Autonomous navigation method for lunar satellite formation release process based on GNSS auxiliary measurement

Abstract

The invention relates to a GNSS (Global Navigation Satellite System) auxiliary measurement-based autonomous navigation method for a lunar satellite formation release process, which comprises the following steps of: establishing a kinetic model of a primary satellite and a secondary satellite under a lunar center inertial coordinate system J2000; establishing and fusing an inter-satellite measurement model and a distance measurement model of a main satellite fused GNSS signal to obtain a collaborative observation model; and acquiring orbit prediction information based on the kinetic model, acquiring collaborative theory observation information based on the collaborative observation model, performing fusion processing on the orbit prediction information and the collaborative theory observation information by adopting an extended Kalman filtering algorithm, and estimating orbit states of the primary satellite and the secondary satellites. According to the autonomous navigation method, full-autonomous orbit determination can be realized in orbit without depending on the support of a ground station.

Description

Technical Field

[0001] The present invention relates to the field of satellite technology, and in particular to an autonomous navigation method for a lunar satellite formation release process using GNSS-assisted measurement. Background Art

[0002] Ultra-long-wavelength radio astronomical observations hold unique scientific value in revealing the early evolution of the universe, studying extreme celestial phenomena, and probing the large-scale magnetic field structure of the universe. By deploying a multi-satellite formation in lunar orbit, utilizing the Moon as a natural electromagnetic shield, high-resolution observations and precise measurements can be conducted in a low-interference electromagnetic environment. During formation deployment, the release of satellites from the primary satellite is a critical step in achieving formation configuration, and their navigation accuracy directly impacts subsequent formation control and the effectiveness of scientific mission execution. Therefore, high-precision autonomous navigation capabilities during the release process are a core technology for formation missions.

[0003] However, autonomous navigation for lunar formation satellite releases still faces numerous challenges. First, due to the poor intersatellite observation geometry and measurement noise during the initial release phase, navigation algorithms rely on intersatellite measurements, making it difficult to achieve stable convergence within the mission's required timeframe (1 hour). Second, existing methods typically rely on ground stations for real-time orbit corrections. However, in the lunar orbital environment, communication transmission delays and occlusions impose strict constraints on the release window, significantly reducing the independence and real-time performance of the navigation system. Therefore, there is an urgent need to develop an autonomous navigation method that is fully independent of ground stations and possesses rapid convergence capabilities. This approach can improve orbit determination efficiency and system robustness during the formation release phase, thereby meeting the requirements for highly autonomous navigation for future deep space exploration missions. Summary of the Invention

[0004] The present invention provides an autonomous navigation method for the release process of a lunar satellite formation using GNSS-assisted measurement. By integrating GNSS ranging information with the master satellite and combining it with inter-satellite measurements between the master satellite and the sub-satellites, it is possible to achieve fully autonomous orbit determination on-orbit without relying on support from ground stations, and to achieve rapid convergence in the early stages of release.

[0005] A GNSS-assisted measurement autonomous navigation method for a lunar satellite formation release process includes the following steps: In the lunar center inertial coordinate system J2000, the dynamic model of the primary and secondary stars is established; Establish and integrate the intersatellite measurement model and the ranging model of the host satellite integrated GNSS signal to obtain a collaborative observation model; and Orbital prediction information is obtained based on the dynamic model, and collaborative theoretical observation information is obtained based on the collaborative observation model. The extended Kalman filter algorithm is used to fuse the orbital prediction information and the collaborative theoretical observation information to estimate the orbital states of the primary and secondary satellites.

[0006] Furthermore, in the dynamic model, the equation of motion of a single star is expressed as: , in, is the three-dimensional position of the satellite, is the three-dimensional velocity, represents the non-spherical gravitational acceleration of the moon, Represents the acceleration caused by the gravitational perturbation of the Sun-Earth triad and the solar light pressure perturbation; Based on the motion equation of a single satellite, the motion model of the absolute navigation system of the lunar satellite formation is: , in, is the differential of the three-dimensional position of the primary star, is the differential of the primary star's three-dimensional velocity, is the differential of the three-dimensional position of the sub-star, is the differential of the three-dimensional velocity of the sub-star.

