fit the change of the tangential residual sequence with the forecast duration to obtain the tangential residual growth rate. Then, it compares the corrected single-time residual with the corresponding allowable error in the confidence judgment data, merges the forecast times that continuously exceed the corresponding allowable error to obtain high residual periods, and if there are forecast times that do not exceed the corresponding allowable error in the middle, they are divided into different high residual periods.

[0193] When the amount of correction residual exceeds the corresponding allowable error and the contribution matching score is lower than the first score limit, a fourth-order correction insufficient flag is generated, indicating that the current fourth-order correction amount is insufficient to improve the error of the track segment.

[0194] When the high residual period begins near the forecast start time and the tangential residual growth rate is lower than the growth rate judgment limit, an initial orbit error dominant marker is generated, indicating that the error is more likely to come from the inaccuracy of the initial orbit state.

[0195] When the perigee altitude is lower than the low altitude judgment limit and the tangential residual growth rate is not lower than the growth rate judgment limit, an aerodynamic drag error dominant marker is generated, indicating that the error is more likely to come from the insufficient compensation of the aerodynamic drag effect in the low orbit section.

[0196] When the high residual period coincides with the time of entering or leaving the field of view, and the time residual of the visible window exceeds the allowable window time error, a time base deviation mark is generated, indicating that the error is more likely to come from the time base deviation near the boundary of the visible window.

[0197] When the reference source is identified as recent observation data, and the trend of the corrected residual is consistent with the trend of the residual in the observation residual information, an observation residual dominant marker is generated, indicating that the error is more likely to come from fluctuations in recent observation data.

[0198] The growth rate determination limit is used to determine whether the residual continues to increase with the forecast duration. The growth rate determination limit is obtained by statistically analyzing the slope of the tangential residual as the forecast duration changes in the historical verification samples of similar satellites. For example, the median of the slope corresponding to the samples with continuously increasing residuals is used as the initial limit.

[0199] The low altitude decision limit is used to determine whether the orbital altitude is easily affected by aerodynamic drag. The low altitude decision limit is obtained by statistically analyzing the perigee altitudes of similar low-Earth orbit satellites in historical verification samples where the impact of aerodynamic drag is significantly increased. For example, the perigee altitudes of samples dominated by aerodynamic drag are arranged from low to high, and the perigee altitude at the 75th position is taken as the initial limit.

[0200] The processing terminal writes at least one of the aforementioned markers into the error source result. This allows the processing terminal to simultaneously output whether the error has decreased and where the error might originate, ensuring that the forecast results not only have a reliable state but also explain the main reasons for the low-reliability state, thus reducing the burden of manual judgment on the orbit forecast results for users.

[0201] As an optional implementation, if the forecast confidence results and error source results are only used for display, it is still difficult to determine whether the fourth-order corrected orbit forecast results can be directly used, and whether it is necessary to supplement observations, shorten the forecast duration, or switch models. In view of this, the present invention provides the following working method:

[0202] S8. Based on the forecast confidence results and error source results, perform model adjustment matching to obtain model adjustment suggestions;

[0203] Model adjustment and matching refers to the process terminal determining usage recommendations for the current orbit forecast results based on forecast credibility results, error source results, and credibility judgment data.

[0204] S8.1. Generate the model adjustment triggering basis based on the forecast credibility results, error source results, and credibility judgment data;

[0205] The processing terminal reads the forecast confidence results and determines which type of forecast results it includes: high confidence, medium confidence, and low confidence; it reads the error source results and identifies the error source markers recorded therein; it reads the allowable window time error in the confidence determination data and generates a window boundary proximity marker based on the task window start and end times, the time of entering the field of view, and the time of leaving the field of view.

[0206] The processing terminal writes the forecast confidence results, error source markers, and window boundary proximity markers into the model adjustment triggering criteria.

[0207] S8.2, Perform model adjustment matching based on the triggering basis for model adjustment, and determine the suggestion type;

[0208] When the model adjustment is triggered by high-confidence forecast results, a recommendation is generated to continue using the fourth-order corrected orbit forecast results.

