Method for detecting physical decoupling adaptive envelope normalization maneuver based on flat spring root number

Abstract

The application discloses a physical decoupling adaptive envelope normalization maneuver detection method based on plane spring root numbers, and comprises the following steps: S1, acquiring a Cartesian state vector of a target satellite at a current time; S2, converting the Cartesian state vector into a non-singular plane spring orbit root number set; S3, performing adaptive normalization processing on a first-order difference value of each root number at the current time by using a first-order difference maximum noise envelope corresponding to each root number, and obtaining a normalized significance index of each root number; S4, based on the normalized significance index of each root number, three physically decoupled sub-detection factors are constructed; S5, the three physically decoupled sub-detection factors are compressed and fused to obtain a comprehensive maneuver detection statistic; and S6, the comprehensive maneuver detection statistic is compared with a preset detection threshold. The application can realize rapid and robust maneuver detection in a global orbit scene, especially in singular point and blind point working conditions in which classical root numbers fail.

Description

Technical Field

[0001] This invention relates to the fields of space situational awareness and satellite orbital dynamics, specifically to a physical decoupling adaptive envelope normalization maneuver detection method based on the Pingchun root. Background Technology

[0002] With the rapid development of space activities, the number of space targets is growing exponentially. Real-time and robust detection of orbital maneuvers of non-cooperative targets has become a core challenge in ensuring the safety of on-orbit assets. In engineering practice, maneuver detection methods based on classical orbital elements (COEs) are widely used, which inversely determine maneuvers by monitoring jumps in parameters such as semi-major axis, eccentricity, and orbital inclination.

[0003] However, the method based on classical roots faces fundamental theoretical obstacles when dealing with singular orbits. In near-circular orbits (… or near-equatorial orbit ( Under the condition that the argument of perigee in classical radicals is... Right ascension of ascending node Definition failures lead to severe numerical instability. Furthermore, according to the Gaussian variational equations, classical roots exhibit detection "blind spots" at specific phases, such as insensitivity to radial maneuvers at perigee / apex and insensitivity to normal maneuvers at the highest / lowest latitude points. These deficiencies make traditional methods highly susceptible to missed detections or false alarms under critical operating conditions such as GEO (Geostationary Orbit), GTO (Geosynchronous Transfer Orbit), and SSO (Sun-synchronous Orbit).

[0004] While existing filtering-based methods offer high accuracy, they suffer from high computational complexity and struggle to balance search range and estimation accuracy. Therefore, a robust, mobile detection method that can overcome geometric singularities, eliminate detection blind spots, and boast low computational cost is urgently needed. Summary of the Invention

[0005] To overcome the shortcomings of existing technologies, the present invention aims to provide a physical decoupling adaptive envelope normalization maneuver detection method based on the Pingchun radical, which can achieve fast and robust maneuver detection in the whole-domain orbit scenario, especially in the singularity and blind spot conditions where classical radicals fail.

[0006] To achieve the objectives of this invention, the following solution is adopted: The physical decoupling adaptive envelope normalization motion detection method based on the Pingchun radical includes the following steps: S1. Obtain the Cartesian state vector of the target satellite at the current moment, wherein the Cartesian state vector includes the position vector and the velocity vector; S2. Convert the Cartesian state vector into a set of non-singular flat spring orbital elements; S3. Calculate the first-order difference value of each root in the non-singular flat spring orbit root set at the current time; use the non-maneuvering historical data within the sliding time window to calculate the maximum noise envelope of the first-order difference of each root, and use the maximum noise envelope of the first-order difference of each root to perform adaptive normalization on the first-order difference value of each root at the current time to obtain the normalized significance index of each root. S4. Based on the significance index after normalization of each root number, three physically decoupled sub-detection factors are constructed, namely, energy sub-detection factor, in-plane shape sub-detection factor, and out-of-plane orientation sub-detection factor. S5. Compress and fuse the three physically decoupled sub-detection factors to obtain a comprehensive maneuver detection statistic; S6. Compare the comprehensive maneuver detection statistics with a preset detection threshold. If the comprehensive maneuver detection statistics exceed the preset detection threshold, it is determined that the target has maneuvered.

