CN110553653B - Spacecraft orbit determination method based on multi-source data driving - Google Patents

Spacecraft orbit determination method based on multi-source data driving Download PDF

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CN110553653B
CN110553653B CN201910784795.2A CN201910784795A CN110553653B CN 110553653 B CN110553653 B CN 110553653B CN 201910784795 A CN201910784795 A CN 201910784795A CN 110553653 B CN110553653 B CN 110553653B
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杨盛庆
贾艳胜
杜耀珂
王文妍
王禹
刘美师
王嘉轶
吴敬玉
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Shanghai Aerospace Control Technology Institute
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/24Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for cosmonautical navigation
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
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    • G01S19/35Constructional details or hardware or software details of the signal processing chain
    • G01S19/37Hardware or software details of the signal processing chain
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42Determining position

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Abstract

The invention discloses a spacecraft orbit determination method based on multi-source data driving, which comprises the following steps: performing orbit data preprocessing on GNSS measurement data; converting a coordinate system of the GNSS measurement data; maintaining system time at the filtering moment and the satellite-borne computer running moment, and performing time compensation on orbit data obtained by filtering; constructing a navigation filtering algorithm, and using a calculation result of the EKF filter as a master scheme determined by the spacecraft orbit; determining the position and speed information of an inertial system of the spacecraft orbit, and converting the position and speed information to obtain instantaneous orbit parameters and orbit flat number; judging the stability of navigation filtering aiming at the flat number of the track; using an orbit recursion algorithm as a backup scheme for spacecraft orbit determination; and designing switching logic between the main backup schemes according to the working state of the GNSS measurement system. The invention overcomes the influence of noise error generated by a GNSS measurement system and time deviation between satellite platform subsystems, and provides high-precision space-time reference for an attitude and orbit control system.

Description

Spacecraft orbit determination method based on multi-source data driving
Technical Field
The invention relates to the field of spacecraft engineering technology application, in particular to a spacecraft orbit determination method based on multi-source data driving, and more particularly to a method for determining a spacecraft orbit by using a filtering algorithm or an orbit recursion algorithm aiming at real-time orbit information acquired by a Global Navigation Satellite System (GNSS) and reference time orbit parameters acquired by a ground orbit determination; compared with a mode of directly using the GNSS system measurement value, the spacecraft orbit determination method designed by the invention can obtain a space-time reference with higher precision.
Background
The orbit determination of the in-orbit spacecraft can be based on real-time measurement data of a GNSS system or forecast acquisition of an orbit recursion algorithm. In the two modes, the accuracy of the GNSS real-time measurement data is higher, but the time deviation among subsystems of the satellite platform exists, so that the attitude determination is influenced. The orbit prediction precision of the orbit recursion algorithm is relatively poor, and the algorithm can be used as a backup scheme for spacecraft orbit determination considering that the stability is good and the algorithm is not influenced by time deviation among subsystems. At present, for a spacecraft orbit determination method based on multi-source data driving of an attitude and orbit control system, no published patent or paper and other research results exist.
Disclosure of Invention
The invention aims to provide a spacecraft orbit determination method based on multi-source data driving, which can overcome the influence of time deviation among subsystems of a satellite platform on orbit determination; compared with a mode of directly using the GNSS system measurement value or using an orbit recursion algorithm, the new method can provide a higher-precision space-time reference for the attitude and orbit control system.
In order to achieve the purpose, the invention is realized by the following technical scheme:
a spacecraft orbit determination method based on multi-source data driving comprises the following processes: track data preprocessing is carried out on GNSS measurement data, and error data are eliminated; performing coordinate system conversion on the preprocessed GNSS measurement data; maintaining system time at the filtering time and the satellite-borne computer operation time, and performing time compensation on the orbit data obtained by filtering; constructing a navigation filtering algorithm, and using a calculation result of the EKF filter as a master scheme determined by the spacecraft orbit; determining the position and speed information of an inertial system of the spacecraft orbit, and converting to obtain instantaneous orbit parameters and orbit average number; judging the stability of navigation filtering aiming at the flat number of the track; using an orbit recursion algorithm as a backup scheme for spacecraft orbit determination; and providing switching logic between the master scheme and the backup scheme according to the working state of the GNSS measurement system.