[0007] Furthermore, the inter-satellite measurement model includes an inter-satellite angle measurement model and an inter-satellite distance measurement model, wherein the inter-satellite angle measurement model is: , in, is the azimuth information between the satellite and the main star, is the pitch angle information between the satellite and the main satellite, represents the inter-satellite angle measurement noise, is the y-axis position of the satellite, is the y-axis position of the primary star, is the x-axis position of the sub-star, is the x-axis position of the primary star, is the z-axis position of the satellite, is the z-axis position of the primary star; The intersatellite distance measurement model is: , in, Represent the three-dimensional positions of the satellite and the main star respectively, Represents the intersatellite ranging noise.

[0008] Furthermore, the ranging model of the primary satellite fused GNSS signal is: , in, Represents the position vector of two GNSS navigation stars, Represents the true distance measurement between the host satellite and the GNSS satellite, Represents the GNSS ranging noise.

[0009] Furthermore, the collaborative observation model of the fused inter-satellite measurement model and the master satellite fused GNSS measurement model is: , in, and These are the GNSS ranging noises when measuring distance using two GNSS navigation stars.

[0010] Furthermore, the collaborative theoretical observation information includes the true distance measurement data between the main satellite and the GNSS satellite, the azimuth information between the sub-satellite and the main satellite, the pitch angle information between the sub-satellite and the main satellite, and the distance between the sub-satellite and the main satellite.

[0011] Furthermore, the dynamic model is used to predict the orbital state of the primary and secondary satellites at the previous moment to obtain orbital prediction information; The extended Kalman filter algorithm integrates orbit prediction information, collaborative theoretical observation information, and multi-source observation data of on-orbit observations to obtain the absolute orbital status of the primary and secondary satellites at the current moment.

[0012] The present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the computer program performs the steps of the autonomous navigation method for the lunar satellite formation release process with GNSS-assisted measurement.

[0013] The present invention also provides a computer system, comprising: a processor configured to execute machine-executable instructions; and A memory stores machine-executable instructions, which, when executed by a processor, perform the steps of an autonomous navigation method for a lunar satellite formation release process using GNSS-assisted measurement.

[0014] The present invention has at least the following beneficial effects: The autonomous navigation method for the lunar satellite formation release process using GNSS-assisted measurement of the present invention obtains collaborative observation information through a collaborative observation model that integrates an inter-satellite measurement model and a ranging model that integrates GNSS signals of the master satellite, obtains orbit prediction information based on a dynamic model, and uses an extended Kalman filter algorithm to fuse the orbit prediction information with the collaborative observation information, accurately estimates the orbital states of the master satellite and the sub-satellite, can significantly improve the observability of the orbit estimation, and can achieve rapid and stable convergence of the navigation solution in the early stage of release. This method does not require the participation of ground stations, greatly enhances the autonomy, real-time performance and reliability of the navigation system, and has significant engineering application prospects and promotion value. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] To further illustrate the above and other advantages and features of various embodiments of the present invention, a more detailed description of various embodiments of the present invention will be presented with reference to the accompanying drawings. It will be understood that these drawings depict only typical embodiments of the present invention and are not to be considered as limiting the scope thereof. In the drawings, for clarity, identical or corresponding parts will be represented by the same or similar reference numerals.

[0016] Figure 1 The flowchart of the autonomous navigation method for the lunar satellite formation release process using GNSS-assisted measurement according to one embodiment of the present invention is shown.

[0017] Figure 2 A logical diagram of an autonomous navigation method for a lunar satellite formation release process using GNSS-assisted measurement according to an embodiment of the present invention is shown.

[0018] Figure 3 FIG. 4 shows the absolute position error of each satellite in the lunar satellite formation according to one embodiment of the present invention.

[0019] Figure 4 FIG. 4 shows the relative position errors between satellites in a lunar satellite formation according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] It should be noted that components in the drawings may be shown exaggerated for illustrative purposes and are not necessarily true to scale.

[0021] In the present invention, each embodiment is only intended to illustrate the aspects of the present invention and should not be construed as limiting.

[0022] In the present invention, unless otherwise specified, the quantifiers "a" and "an" do not exclude the presence of multiple elements.

[0023] It should also be pointed out that in the embodiments of the present invention, for the sake of clarity and simplicity, only a portion of the parts or components may be shown, but a person skilled in the art will understand that under the teachings of the present invention, the required parts or components may be added according to the needs of the specific scenario.

[0024] It should also be pointed out that within the scope of the present invention, the terms "same", "equal", "equal to" and the like do not mean that the two values ​​are absolutely equal, but allow a certain reasonable error, that is, the terms also cover "substantially the same", "substantially equal", and "substantially equal to".