[0007] Furthermore, in step S2, the non-singular flat spring orbital element set is defined as follows: in, For the semi-major axis, For eccentricity, For the track inclination angle, The perigee argument, Right ascension of the ascending node, For longitude, and To describe the components of the eccentricity vector, and To describe the projection components of the orbital plane direction, It is the angle closest to the point.

[0008] Furthermore, in step S3, for any non-singular flat spring root state variable... Selecting a sliding time window from historical data without motor vehicles Within, calculate its first-order difference maximum noise envelope. for: in, For a historic moment The first-order difference of the non-singular flat spring orbital elements.

[0009] Furthermore, in step S3, for any non-singular flat spring root state variable... Its normalized significance index The calculation method is as follows: in, Let be the first-order difference value of the non-singular spring orbital elements at the current moment. It is the corresponding first-order difference maximum noise envelope.

[0010] Further, in step S4, the energy quantum detection factor Based on the semi-major axis The normalized significance index is constructed to characterize the change in orbital energy, and its expression is as follows: in, The semi-major axis at the current moment The first difference value, For semi-major axis The first-order difference maximum noise envelope, The semi-major axis at the current moment The first-order difference normalized value.

[0011] Further, in step S4, the in-plane shape sub-detection factor Based on eccentricity vector components and The joint norm is constructed from the normalized significance index to characterize the change in shape within the orbital plane, and its expression is: in, and These are the roots of Pingchun at the current moment. and The first difference value of , and Number of roots and The first-order difference maximum noise envelope, and The root at the current time. and The first-order difference normalized value.

[0012] Further, in step S4, the out-of-plane orientation sub-detection factor Based on the projection component of the orbital plane orientation and The joint norm is constructed from the normalized significance index to characterize the change in out-of-plane orientation, and its expression is: in, and These are the roots of Pingchun at the current moment. and The first difference value of , and Number of roots and The first-order difference maximum noise envelope, and The root at the current time. and The first-order difference normalized value.

[0013] Furthermore, in step S5, the comprehensive maneuver detection statistics... Defined as the arithmetic sum of three sub-detection factors: in, For energy quantum detection factor, In-plane shape detection factor , For out-of-plane orientation detection factors.

[0014] Furthermore, in step S6, the decision logic is as follows: in, The preset detection threshold, This indicates that the target has been determined to be maneuvering.

[0015] Furthermore, the preset detection threshold The value range is 4.0 to 5.0.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention achieves full coverage of various Earth orbits by eliminating geometric singularities. This invention converts the Cartesian state vector into a non-singular set of planar orbital elements, utilizing the planar elements in near-circular orbits (…). ) and near-equatorial orbit ( The topological stability under the condition of singularity fundamentally solves the problem of the argument of perigee of classical orbital elements in singularity conditions. Right ascension of ascending node The method defines the numerical instability problem caused by failure, making it applicable to various orbital scenarios such as geostationary orbit, geosynchronous transfer orbit, sun-synchronous orbit, and highly elliptical orbit.

[0017] 2. This invention overcomes the detection blind zone and achieves full-phase sensitive response to maneuvers in any direction. Based on the sensitivity analysis of the Gaussian variational equation with the Pingchun radical, this invention constructs three physically decoupled sub-detection factors: an energy sub-detection factor, an in-plane shape sub-detection factor, and an out-of-plane orientation sub-detection factor, utilizing... and , and Its positive interactive complementation characteristics effectively eliminate the detection blind spots of classical roots, which are insensitive to radial maneuvers at perigee / apex and to normal maneuvers at the highest / lowest latitude points, thus achieving full phase coverage of maneuvers in any direction.