Preferably, the orbit data preprocessing comprises the following processes:
according to the dynamic characteristics of the track, a threshold judgment formula is set as follows:
6.79×106m≤||r||≤7.05×106m and 7.46X 103m/s≤||v||≤7.75×103m/s
Figure BDA0002177700800000021
Wherein, x, y and z are triaxial position data measured by the GNSS receiver respectively; vx, vy and vz are triaxial speed data measured by the GNSS receiver respectively;
measurement inputs that are outside of the threshold range are rejected as erroneous data.
Preferably, the J2000.0 coordinate required by filtering is accessed, and the coordinate conversion process comprises time conversion and calculation of the time difference RPNutating RNPolar motion RMAnd a rotation matrix RSThe following can be obtained:
RJ2000=(RMRSRNRP)-1R84
Figure BDA0002177700800000022
in the formula, RJ2000Position data in the J2000.0 coordinate system; v. ofJ2000Velocity data for the J2000.0 coordinate system; r84Position data in WGS84 coordinate system; v. of84Velocity data in the WGS84 coordinate system.
Preferably, the navigation filtering algorithm comprises:
the standard EKF filtering algorithm is used, and the absolute navigation filtering operation of each beat comprises the position and the speed of the previous beat in the inertial system
Figure BDA0002177700800000023
Error covariance matrix P of previous beat statek-1Absolute position and speed data Z measured in real time by a system state noise covariance matrix Q and a measurement noise covariance matrix R, GNSSkThe output is the position and the speed of the current beat under the inertial system
Figure BDA0002177700800000024
Covariance matrix P with current beat state errorkThe calculation process is as follows:
(1) from the previous beat state
Figure BDA0002177700800000025
Performing state quantity prediction
Figure BDA0002177700800000026
Previous beat state of algorithm input
Figure BDA0002177700800000031
Is position and velocity under the inertial system
Figure BDA0002177700800000032
Is recorded as [ x y z v ]x vy vz]TAnd dX ═ f (x) expression is as follows:
Figure BDA0002177700800000033
wherein,
Figure BDA0002177700800000034
Figure BDA0002177700800000035
Figure BDA0002177700800000036
Figure BDA0002177700800000037
Figure BDA0002177700800000038
Figure BDA0002177700800000039
in the formula, r is a position module value of the satellite J2000.0 in an inertial coordinate system; x ═ X y z vx vy vz]TRefers to the position and the speed of the satellite J2000.0 in an inertial coordinate system; μ represents the earth gravity constant; a isJ2、aJ3、aJ4Represents perturbation accelerations of J2, J3 and J4 items respectively; rEIs the radius of the earth; Δ t means a time difference;
(2) solving for Pk/k-1The following are:
Figure BDA00021777008000000310
Φk,k-1=I+Fk-1Δt;
Figure BDA0002177700800000041
in the formula, I is a unit array; phik,k-1Representing a state matrix; q represents a system state noise covariance matrix; pk-1Representing a state error matrix;
(3) calculating a filter gain KK,KKIs equal to Pk/k-1(Pk/k-1+R)-1
(4) Completion state quantity estimation
Figure BDA0002177700800000042
Figure BDA0002177700800000043
Is equal to
Figure BDA0002177700800000044
(5) Completion state error matrix PkUpdate, PkIs equal to (I-K)k)Pk/k-1
Preferably, in the process of determining the stability of the navigation filter for the flat number of the track, the method further includes: storing the average number of the track, sampling every M seconds, taking the first N average semi-major axis sampling points, and calculating the average value of the average semi-major axis
Figure BDA0002177700800000045
As the average of the current beat semimajor axis; when the number of the points is less than N, the average value of the current number of the flat semi-major axes is obtained; and clearing all data for recalculation each time the absolute navigation based on the GNSS data is accessed again.