[0025] It should also be noted that in the description of the present invention, the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "back," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer" and the like, indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate description and simplify the present invention. They do not explicitly or implicitly state that the devices or components referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limitations on the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0026] In addition, the embodiments of the present invention describe the process steps in a specific order, but this is only for the convenience of distinguishing the steps, and does not limit the order of the steps. In different embodiments of the present invention, the order of the steps can be adjusted according to the adjustment of the process.

[0027] Figure 1 The flowchart of the autonomous navigation method for the lunar satellite formation release process using GNSS-assisted measurement according to one embodiment of the present invention is shown. Figure 2 A logical diagram of an autonomous navigation method for a lunar satellite formation release process using GNSS-assisted measurement according to an embodiment of the present invention is shown.

[0028] like Figure 1 and 2 As shown, a GNSS-assisted measurement lunar satellite formation release process autonomous navigation method includes the following steps: Step 1: Establish the dynamic model of the primary and secondary stars in the lunar center inertial coordinate system J2000.

[0029] In the lunar-centered inertial coordinate system J2000, a high-precision dynamic model of the primary and secondary satellites was established, mainly considering the effects of high-order lunar non-spherical gravitational perturbations, the gravitational perturbations of the Sun-Earth three-body system, and the solar light pressure perturbations, in order to improve the orbit propagation accuracy of the navigation algorithm. In the dynamic model, the motion equation of a single satellite can be expressed as: (1), in, is the three-dimensional position of the satellite, is the three-dimensional velocity, represents the non-spherical gravitational acceleration of the moon, It represents the influence of various perturbation accelerations, namely the acceleration caused by the gravitational perturbation of the Sun-Earth three-body system and the perturbation of solar radiation pressure.

[0030] Based on the single-satellite motion equation shown in formula (1), the motion model of the absolute navigation system of the lunar satellite formation is: , in, is the differential of the three-dimensional position of the primary star, is the differential of the primary star's three-dimensional velocity, is the differential of the three-dimensional position of the sub-star, is the differential of the three-dimensional velocity of the sub-star.

[0031] Step 2: Establish and fuse the inter-satellite measurement model and the ranging model of the master satellite fused GNSS signal to obtain a collaborative observation model.

[0032] During the release process, the sub-star optically observes the main star to obtain angle measurement information, and uses microwave ranging to obtain distance measurement information.

[0033] The inter-satellite measurement model includes the inter-satellite angle measurement model and the inter-satellite distance measurement model. The inter-satellite angle measurement model is: (2), in, is the azimuth information between the satellite and the main star, is the pitch angle information between the satellite and the main satellite, represents the inter-satellite angle measurement noise, is the y-axis position of the satellite, is the y-axis position of the primary star, is the x-axis position of the sub-star, is the x-axis position of the primary star, is the z-axis position of the satellite, is the z-axis position of the primary star.

[0034] The intersatellite distance measurement model is: (3), in, Represent the three-dimensional positions of the satellite and the main star respectively, Represents the intersatellite ranging noise.

[0035] The GNSS receiver on the master satellite acquires the true distance measurement information between the master satellite and the GNSS satellite. In addition to the above inter-satellite measurement model, the ranging model of the master satellite fused with the GNSS signal is: (4), in, Represents the position vector of two GNSS navigation stars, Represents the true distance measurement between the host satellite and the GNSS satellite, Represents the GNSS ranging noise.

[0036] The collaborative observation model of the satellite release process is as follows: (5), in, and These are the GNSS ranging noises when measuring distance using two GNSS navigation stars.

[0037] Step 3: Obtain orbital prediction information based on the dynamic model shown in formula (1), obtain collaborative theoretical observation information based on the collaborative observation model shown in formula (5), and use the extended Kalman filter algorithm to fuse the orbital prediction information and collaborative theoretical observation information to estimate the orbital states of the primary and secondary satellites.

[0038] The collaborative theoretical observation information includes the true distance measurement data between the main satellite and the GNSS satellite, the azimuth information between the sub-satellite and the main satellite, the pitch angle information between the sub-satellite and the main satellite, and the measured distance between the sub-satellite and the main satellite.

[0039] The extended Kalman filter inputs the orbital state of the lunar satellite formation at the previous moment and the multi-source observation data at the current moment, and outputs the orbital state of the lunar satellite formation at the current moment.