[0018] 3. This invention combines high sensitivity and low false alarm rate through adaptive noise suppression. It calculates the maximum noise envelope of the first-order difference of each root using historical data within a sliding time window, and then uses this envelope to adaptively normalize the first-order difference value at the current moment. This maps roots with different physical dimensions to a dimensionless "signal-to-noise ratio space," effectively suppressing environmental interference such as atmospheric drag, J2 perturbation, and observation noise. While maintaining a low false alarm rate, it achieves a second-level rapid response for small thrust maneuvers.

[0019] 4. This invention features high computational efficiency and is suitable for real-time on-orbit applications. It employs an envelope normalization method based on historical difference statistics, eliminating the need for complex filtering iterations or high-dimensional matrix operations. The computation process is simple and efficient, meeting the requirements for real-time monitoring of space target maneuvers and demonstrating good engineering practicality. Attached Figure Description

[0020] Figure 1 This is a flowchart of the physical decoupling adaptive envelope normalization maneuver detection method based on the Pingchun root number in an embodiment of the present invention; Figure 2 This is a timing diagram of the Pingchun orbital element response for normal thrust maneuvering under the GEO double singularity condition in Experiment 1 of this invention. Figure 3 This is a timing diagram of the Pingchun orbital element response for radial thrust maneuvering under the GEO double singularity condition in Experiment 1 of this invention. Figure 4 This is the timing diagram of the Pingchun orbital element response for tangential thrust maneuvering under the GEO double singularity condition in Experiment 1 of this invention. Figure 5 This is a comparison chart of the detection performance of Experiment 2 and the classic COE benchmark algorithm in the GEO orbit radial maneuver scenario in this embodiment of the invention; Figure 6 This is a comparison chart of the detection performance of Experiment 2 and the classic COE benchmark algorithm in the GEO orbital normal maneuver scenario in this embodiment of the invention; Figure 7 This is a comparison chart of the detection performance of Experiment 2 and the classic COE benchmark algorithm in the SSO orbital radial maneuver scenario in this embodiment of the invention; Figure 8 This is a comparison chart of the detection performance of Experiment 2 and the classic COE benchmark algorithm in the GTO orbital normal maneuver scenario in this embodiment of the invention; Figure 9 This is a comparison of the detection performance of Experiment 2 and the classic COE benchmark algorithm in the radial maneuver scenario of the Molniya orbit in this embodiment of the invention; Figure 10 This is a comparison chart of the detection performance of Experiment 2 and the classic COE benchmark algorithm in the Molniya orbital normal maneuver scenario in this embodiment of the invention. Detailed Implementation

[0021] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments. It should be noted that, without conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments.

[0022] like Figure 1 As shown, this embodiment of the invention provides a physical decoupling adaptive envelope normalization maneuver detection method based on the Pingchun root, including the following steps: S1. Obtain the Cartesian state vector of the target satellite at the current moment. The Cartesian state vector includes the position vector and the velocity vector.

[0023] S2. Convert the Cartesian state vector into a set of non-singular flat spring orbital elements.

[0024] Specifically, assuming the Cartesian state vector (position) of the target is obtained in the J2000 geocentric inertial coordinate system. and speed To overcome the problem of the classical orbital elements failing to define near singularities (i.e., when the eccentricity...) hour Undefined, when the tilt angle hour (Undefined), this embodiment converts it into a non-singular set of Pingchun orbital roots. Among them, the set of slow variables Used to construct detection criteria, its definition is as follows: The above transformation guarantees that when hour, and Smoothness approaches 0; when hour, and The smoothness approaches 0, thus eliminating numerical singularities and ensuring the well-posedness of the transformation process.

[0025] S3. Calculate the first-order difference value of each root in the non-singular flat-spring orbit root set at the current time; using the non-maneuvering historical data within the sliding time window, calculate the maximum noise envelope of the first-order difference of each root, and use the maximum noise envelope of the first-order difference of each root to perform adaptive normalization processing on the first-order difference value of each root at the current time to obtain the normalized significance index of each root.