Preferably, the stability criterion of the absolute navigation is: when the N average semimajor axis sampling points are fully collected, if the module value meeting the difference of the average values of the front and back beat semimajor axes in the calculation period of 10 continuous spaceborne computers is smaller than the stability judgment threshold value adhIf so, judging that the absolute navigation filtering is stable; threshold value a for stability judgmentdhThe number of notes can be modified.
Preferably, in the logic process of switching between the master backup scheme and the backup scheme, the method further includes:
starting a backup scheme determined by a spacecraft orbit when the GNSS receiver data are unavailable for a long time, and restarting absolute navigation filtering if the GNSS receiver has data again and the data are valid within a certain continuous time;
determining orbit data of an access system according to the current working mode; when the working mode is to forcibly use the GNSS, the result of the navigation filtering is accessed into the system; and if the working mode is on-satellite autonomous, accessing the orbit data of the backup scheme into the system.
Compared with the prior art, the invention has the beneficial effects that: the method can overcome the influence of time deviation among subsystems of the satellite platform on the orbit determination; compared with a mode of directly using the GNSS system measurement value or using an orbit recursion algorithm, the new method can provide a higher-precision space-time reference for the attitude and orbit control system.
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FIG. 1 is a flow chart of a multi-source data-driven spacecraft orbit determination method of the present invention;
FIG. 2 is a flow chart of an EKF filter design of a navigation filtering algorithm of the present invention;
FIG. 3 is a schematic diagram of the position error of the navigation filtering algorithm of the present invention;
FIG. 4 is a velocity error diagram of the navigation filter algorithm of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1 to 4, the present invention provides a method for determining a spacecraft orbit based on multi-source data driving, which comprises the following steps:
step S1, orbit data preprocessing is carried out on the GNSS measurement data, threshold judgment is combined, and error data are eliminated.
In step S1, the track data preprocessing includes the following steps:
according to the dynamic characteristics of the track, a threshold judgment formula is set as follows:
6.79×106m≤||r||≤7.05×106m and 7.46X 103m/s≤||v||≤7.75×103m/s
Figure BDA0002177700800000051
The GNSS receiver is used for measuring the three-axis position data, and the x, y and z are respectively three-axis speed data measured by the GNSS receiver. And the measurement input exceeding the threshold range is removed as error data, and the calculation of navigation filtering is not introduced.
Step S2, converting the coordinate system of the preprocessed GNSS measurement data, and converting the WGS84 coordinate (WGS84 is a coordinate system established by the GPS global positioning system) measured by the GNSS receiver into the J2000.0 coordinate required by the access dynamics navigation filtering.
In step S2, the coordinate system conversion includes:
the GNSS receiver provides data in WGS84 coordinate system, and needs to be converted to J2000.0 coordinate system before filter is switched in, and the coordinate conversion process comprises time conversion and calculation of the time difference RPNutating RNPolar motion RMAnd a rotation matrix RSEtc.; the following can be obtained:
RJ2000=(RMRSRNRP)-1R84
Figure BDA0002177700800000061
in the formula, RJ2000Position data, v, for the J2000.0 coordinate systemJ2000Speed data for the J2000.0 coordinate System, R84Position data, v, being the WGS84 coordinate system84Velocity data in the WGS84 coordinate system.
In step S3, the orbit data is a fast variable with respect to time, and a mismatch between time and position and speed information may result in distortion of the orbit determination result. The satellite-borne software designs a plurality of time systems, system time maintenance is carried out on filtering time and satellite-borne computer running time, and time compensation is carried out on orbit data obtained through filtering, because the orbit data are fast variables related to time, and the track determination result is distorted due to mismatching of time, position and speed. A plurality of time systems are designed on the satellite for maintenance and compensation, so that the matching between the orbit and the time can be ensured.
