A GNSS-aided lunar satellite formation release process autonomous navigation method

Abstract

The application relates to a kind of GNSS auxiliary measurement lunar satellite formation release process autonomous navigation method, comprising the following steps: in the lunar center inertial coordinate system J2000, the dynamic model of main star and substar is established;Establish and fuse the ranging model of interstellar measurement model and the GNSS signal of main star to obtain collaborative observation model;And based on the dynamic model, obtain the orbit prediction information, based on the collaborative observation model, obtain the collaborative theoretical observation information, adopt the fusion processing of extended Kalman filtering algorithm to orbit prediction information and collaborative theoretical observation information, estimate the orbit state of main star and substar.The autonomous navigation method can realize full autonomous orbit determination in orbit without relying on ground station support.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of satellites, in particular to a GNSS-assisted lunar satellite formation release process autonomous navigation method. BACKGROUND

[0002] Ultra-long wave radio astronomy observation has unique scientific value in revealing the early evolution of the universe, studying extreme astrophysical phenomena, and detecting the large-scale magnetic field structure of the universe. By deploying multiple satellite formations in the lunar orbit using the moon as a natural electromagnetic shield, high-resolution observations and precise measurements can be carried out in a low-interference electromagnetic environment. During the formation deployment process, the release of the sub-satellite from the main satellite body is a key stage in achieving the formation configuration, and its navigation accuracy directly affects the subsequent formation control and scientific mission execution effect. Therefore, the high-precision autonomous navigation capability of the release process is one of the core technologies of the formation mission.

[0003] However, the autonomous navigation of the lunar formation sub-satellite release currently still faces many challenges. On the one hand, due to the poor inter-satellite observation geometry and measurement noise at the initial stage of release, the navigation algorithm relies on inter-satellite measurement information, making it difficult to achieve stable convergence within the mission demand time (1 hour); on the other hand, existing methods usually rely on real-time orbit correction support provided by ground stations, but in the lunar orbit environment, due to the communication transmission delay and the problem of occlusion, the selection of the release window is strictly limited, significantly weakening the independence and real-time performance of the navigation system. Therefore, it is urgent to develop an autonomous navigation method that is completely independent of ground stations and has fast convergence capability to improve the orbit determination efficiency and system robustness during the formation release stage, and to meet the needs of future deep space exploration missions for high autonomy navigation. SUMMARY

[0004] The present application provides a GNSS-assisted lunar satellite formation release process autonomous navigation method, which fuses GNSS ranging information of the main satellite and combines inter-satellite measurements between the main satellite and the sub-satellite, enabling full autonomous orbit determination on-orbit without relying on ground station support, and achieving fast convergence at the initial stage of release.

[0005] A GNSS-assisted lunar satellite formation release process autonomous navigation method includes the following steps:

[0006] In the lunar center inertial coordinate system J2000, a dynamic model of the main satellite and the sub-satellite is established;

[0007] An inter-satellite measurement model and a main satellite fused GNSS signal ranging model are established and fused to obtain a collaborative observation model; and

[0008] The orbit prediction information is obtained based on a dynamic model, the cooperative observation information is obtained based on a cooperative observation model, and the orbit prediction information and the cooperative observation information are fused by using an extended Kalman filtering algorithm to estimate the orbit states of the primary star and the secondary star.

[0009] Further, in the dynamic model, the motion equation of the single star is expressed as:

[0010] ,

[0011] wherein, 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 solar gravitational perturbation and the solar pressure perturbation;

[0012] Based on the motion equation of the single star, the motion model of the absolute navigation system of the lunar satellite formation is:

[0013] ,

[0014] wherein, is the differential of the three-dimensional position of the primary star, is the differential of the three-dimensional velocity of the primary star, is the differential of the three-dimensional position of the secondary star, is the differential of the three-dimensional velocity of the secondary star.

[0015] Further, 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:

[0016] ,

[0017] wherein, is the azimuth angle information between the secondary star and the primary star, is the elevation angle information between the secondary star and the primary star, represents the inter-satellite angle measurement noise, is the y-axis position of the secondary star, is the y-axis position of the primary star, is the x-axis position of the secondary star, is the x-axis position of the primary star, is the z-axis position of the secondary star, is the z-axis position of the primary star;

[0018] The inter-satellite distance measurement model is:

[0019] ,

[0020] wherein, respectively represent the three-dimensional positions of the sub-satellite and the primary satellite, represents the inter-satellite ranging noise.