[0026] Specifically, due to the coupling effect of atmospheric drag, J2 perturbation, and observation errors, different Pingchun orbital elements (such as...) and The background noise level varies significantly under non-motorized conditions (anisotropy). To unify the dimensions and whiten the noise, this embodiment introduces a maximum noise envelope.

[0027] For any state variable Selecting a sliding time window from historical data without motor vehicles Its first-order differential noise envelope Defined as the maximum modulus of the historical differences within this window: Based on this, calculate the current time. Dimensionless significance index : This step maps variables from different physical dimensions to a unified "signal-to-noise ratio space".

[0028] S4. Based on the significance index after normalization of each root number, three physically decoupled sub-detection factors are constructed, namely, energy sub-detection factor, in-plane shape sub-detection factor, and out-of-plane orientation sub-detection factor.

[0029] Specifically, based on the sensitivity analysis of the Gaussian variational equation of the Pingchun roots, the detection features are decoupled into three orthogonal physical subspaces: 1. Energy quantum detection factor Semi-long shaft The orbital energy is independently characterized, and its normalized change directly constitutes the energy sub-factor: 2. In-plane shape sub-detection factor :Depend on and They jointly describe the eccentricity vector. This is because their responses to radial / tangential maneuvers are orthogonal. Phase relationship, joint norm to eliminate blind spots: 3. In-plane shape sub-detection factor :Depend on and They jointly describe the orbital plane normal vector. For normal maneuvers, a joint norm is constructed: S5. Compress and fuse the three physically decoupled sub-detection factors to obtain a comprehensive maneuver detection statistic.

[0030] S6. Compare the comprehensive maneuver detection statistics with a preset detection threshold. If the comprehensive maneuver detection statistics exceed the preset detection threshold, it is determined that the target has maneuvered.

[0031] Specifically, the final comprehensive testing statistics Defined as the arithmetic sum of the three sub-detection factors mentioned above: The logic behind the judgment is as follows: in The recommended range for the detection threshold is [value range missing]. Due to the use of maximum envelope normalization, the background noise baseline is strictly limited to a low level (theoretically). Therefore, this threshold can effectively distinguish between maneuvering and noise.

[0032] Experimental example: The effectiveness of the Physical Decoupling Adaptive Envelope Normalization Maneuver Detection Method (PD-AEN) based on the Spring Roots proposed in this invention is verified using the Systems Tool Kit (STK) simulation environment.

[0033] Simulation Environment and Parameter Settings: The sampling rate of all simulation data was set to 1Hz. To simulate a real, non-ideal observation environment, Gaussian white noise (position standard deviation) was superimposed on the high-precision ephemeris data (true values) generated by STK. for speed standard deviation for ).

[0034] Experiment 1: Verification of the detection response of Pingchun orbital elements to maneuvers in different directions under GEO scenario.

[0035] 1. Simulation Settings: Select the meteorological satellite GOES-18 as the simulation object, and set its orbital parameters to the semi-major axis. eccentricity track inclination This is a typical double singularity orbit. During the simulation, an acceleration of magnitude [value missing] was applied to the satellite. A thrust maneuver lasting 100 seconds.

[0036] 2. Experimental Procedure and Results Analysis: (1) Normal maneuver detection response: A continuous normal thrust was applied when the satellite passed its highest latitude point in orbit. The experimental results are as follows: Figure 2 As shown: the projected components in the Hiraharu roots at the moment the maneuver occurs. and It exhibits a significant step change, while the semi-major axis and eccentricity vector components , It remained stable and was not affected by normal maneuvers.

[0037] Technical effect: This indicates that by , Out-of-plane orientation sub-detection factor It can independently and keenly capture normal maneuvers, and overcomes the limitations of classical roots in... hour The problem of defining failure and detection blind spots at the highest latitude point.

[0038] (2) Radial and tangential motion detection response: Radial and tangential thrusts were applied at the moment the satellite passed perigee. The experimental results are as follows: Figure 3 and Figure 4 As shown: For tangential maneuvers, the semi-major axis Significant changes occur (characterizing energy changes), and at the same time and It also exhibits a significant step change. For radial maneuvering, although the semi-major axis... It is insensitive to radial forces near the perigee, but the spring element... and It still exhibits remarkable response characteristics.