[0040] Using the dynamic model, the orbital state prediction is performed based on the orbital state of the primary and secondary satellites at the previous moment, obtaining the orbital prediction information at the current moment. The orbit prediction information is then integrated with the synergistic theoretical observation information and multi-source observation data using the extended Kalman filter algorithm to obtain a more accurate and reliable orbital state.

[0041] The use of extended Kalman filtering to fuse orbit prediction information with collaborative theory observation information and multi-source observation data can fully utilize the complementarity of dynamic priors and observation information, and still maintain good stability and convergence performance under complex orbit change conditions.

[0042] The process of fusing orbit prediction results with observation data using the extended Kalman filter algorithm consists of two steps: 1) Time update: , in, is the orbital state of the lunar satellite formation at the previous moment, is a nonlinear state function (the motion equation function of the lunar satellite formation), is the state covariance matrix, is the system process noise matrix, is the state transition matrix.

[0043] 2) Measurement update: in, is multi-source observation data, is a nonlinear observation function (cooperative observation model), is the observation matrix, is the measurement noise matrix, is the identity matrix, is the uncertainty of the state estimate, is the orbital state of the lunar satellite formation at the current moment.

[0044] Multi-source observation data The distance, azimuth and elevation angle between each satellite and the main satellite are obtained through real-time measurement sensors. It refers to the error between the multi-source observation data obtained by the measurement sensor and the collaborative theoretical observation information calculated by the collaborative observation model. The collaborative theoretical observation information includes the calculated inter-satellite distance, azimuth and elevation angle.

[0045] The fully autonomous navigation method for main satellite integrated GNSS-assisted measurement of the present invention can realize the fully autonomous navigation function of the sub-satellite release process without the participation of ground stations.

[0046] In summary, the autonomous navigation method for the lunar formation satellite release process consists of the following three parts: (1) Establishment of high-precision dynamic model.

[0047] In the lunar-centered inertial coordinate system, a high-precision dynamic model of the primary and secondary stars is constructed, fully considering the influence of perturbation factors such as high-order non-spherical gravity, the three-body gravity of the Sun and the Earth, and solar light pressure to ensure the accuracy of the orbital evolution process.

[0048] (2) Establishment of collaborative observation model integrating GNSS signals.

[0049] A collaborative observation model is established that integrates GNSS-assisted measurements from the primary satellite and intersatellite observations between the primary and secondary satellites. The primary satellite, equipped with a high-gain antenna, acquires true range measurement data from GNSS satellites to correct its own orbital state. Furthermore, intersatellite ranging and angle measurements are used to achieve relative observation between the primary and secondary satellites. These two types of observation information are jointly modeled to form a unified multi-source collaborative observation model, enhancing the system's observation redundancy and observability.

[0050] (3) Multi-source information fusion and orbit state estimation.

[0051] Based on a high-precision dynamic model and a collaborative observation model that integrates GNSS signals, the extended Kalman filter algorithm is used to estimate the system state in real time. By jointly processing the GNSS observation data of the primary satellite and the measurement data between the primary satellite and the satellite, the orbital state of the primary and satellite satellites can be accurately estimated in real time.

[0052] Figure 3FIG. 4 shows the absolute position error of each satellite in the lunar satellite formation according to one embodiment of the present invention. Figure 4 FIG. 4 shows the relative position errors between satellites in a lunar satellite formation according to an embodiment of the present invention.

[0053] During the release process, it is assumed that the initial orbital error of the main satellite is 600m, 0.6m / s, and the initial orbital error of the sub-satellite is 600m, 1m / s. The inter-satellite ranging error is 3m ( ), the inter-satellite angle measurement error is ( The main satellite GNSS assisted ranging accuracy is 100m ( ), the ephemeris error is 6m ( After 1h track duration simulation test, the absolute position error and relative position error are as follows Figure 3 and 4 The simulation results show that the navigation algorithm can converge quickly, and the absolute position error is 31.731m ( ), the absolute speed error is 0.0279m / s ( ); The relative position error is 7.625m ( ), the relative speed error is 0.0126m / s ( ).

[0054] In summary, the autonomous navigation method for the satellite release process proposed in the present invention can achieve accurate autonomous orbit determination and provide reliable technical support for the initial deployment of the lunar satellite formation.

[0055] The present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the computer program performs the steps of the autonomous navigation method for the lunar satellite formation release process with GNSS-assisted measurement.

[0056] The present invention also provides a computer system, comprising: a processor configured to execute machine-executable instructions; and A memory stores machine-executable instructions, which, when executed by a processor, perform the steps of an autonomous navigation method for a lunar satellite formation release process using GNSS-assisted measurement.