[0021] Further, the ranging model of the primary satellite fusing GNSS signals is:

[0022] ,

[0023] wherein, represents the position vectors of the two GNSS navigation satellites, represents the true range measurement between the primary satellite and the GNSS satellite, represents the GNSS ranging noise.

[0024] Further, the collaborative observation model fusing the inter-satellite measurement model and the primary satellite fusing GNSS measurement model is:

[0025] ,

[0026] wherein, and are the GNSS ranging noises when the two GNSS navigation satellites are ranging.

[0027] Further, the collaborative observation information includes the true range measurement data between the primary satellite and the GNSS satellite, the azimuth angle information between the sub-satellite and the primary satellite, the elevation angle information between the sub-satellite and the primary satellite, and the distance between the sub-satellite and the primary satellite.

[0028] Further, the orbit state prediction is performed based on the orbit states of the primary satellite and the sub-satellite at the last moment by using the dynamic model, and orbit prediction information is obtained.

[0029] The extended Kalman filtering algorithm fuses the orbit prediction information, the collaborative observation information, and the multi-source observation data in orbit observation, and obtains the absolute orbit states of the primary satellite and the sub-satellite at the current moment.

[0030] The application also provides a computer readable storage medium, which stores a computer program, wherein the computer program performs the steps of the GNSS-aided lunar satellite formation release process autonomous navigation method when executed by a processor.

[0031] The application also provides a computer system, which comprises:

[0032] a processor configured to execute machine executable instructions; and

[0033] a memory having stored thereon machine executable instructions, which, when executed by the processor, perform the steps of the GNSS-aided lunar satellite formation release process autonomous navigation method.

[0034] The application has at least the following beneficial effects:

[0035] The moon satellite formation release process autonomous navigation method of GNSS auxiliary measurement of the application obtains collaborative observation information by fusing the inter-satellite measurement model and the ranging model of the master satellite fusion GNSS signal collaborative observation model, obtains orbit prediction information based on a dynamic model, and fuses the orbit prediction information and the collaborative observation information by using an extended Kalman filtering algorithm, so as to accurately estimate the orbit state of the master satellite and the sub-satellite, significantly improve the observability of orbit estimation, realize rapid and stable convergence of navigation solution at the initial stage of release, and greatly enhance the autonomy, real-time performance and reliability of the navigation system, and has significant engineering application prospect and popularization value. BRIEF DESCRIPTION OF DRAWINGS

[0036] To further clarify the above and other advantages and features of the embodiments of the present application, a more particular description of embodiments of the application will be rendered by reference to specific embodiments thereof which are illustrated in the drawings. It is appreciated that these drawings depict only typical embodiments of the application and are therefore not to be considered limiting of its scope. The drawings show, for the purpose of clarity and understanding, identical or similar components with identical or similar reference numerals.

[0037] Figure 1 The flow of the moon satellite formation release process autonomous navigation method of GNSS auxiliary measurement according to one embodiment of the application is shown.

[0038] Figure 2 The logic diagram of the moon satellite formation release process autonomous navigation method of GNSS auxiliary measurement according to one embodiment of the application is shown.

[0039] Figure 3 The absolute position error of each satellite in the moon satellite formation according to one embodiment of the application is shown.

[0040] Figure 4 The relative position error between satellites in the moon satellite formation according to one embodiment of the application is shown. DETAILED DESCRIPTION

[0041] It should be noted that the components in the drawings can be shown exaggerated for illustration, not necessarily in proportion.

[0042] In the present application, each embodiment is only intended to illustrate the scheme of the present application, and should not be understood as limiting.

[0043] In the present application, the quantifier "one" does not exclude the scenario of multiple elements, unless specifically indicated.

[0044] It should also be noted that, in the embodiments of the present application, only a part of components or assemblies can be shown for the sake of clarity and simplicity, but those skilled in the art can understand that, under the teaching of the present application, the required components or assemblies can be added according to the specific scene.

[0045] It should also be noted that, within the scope of the present application, the words "same", "equal", "equal to" and the like do not mean that the numerical values of the two are absolutely equal, but allow a certain reasonable error, that is, the words also cover "substantially the same", "substantially equal", "substantially equal to".

[0046] It should also be noted that, in the description of the present application, the orientations or positional relationships indicated by the terms "center", "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and are not meant to imply or suggest that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, the terms "first" and "second" are only for descriptive purposes and cannot be understood as implying or suggesting relative importance.