[0039] Technical effect: This indicates that by The energy quantum detection factor constituted and by , In-plane shape sub-detection factor This creates complementarity. Even in geometrically inactive regions where energy changes are not significant, utilizing... , The topological stability still enables effective detection of radial maneuvers, verifying the completeness of the Pingchun radical in the GEO double singularity condition.

[0040] Experiment 2: Comparative verification of detection performance under four typical orbits.

[0041] This experiment selected four representative orbit types: geostationary orbit (GEO, double singularity), sun-synchronous orbit (SSO, near-circular singularity), geosynchronous transfer orbit (GTO, equatorial singularity), and lightning orbit (Molniya, no singularity). The robustness of the proposed method (PD-AEN) was verified by comparing it with an improved differential detection algorithm based on classical orbital elements (COEs). The detection threshold was set to... Maneuvering settings: Apply small thrust maneuvers uniformly, with an acceleration magnitude of... The duration is 100 seconds.

[0042] 1. Definition of experimental scenario: Scenario A (GEO): Simulation and A double singularity environment.

[0043] Scenario B (SSO): Simulation The near-circular orbital environment.

[0044] Scenario C (GTO): Simulation The equatorial orbital environment.

[0045] Scene D (Molniyaorbit): Simulates a singularity-free environment with large eccentricity and high tilt angle, focusing on the geometric blind zone.

[0046] 2. Experimental Procedure and Results Analysis: (1) GEO orbit test: Radial motion test results as follows Figure 5 As shown, after applying radial maneuvering, this invention achieves zero-delay detection, with the detection statistic immediately exceeding the threshold at the moment of maneuvering. In contrast, the COE comparison algorithm suffers from a detection delay of approximately 5 seconds due to limited sensitivity and noise interference in near-circular orbits.

[0047] Normal maneuver test results are as follows Figure 6 As shown, the method of this invention also achieves zero-delay detection for normal maneuvers. In contrast, the COE comparison algorithm has a detection delay of approximately 3 seconds.

[0048] (2) SSO orbit test: Radial motion test such as Figure 7 As shown, under strong perturbation conditions, when radial maneuvers are applied, the output statistics of the COE comparison algorithm never exceed the detection threshold during the maneuver, resulting in missed maneuvers. In contrast, the method of this invention effectively suppresses perturbation noise through adaptive envelope normalization. Although there is a brief delay due to noise, the maneuver is successfully detected 2 seconds after it occurs, demonstrating significant superiority.

[0049] (3) GTO orbital testing: Normal maneuver test, such as Figure 8 As shown: The method of this invention utilizes out-of-plane subplane detection factors. Zero-latency detection was achieved. Although the COE comparison algorithm can detect maneuvers, it suffers from a detection delay of approximately 3 seconds due to numerical instability.

[0050] (4) MO orbital testing: Radial and normal motion tests, such as Figure 9 and Figure 10 As shown, at these specific phase points, the maneuver signal characteristics of the COE comparison algorithm are weak and completely submerged in background noise, making detection impossible (missed detection). In contrast, the method of this invention utilizes the decoupling and complementarity characteristics of the physical subspace to eliminate the geometric detection blind zone, achieving time-delay-free detection in both radial and normal maneuver tests, demonstrating the robustness of the algorithm in the entire spatial domain.