[0209] When the model adjustment triggers include medium-confidence forecast results and window boundary proximity markers, a task window review suggestion is generated.

[0210] When model adjustments are triggered by low-confidence forecast results, the processing terminal determines the recommendation type based on the error source markers. Specifically, if the error source results include a marker dominated by initial orbital error or observation residual error, the processing terminal generates a recommendation to increase observation updates; if the error source results include a marker of insufficient fourth-order correction or aerodynamic drag error, the processing terminal generates a recommendation to shorten the forecast duration or switch to a higher-precision numerical model; if the error source results include a marker of time base deviation, the processing terminal generates a task window review recommendation.

[0211] S8.3 Generate model adjustment suggestion results based on suggestion type and model adjustment trigger criteria;

[0212] The processing terminal reads the high residual periods from the forecast residual results and determines the high residual periods as the applicable periods for the model adjustment suggestions; if there are no high residual periods in the forecast residual results, the forecast period is determined as the applicable period.

[0213] The processing terminal writes the suggestion type, triggering basis, and applicable time period into the model adjustment suggestion results. The model adjustment suggestion results include at least one of the following: continuing to use the fourth-order corrected orbit forecast results, mission window verification, increasing observation updates, shortening the forecast duration, and switching to a high-precision numerical model.

[0214] The model adjustment recommendations serve as supplementary information in the orbital forecast output, illustrating the applicability boundaries of the fourth-order corrected orbital forecast results. Using this approach, the processing terminal can transform forecast reliability and error sources into actionable recommendations, facilitating timely prompts for verification, supplementary observations, or model replacement when forecast results are unstable, thus reducing the burden of manual judgment.

[0215] As an optional implementation, if the trajectory results, contribution results, credibility results, and suggestion results are output separately, users still need to manually judge the relationship between the various pieces of information, which can easily lead to instability in the use of task window planning. In view of this, the present invention provides the following working method:

[0216] S9. Integrate the fourth-order corrected orbit prediction results, fourth-order corrected contribution results, prediction confidence results, error source results, and model adjustment suggestion results to obtain the comprehensive orbit prediction results.

[0217] The processing terminal establishes an integrated forecast record indexed by satellite identifier, reference epoch, and forecast period; it reads fourth-order corrected position data, fourth-order corrected velocity data, fourth-order corrected ground trajectory data, and fourth-order corrected visibility window data from the fourth-order corrected orbit forecast results and writes them into the integrated forecast record; it reads the position contribution, velocity contribution, ground trajectory contribution, and visibility window time contribution from the fourth-order corrected contribution results and writes them into the integrated forecast record; then it writes the forecast confidence result, error source result, and model adjustment suggestion result into the integrated forecast record to obtain the integrated orbit forecast result.

[0218] The comprehensive orbit forecast results record satellite identifier, reference epoch, forecast period, fourth-order corrected orbital position, orbital velocity, ground trajectory, visibility window time, fourth-order correction contribution, forecast reliability, error sources, and model adjustment recommendations.

[0219] When the integrated orbit forecast results are used for ground station visibility window planning, the processing terminal outputs the entry time into the field of view, the time of maximum elevation angle, the time of exit from the field of view, the time contribution of the visibility window, and model adjustment suggestions. When the integrated orbit forecast results are used for mission window evaluation, the processing terminal outputs the orbit position near the mission window, the ground trajectory, the forecast reliability results, and the error sources.

[0220] By adopting a centralized integration approach, orbital status, correction contribution, reliability assessment, and adjustment recommendations can be included in the same forecast result. This helps reduce usage bias caused by secondary manual assessments and makes ground station visibility window planning and mission window assessment easier to execute stably.

[0221] like Figure 2As shown, existing technologies typically focus on fixed-orbit propagation calculations, making it difficult to simultaneously reflect the necessity of fourth-order corrections, segmented correction strategies, interpretation of correction contributions, residual improvement verification, and credible attribution and model recommendations. This invention determines the results of the fourth-order correction strategy through fourth-order gravitational sensitivity analysis and combines it with correction contribution analysis, residual verification, forecast reliability attribution analysis, and model adjustment matching. This enables the orbit prediction results to not only provide the corrected orbit state but also reflect the correction magnitude, error improvement, forecast credibility, and subsequent model adjustment recommendations, thereby improving the interpretability of orbit prediction results and the stability of mission use.