[0047] In addition, the embodiments of the present application describe the process steps in a specific order, however, this is only for the convenience of distinguishing between steps, and is not limited to the order of the steps, and in different embodiments of the present application, the order of the steps can be adjusted according to the adjustment of the process.

[0048] Figure 1 The flow of the GNSS-assisted lunar satellite formation release process autonomous navigation method according to an embodiment of the present application is shown. Figure 2 The logic diagram of the GNSS-assisted lunar satellite formation release process autonomous navigation method according to an embodiment of the present application is shown.

[0049] As shown in Figure 1 and 2 The GNSS-assisted lunar satellite formation release process autonomous navigation method includes the following steps:

[0050] Step 1, in the lunar center inertial coordinate system J2000, a dynamic model of the main star and the sub-star is established.

[0051] In the lunar center inertial coordinate system J2000, a high-precision dynamic model of the main star and the sub-star is established, mainly considering high-order lunar non-spherical gravity perturbation, solar three-body gravity perturbation and solar radiation pressure perturbation and other perturbation effects, so as to improve the orbit propagation accuracy of the navigation algorithm. In the dynamic model, the motion equation of a single star can be expressed as:

[0052] (1),

[0053] where, is the three-dimensional position of the satellite, is the three-dimensional velocity, represents the non-spherical gravitational acceleration of the moon, represents various perturbation acceleration effects, that is, acceleration caused by the Sun-Earth-Moon gravitational perturbation and solar radiation pressure perturbation.

[0054] 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:

[0055] ,

[0056] where, is the differential of the three-dimensional position of the primary star, is the differential of the three-dimensional velocity of the primary star, is the differential of the three-dimensional position of the secondary star, is the differential of the three-dimensional velocity of the secondary star.

[0057] Step 2, establish and fuse the inter-satellite measurement model and the ranging model of the primary star fused GNSS signal to obtain the collaborative observation model.

[0058] During the release process, the secondary star optically observes the primary star to obtain angle measurement information, and the microwave ranging obtains distance measurement information.

[0059] The inter-satellite measurement model includes an inter-satellite angle measurement model and an inter-satellite distance measurement model. The inter-satellite angle measurement model is:

[0060] (2),

[0061] where, is the azimuth angle information between the secondary star and the primary star, is the elevation angle information between the secondary star and the primary star, represents the inter-satellite angle measurement noise, is the y-axis position of the secondary star, is the y-axis position of the primary star, is the x-axis position of the secondary star, is the x-axis position of the primary star, is the z-axis position of the secondary star, is the z-axis position of the primary star.

[0062] The inter-satellite distance measurement model is:

[0063] (3),

[0064] where, respectively represent the three-dimensional position of the sub-satellite and the primary satellite, represents the inter-satellite ranging noise.

[0065] The primary satellite is equipped with a GNSS receiver to obtain the true range measurement information between the primary satellite and the GNSS satellite. In addition to the above inter-satellite measurement model, the primary satellite fuses the GNSS signal ranging model as follows:

[0066] (4),

[0067] wherein, represents the position vector of the two GNSS navigation stars, represents the true range measurement between the primary satellite and the GNSS satellite, represents the GNSS ranging noise.

[0068] Fusing the inter-satellite measurement model and the primary satellite fusion GNSS measurement model, the cooperative observation model of the sub-satellite release process is as follows:

[0069] (5),

[0070] wherein, and are the GNSS ranging noise when the two GNSS navigation stars are ranging.

[0071] Step 3, based on the dynamic model shown in formula (1) to obtain the orbit prediction information, based on the cooperative observation model shown in formula (5) to obtain the cooperative theoretical observation information, using the extended Kalman filter algorithm to fuse the orbit prediction information and the cooperative theoretical observation information, and estimate the orbit state of the primary satellite and the sub-satellite.

[0072] The cooperative theoretical observation information includes the true range measurement data between the primary satellite and the GNSS satellite, the azimuth angle information between the sub-satellite and the primary satellite, the pitch angle information between the sub-satellite and the primary satellite, and the measurement distance between the sub-satellite and the primary satellite.

[0073] The extended Kalman filter inputs the orbit state of the lunar satellite formation at the last time and the multi-source observation data at the current time, and outputs the orbit state of the lunar satellite formation at the current time.