[0051] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A physical decoupling adaptive envelope normalization motion detection method based on the Pingchun radical, characterized in that, Includes the following steps: S1. Obtain the Cartesian state vector of the target satellite at the current moment, wherein the Cartesian state vector includes the position vector and the velocity vector; S2. Convert the Cartesian state vector into a set of non-singular flat spring orbital elements; S3. Calculate the first difference of each root in the non-singular Pingchun orbit root set at the current time. Using the unmoving historical data within the sliding time window, the first-order difference maximum noise envelope of each root is calculated, and the first-order difference value of each root at the current time is adaptively normalized using the first-order difference maximum noise envelope corresponding to each root to obtain the normalized significance index of each root. S4. Based on the significance index after normalization of each root number, three physically decoupled sub-detection factors are constructed, namely, energy sub-detection factor, in-plane shape sub-detection factor, and out-of-plane orientation sub-detection factor. S5. Compress and fuse the three physically decoupled sub-detection factors to obtain a comprehensive maneuver detection statistic; S6. Compare the comprehensive maneuver detection statistics with a preset detection threshold. If the comprehensive maneuver detection statistics exceed the preset detection threshold, it is determined that the target has maneuvered.

2. The physical decoupling adaptive envelope normalization motion detection method based on the Pingchun root as described in claim 1, characterized in that, In step S2, the non-singular flat spring orbital element set is defined as follows: in, For the semi-major axis, For eccentricity, For the track inclination angle, The perigee argument, Right ascension of the ascending node, For longitude, and To describe the components of the eccentricity vector, and To describe the projection components of the orbital plane direction, It is the angle closest to the point.

3. The physical decoupling adaptive envelope normalization motion detection method based on the Pingchun root as described in claim 2, characterized in that, In step S3, for any non-singular quasi-spring root state variable Selecting a sliding time window from historical data without motor vehicles Calculate its first-order difference maximum noise envelope. : in, For a historic moment The first-order difference of the non-singular flat spring orbital elements.

4. The physical decoupling adaptive envelope normalization motion detection method based on the Pingchun root as described in claim 2, characterized in that, In step S3, for any non-singular quasi-spring root state variable Its normalized significance index The calculation method is as follows: in, Let be the first-order difference value of the non-singular spring orbital elements at the current moment. It is the corresponding first-order difference maximum noise envelope.

5. The physical decoupling adaptive envelope normalization motion detection method based on the Pingchun root as described in claim 4, characterized in that, In step S4, the energy quantum detection factor Based on the semi-major axis The normalized significance index is constructed to characterize the change in orbital energy, and its expression is as follows: in, The semi-major axis at the current moment The first difference value, For semi-major axis The first-order difference maximum noise envelope, The semi-major axis at the current moment The first-order difference normalized value.

6. The physical decoupling adaptive envelope normalization motion detection method based on the Pingchun root as described in claim 4, characterized in that, In step S4, the in-plane shape sub-detection factor Based on eccentricity vector components and The joint norm is constructed from the normalized significance index to characterize the change in shape within the orbital plane, and its expression is: in, and These are the current spring roots. and The first difference value of , and The number of roots and The first-order difference maximum noise envelope, and The root at the current time. and The first-order difference normalized value.

7. The physical decoupling adaptive envelope normalization motion detection method based on the Pingchun root as described in claim 4, characterized in that, In step S4, the out-of-plane orientation sub-detection factor Based on the projection component of the orbital plane orientation and The joint norm is constructed from the normalized significance index to characterize the change in out-of-plane orientation, and its expression is: in, and These are the current spring roots. and The first difference value of , and The number of roots and The first-order difference maximum noise envelope, and The root at the current time. and The first-order difference normalized value.

8. The physical decoupling adaptive envelope normalization motion detection method based on the Pingchun root as described in claim 1, characterized in that, In step S5, the comprehensive maneuver detection statistics Defined as the arithmetic sum of three sub-detection factors: in, For energy quantum detection factor, In-plane shape detection factor , For out-of-plane orientation sub-detection factors.

9. The physical decoupling adaptive envelope normalization maneuver detection method based on the Pingchun root as described in claim 8, characterized in that, In step S6, the decision logic is as follows: in, The preset detection threshold, This indicates that the target has been determined to be maneuvering.

10. The physical decoupling adaptive envelope normalization maneuver detection method based on the Pingchun root as described in claim 9, characterized in that, The preset detection threshold The value range is 4.0 to 5.0.

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