[0222] The embodiments of the present invention described above are subject to modification and change of method by those skilled in the art without departing from the embodiments and broader aspects of the present invention. The appended claims are intended to include all such modifications and changes of method that do not depart from the present invention.

[0223] Those skilled in the art should understand that the embodiments of the present invention can be implemented using a pure hardware architecture, a pure software architecture, or an integrated hardware and software architecture. The present invention can be prepared as a computer program product, which can be stored in various non-volatile computer-readable storage media, including but not limited to solid-state drives, flash memory chips, mobile storage devices, optical discs, cloud storage servers, and other standardized storage media, and is not limited to traditional storage media.

[0224] Based on the foregoing description in conjunction with the accompanying drawings, those skilled in the art will understand that the embodiments of this application can also be implemented by software programs. Therefore, this application also provides a computer-readable storage medium. This computer-readable storage medium stores computer-readable instructions thereon, which, when executed by one or more processors, implement the method described above in conjunction with the accompanying drawings.

[0225] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0226] It should be noted that although the operations of the method of this application are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. On the contrary, the steps depicted in the flowchart can be performed in a different order. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0227] It should be understood that when the terms "first," "second," "third," and "fourth," etc., are used in the claims, specification, and drawings of this application, they are used only to distinguish different objects and not to describe a specific order. The terms "comprising" and "including" as used in the specification and claims of this application indicate the presence of the described features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or collections thereof.

[0228] It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application. As used in this specification and claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this specification and claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations.

[0229] Although the embodiments of this application are described above, the content is merely an example adopted for the purpose of facilitating understanding of this application and is not intended to limit the scope and application scenarios of this application. Any person skilled in the art described in this application may make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in this application, but the scope of patent protection of this application shall still be determined by the scope defined in the appended claims.

Claims

1. A J4 orbit prediction method, characterized in that, include: Obtain basic track information and perform consistency checks to obtain usable input data; Perform second-order flattening extrapolation on the available input data to obtain the second-order flattening baseline prediction result; A fourth-order gravitational sensitivity analysis was performed on the available input data to obtain the fourth-order gravitational sensitivity results; The results of the fourth-order correction strategy are determined based on the fourth-order gravitational sensitivity results. Using the results of the fourth-order correction strategy as constraints, a correction contribution analysis is performed on the second-order oblateness baseline prediction results to obtain the fourth-order corrected orbit prediction results and the fourth-order correction contribution results.

2. The J4 orbit prediction method according to claim 1, characterized in that, After obtaining the fourth-order corrected orbit prediction results and the fourth-order corrected contribution results, the following is also included: Perform residual verification on the fourth-order corrected trajectory prediction results to obtain the prediction residual results; Based on the fourth-order correction contribution results and the forecast residual results, a forecast reliability attribution analysis was performed to obtain the forecast confidence results and error source results. Based on the forecast reliability results and error source results, model adjustment matching is performed to obtain model adjustment suggestion results; By integrating the fourth-order corrected orbit prediction results, fourth-order corrected contribution results, prediction confidence results, error source results, and model adjustment suggestion results, a comprehensive orbit prediction result is obtained.

3. The J4 orbit prediction method according to claim 1, characterized in that, Perform a fourth-order gravitational sensitivity analysis on the available input data to obtain fourth-order gravitational sensitivity results, including: Sensitive input construction is performed on the available input data to generate sensitive analysis input quantities; The sensitivity analysis input values ​​are normalized to obtain a set of sensitivity input values; A weighted calculation is performed on the set of sensitive input values ​​to obtain the sensitivity values; The sensitivity value is compared with a preset sensitivity threshold to obtain a fourth-order gravitational sensitivity result, which includes one of a low-sensitivity state, a medium-sensitivity state, and a high-sensitivity state.