[0074] Using the dynamic model, based on the orbit state of the primary satellite and the sub-satellite at the last time, the orbit state prediction is performed to obtain the orbit prediction information at the current time. Then, the orbit prediction information, the cooperative theoretical observation information and the multi-source observation data are fused by using the extended Kalman filter algorithm to obtain a more accurate and reliable orbit state.

[0075] The extended Kalman filter is used to fuse the orbit prediction information, the cooperative theory observation information and the multi-source observation data, so that the complementarity of the dynamic priori and the observation information can be fully utilized, and the stability and convergence performance are good under the complex orbit change condition.

[0076] The fusion process of the orbit prediction result and the observation data by using the extended Kalman filter algorithm includes two steps:

[0077] 1) Time update:

[0078] ,

[0079] wherein, is the orbit state of the lunar satellite formation at the last moment, is a nonlinear state function (a function of the motion equation of the lunar satellite formation), is a state covariance matrix, is a system process noise matrix, is a state transition matrix.

[0080] 2) Measurement update:

[0081]

[0082] wherein, is multi-source observation data, is a nonlinear observation function (a cooperative observation model), is an observation matrix, is a measurement noise matrix, is a unit matrix, is the uncertainty of the state estimation, is the orbit state of the lunar satellite formation at the current moment.

[0083] Multi-source observation data include the interstellar distance, the azimuth angle and the elevation angle of each sub-satellite and the main satellite, which are obtained by real-time measurement sensors. Observation residual is the error between the multi-source observation data obtained by the measurement sensor and the cooperative theory observation information calculated by the cooperative observation model. The cooperative theory observation information includes the calculated interstellar distance, the azimuth angle and the elevation angle.

[0084] The full-autonomous navigation method of the main satellite of the application fuses GNSS auxiliary measurement, and can realize the full-autonomous navigation function of the sub-satellite release process without the participation of the ground station.

[0085] In summary, the autonomous navigation method of the lunar formation sub-satellite release process is composed of the following three parts:

[0086] (1) Establishment of a high-precision dynamic model.

[0087] In the lunar barycentric inertial coordinate system, a high-precision dynamic model of the primary satellite and the secondary satellite is constructed, and the influence of high-order non-spherical gravity, the gravity of the Sun-Earth three-body system and the solar radiation pressure and other perturbation factors is fully considered to ensure the accuracy of the orbit evolution process.

[0088] (2) Establishment of a cooperative observation model fused with GNSS signals.

[0089] A cooperative observation model fused with the GNSS auxiliary measurement of the primary satellite and the inter-satellite observation between the primary satellite and the secondary satellite is established. On the one hand, the primary satellite acquires true range measurement data from GNSS satellites through a high-gain antenna to correct its own orbit state; on the other hand, the primary satellite and the secondary satellite realize relative observation through inter-satellite ranging and angle measurement. The above two types of observation information are jointly modeled to form a unified multi-source cooperative observation model to enhance the observation redundancy and observability of the system.

[0090] (3) Multi-source information fusion and orbit state estimation.

[0091] Based on the high-precision dynamic model and the cooperative observation model fused with GNSS signals, an extended Kalman filter algorithm is used to estimate the system state in real time. Through joint processing of the GNSS observation data of the primary satellite and the inter-satellite measurement data of the primary satellite and the secondary satellite, the orbit states of the primary satellite and the secondary satellite are accurately estimated in real time.

[0092] Figure 3 The absolute position error of each satellite in the lunar satellite formation according to an embodiment of the application is shown. Figure 4 The relative position error between satellites in the lunar satellite formation according to an embodiment of the application is shown.

[0093] In the release process, it is assumed that the initial orbit error of the primary satellite is 600 m, 0.6 m / s, and the initial orbit error of the secondary satellite is 600 m, 1 m / s. The inter-satellite ranging error is 3 m ( ), and the inter-satellite angle measurement error is ( ). The GNSS auxiliary ranging accuracy of the primary satellite is 100 m ( ), and the ephemeris error is 6 m ( ). After 1 h of orbit duration simulation test, the absolute position error and the relative position error are shown in Figure 3 and 4 . The simulation results show that the navigation algorithm can quickly converge, the absolute position error is 31.731 m ( ), the absolute velocity error is 0.0279 m / s ( ); the relative position error is 7.625 m ( ), and the relative velocity error is 0.0126 m / s ( ).