[0057] Although certain embodiments of the present invention have been described in this application, those skilled in the art will appreciate that these embodiments are provided by way of example only. Numerous variations, alternatives, and modifications will be contemplated by those skilled in the art in light of the teachings of this disclosure without departing from the scope of the present invention. The appended claims are intended to define the scope of the present invention and are intended to encompass methods and structures within the scope of these claims and their equivalents.

Claims

1. A GNSS-assisted measurement method for autonomous navigation of lunar satellite formation release process, characterized in that: The steps include: In the lunar center inertial coordinate system J2000, the dynamic model of the primary and secondary stars is established; Establish and integrate the intersatellite measurement model and the ranging model of the host satellite integrated GNSS signal to obtain a collaborative observation model; and Orbital prediction information is obtained based on the dynamic model, and collaborative theoretical observation information is obtained based on the collaborative observation model. The extended Kalman filter algorithm is used to fuse the orbital prediction information and the collaborative theoretical observation information to estimate the orbital states of the primary and secondary satellites.

2. The autonomous navigation method for the lunar satellite formation release process using GNSS-assisted measurement according to claim 1, characterized in that: In the dynamic model, the equation of motion of a single star is expressed as: ， in, is the three-dimensional position of the satellite, is the three-dimensional velocity, represents the non-spherical gravitational acceleration of the moon, Represents the acceleration caused by the gravitational perturbation of the Sun-Earth triad and the solar light pressure perturbation; Based on the motion equation of a single satellite, the motion model of the absolute navigation system of the lunar satellite formation is: ， in, is the differential of the three-dimensional position of the primary star, is the differential of the primary star's three-dimensional velocity, is the differential of the three-dimensional position of the sub-star, is the differential of the three-dimensional velocity of the sub-star.

3. The autonomous navigation method for the lunar satellite formation release process using GNSS-assisted measurement according to claim 1, characterized in that: The inter-satellite measurement model includes the inter-satellite angle measurement model and the inter-satellite distance measurement model, wherein the inter-satellite angle measurement model is: ， in, is the azimuth information between the satellite and the main star, is the pitch angle information between the satellite and the main satellite, represents the inter-satellite angle measurement noise, is the y-axis position of the satellite, is the y-axis position of the primary star, is the x-axis position of the sub-star, is the x-axis position of the primary star, is the z-axis position of the satellite, is the z-axis position of the primary star; The intersatellite distance measurement model is: ， in, Represent the three-dimensional positions of the satellite and the main star respectively, Represents the intersatellite ranging noise.

4. The autonomous navigation method for the lunar satellite formation release process using GNSS-assisted measurement according to claim 3, characterized in that: The ranging model of the primary satellite fused GNSS signal is: ， in, Represents the position vector of two GNSS navigation stars, Represents the true distance measurement between the host satellite and the GNSS satellite, Represents the GNSS ranging noise.

5. The autonomous navigation method for the lunar satellite formation release process using GNSS-assisted measurement according to claim 4, characterized in that: The collaborative observation model of the fused inter-satellite measurement model and the master satellite fused GNSS measurement model is: ， in, and These are the GNSS ranging noises when measuring distance using two GNSS navigation stars.

6. The autonomous navigation method for the lunar satellite formation release process using GNSS-assisted measurement according to claim 1, characterized in that: The collaborative theoretical observation information includes the true distance measurement data between the main satellite and the GNSS satellite, the azimuth information between the sub-satellite and the main satellite, the pitch angle information between the sub-satellite and the main satellite, and the distance between the sub-satellite and the main satellite.

7. The autonomous navigation method for the lunar satellite formation release process using GNSS-assisted measurement according to claim 1, characterized in that: Using the dynamic model, the orbital state prediction is performed based on the orbital state of the primary and secondary stars at the previous moment to obtain orbital prediction information; The extended Kalman filter algorithm integrates orbit prediction information, collaborative theoretical observation information, and multi-source observation data of on-orbit observations to obtain the absolute orbital status of the primary and secondary satellites at the current moment.

8. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the computer program performs the steps of the method according to any one of claims 1 to 7.

9. A computer system comprising: a processor configured to execute machine-executable instructions; as well as A memory having machine executable instructions stored thereon, wherein the machine executable instructions, when executed by a processor, perform the steps of the method according to any one of claims 1 to 7.

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