4. The J4 orbit prediction method according to claim 3, characterized in that, The fourth-order correction strategy results are determined based on the aforementioned fourth-order gravitational sensitivity results, including: Strategy determination data is obtained by organizing the available input data and the second-order flattening baseline forecast results; Based on the strategy determination data, a correction strategy determination is performed on different fourth-order gravitational sensitivity results to determine at least one of the target correction period, fourth-order correction calculation time, correction step size, and non-correction reason marker. The result of the fourth-order correction strategy is determined based on the target correction period, the fourth-order correction calculation time, the correction step size, and the flag indicating the reason for not correcting.

5. The J4 orbit prediction method according to claim 1, characterized in that, Using the results of the fourth-order correction strategy as constraints, a correction contribution analysis is performed on the second-order oblateness baseline prediction results to obtain the fourth-order corrected orbit prediction results and the fourth-order correction contribution results, including: Based on the results of the fourth-order correction strategy, data extraction is performed on the second-order oblateness baseline prediction results to determine the baseline orbit data; Based on the aforementioned baseline orbit data and pre-stored Earth gravity model data, calculate the fourth-order correction sequence; The fourth-order correction sequence is added to the reference orbit data at the same prediction time in the second-order flattening reference prediction result time by time to obtain the fourth-order corrected orbit prediction result. The fourth-order corrected orbit prediction result and the second-order oblateness baseline prediction result are compared at the same prediction time to obtain the fourth-order corrected contribution result.

6. The J4 orbit prediction method according to claim 2, characterized in that, Perform residual verification on the fourth-order corrected orbit prediction results to obtain prediction residual results, including: Obtain the verification reference data and mark the reference source identifier for each verification reference data; The verification reference data is compared with the second-order flattening baseline prediction result and the fourth-order corrected orbit prediction result by performing synchronous residual statistics to obtain the baseline residual and the corrected residual. Subtract the corrected residual from the baseline residual to obtain the residual improvement. The baseline residual, the corrected residual, the residual improvement, and the reference source identifier are written into the forecast residual results.

7. The J4 orbit prediction method according to claim 2, characterized in that, Based on the fourth-order correction contribution results and forecast residual results, a forecast reliability attribution analysis was performed to obtain forecast confidence results and error source results, including: The available input data and the pre-stored task error configuration table are processed to generate trustworthy judgment data by organizing the trustworthy parameters. Based on the fourth-order corrected contribution results and the predicted residual results, contribution matching calculations are performed to determine the contribution matching score; Based on the aforementioned credibility determination data, a credibility state determination is performed to generate a forecast credibility result; Based on the predicted residual results and reliable judgment data, the error source determination is performed, and the error source results are generated.

8. The J4 orbit prediction method according to claim 7, characterized in that, Based on the forecast confidence results and error source results, model adjustment matching is performed to obtain model adjustment suggestions, including: The triggering criteria for generating the model are adjusted based on the forecast credibility results, error source results, and credibility determination data. The model adjustment trigger is used to perform model adjustment matching and determine the suggestion type; Based on the suggested type and the triggering criteria for model adjustment, model adjustment suggested results are generated.

9. The J4 orbit prediction method according to claim 4, characterized in that, Based on the strategy determination data, a correction strategy is determined for different fourth-order gravitational sensitivity results, and at least one of the following is determined: target correction period, fourth-order correction calculation time, correction step size, and non-correction reason marker, including: When the fourth-order gravitational sensitivity result is in a moderately sensitive state, the correction period near the task window and the correction period at the visible window boundary are generated according to the strategy determination data. The target correction period is obtained by merging the correction period near the task window and the correction period at the visible window boundary. Each forecast time within the target correction period is determined as a fourth-order correction calculation time, and the correction step size is determined based on the forecast step size in the available input data.

10. The J4 orbit prediction method according to claim 8, characterized in that, The model adjustment trigger is based on the execution of model adjustment matching to determine the suggestion type, including: The forecast confidence result, error source marker, and window boundary proximity marker are determined from the model adjustment trigger criteria. Based on the forecast confidence results, error source markers, and window boundary proximity markers, a suggestion type matching process is performed to obtain the suggestion type.

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