[0094] In summary, the sub-satellite release process autonomous navigation method provided by the application can realize accurate autonomous orbit determination, and can provide reliable technical support for initial deployment of a lunar satellite formation.

[0095] The application further provides a computer readable storage medium, which stores a computer program, and the computer program performs the steps of the GNSS-aided lunar satellite formation release process autonomous navigation method when executed by a processor.

[0096] The application further provides a computer system, comprising:

[0097] a processor configured to execute machine executable instructions; and

[0098] a memory storing machine executable instructions, which perform the steps of the GNSS-aided lunar satellite formation release process autonomous navigation method when executed by the processor.

[0099] Although some embodiments of the application have been described in the present application, those skilled in the art can understand that these embodiments are only shown as examples. Those skilled in the art can think of numerous variations, alternatives and improvements under the teaching of the present application without departing from the scope of the present application. The appended claims are intended to define the scope of the present application, and thereby cover the methods and structures within the scope of the claims themselves and their equivalent transformations.

Claims

1. A method for autonomous navigation during the release of lunar satellite formations using GNSS-assisted measurements, characterized in that, Includes the following steps: A dynamic model of the primary star and the secondary star is established in the lunar inertial coordinate system J2000. A collaborative observation model is obtained by establishing and fusing an inter-satellite measurement model and a ranging model that integrates the primary satellite's fused GNSS signals; and Orbit prediction information is obtained based on the dynamic model, and cooperative theoretical observation information is obtained based on the cooperative observation model. The extended Kalman filter algorithm is used to fuse the orbit prediction information and the cooperative theoretical observation information to estimate the orbital state of the primary star and the secondary star. In the dynamic model, the equations of motion for a single star are expressed as: ， in, It is the satellite's three-dimensional position. It is three-dimensional velocity. Represents the non-spherical gravitational acceleration of the moon. This represents the acceleration caused by gravitational perturbations of the Sun, Earth, and Sun bodies, as well as solar radiation pressure perturbations. Based on the motion equations of a single star, the motion model of the absolute navigation system for a lunar satellite formation is as follows: ， in, It is the differential of the three-dimensional position of the primary star. It is the differential of the primary star's three-dimensional velocity. It is the differential of the three-dimensional position of the sub-star. It is the differential of the three-dimensional velocity of the sub-star; 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 as follows: ， in, This is the azimuth information between the secondary star and the primary star. It is the elevation angle information between the secondary star and the primary star. Represents inter-satellite angle measurement noise. It is the y-axis position of the sub-star. It is the y-axis position of the primary star. It is the x-axis position of the sub-star. It is the x-axis position of the primary star. It is the z-axis position of the sub-star. It is the z-axis position of the primary star; The inter-satellite distance measurement model is as follows: ， in, These represent the three-dimensional positions of the secondary star and the primary star, respectively. This indicates inter-satellite ranging noise; The ranging model for primary satellite fusion GNSS signals is as follows: ， in, Represents the position vectors of two GNSS navigation satellites. This represents the true distance measurement between the primary satellite and GNSS satellites. This represents GNSS ranging noise; The collaborative observation model that integrates the inter-satellite measurement model and the primary satellite fused GNSS measurement model is as follows: ， in, and These are the GNSS ranging noises when ranging is performed using two GNSS navigation satellites.

2. The autonomous navigation method for the release process of lunar satellite formations using GNSS-assisted measurement according to claim 1, characterized in that, The collaborative theoretical observation information includes the true distance measurement data between the primary satellite and GNSS satellites, the azimuth information between the secondary satellite and the primary satellite, the elevation information between the secondary satellite and the primary satellite, and the distance between the secondary satellite and the primary satellite.

3. The autonomous navigation method for the release process of lunar satellite formations using GNSS-assisted measurement according to claim 1, characterized in that, Using a dynamic model, orbital state prediction is performed based on the orbital states of the primary and secondary stars at the previous moment, thus obtaining orbital prediction information; The extended Kalman filter algorithm fuses orbit prediction information, cooperative theoretical observation information, and multi-source observation data from on-orbit observations to obtain the absolute orbital state of the primary and secondary stars at the current moment.

4. A computer-readable storage medium having a computer program stored thereon, the computer program performing the steps of the method according to any one of claims 1-3 when executed by a processor.

5. A computer system, comprising: A processor, which is configured to execute machine-executable instructions; as well as A memory having machine-executable instructions stored thereon, which, when executed by a processor, perform the steps of the method according to any one of claims 1-3.

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