In step S3, the system time maintenance includes the following:
a) the orbit determination of the spacecraft is greatly influenced by time, and time deviation possibly exists among subsystems of a satellite platform, so that a navigation filtering algorithm based on GNSS orbit data is designed, and a filtering time axis is maintained; the maintenance method of the filtering time comprises the steps of designing time calibration in a bus GNSS data packet received at the filtering time, and for the condition that the GNSS data packet is interrupted, cumulatively increasing the filtering time according to the operation cycle duration of an on-board computer;
b) and (3) outputting navigation filtering, wherein due to the time deviation between the satellite-borne computer running time and the filtering time, the track parameters obtained by filtering need to be complemented to the satellite-borne computer running time, so that a higher space-time reference is provided for attitude determination.
And S4, constructing a navigation filtering algorithm, and using the calculation result of the EKF filter (namely, the extended Kalman filter) as a master scheme for determining the spacecraft orbit.
As shown in fig. 2, in step S4, the navigation filter algorithm includes:
the standard EKF filtering algorithm is used, and the absolute navigation filtering operation of each beat comprises the position and the speed of the previous beat in the inertial system
Figure BDA0002177700800000062
Error covariance matrix P of previous beat statek-1The system state noise covariance matrix Q (constant matrix), the measurement noise covariance matrix R (constant matrix), and the absolute position speed data Z of GNSS real-time measurementkThe output is the position and the speed of the current beat under the inertial system
Figure BDA0002177700800000063
Covariance matrix P with current beat state errorkThe calculation process is as follows:
a) from the previous beat state
Figure BDA0002177700800000071
Performing state quantity prediction
Figure BDA0002177700800000072
Previous beat state of algorithm input
Figure BDA0002177700800000073
Is position and velocity under inertia system
Figure BDA0002177700800000074
The expression dX ═ f (x) is as follows:
Figure BDA0002177700800000075
wherein
Figure BDA0002177700800000076
Figure BDA0002177700800000077
Figure BDA0002177700800000078
Figure BDA0002177700800000079
Figure BDA00021777008000000710
Figure BDA00021777008000000711
In the formula, | r | | | refers to a lower position module value of the inertial coordinate system of the satellite J2000.0, and the unit is m;
X=[x y z vx vy vz]Tthe unit is m/s, which is the lower position velocity of the inertial coordinate system of the satellite J2000.0;
μ denotes the earth's gravitational constant, 3.986005 × 1014m3/s2
aJ2、aJ3、aJ4Respectively representing perturbation acceleration of J2, J3 and J4 (industry standard name, which is a representation of model order) with the unit of m/s2;J2Is 1.082636X 10-3;J3Is-2.5356 x 10-6;J4Is-1.62336 x 10-6;REIs the earth radius, 6378140 m.
b) Solving for Pk/k-1The following are:
Figure BDA00021777008000000712
Φk,k-1=I+Fk-1Δt;
Figure BDA0002177700800000081
in the formula, I is a unit array; phik,k-1Representing a state matrix, dimensionless; q represents a system state noise covariance matrix and is dimensionless; pk-1Representing a state error matrix, dimensionless;
c) calculating a filter gain KK,Kk=Pk/k-1(Pk/k-1+R)-1
d) Completion state quantity estimation
Figure BDA0002177700800000082
Figure BDA0002177700800000083
It is to be noted that ZkAbsolute position and speed data measured in real time by GNSS, if no absolute position and speed data exists in the current beat, KkTaking 0;
e) completion state error matrix PkUpdate, Pk=(I-Kk)Pk/k-1
Fig. 3 shows the position error of the navigation filter algorithm of the present invention and fig. 4 shows the velocity error of the navigation filter algorithm of the present invention.
And step S5, converting the position and speed information of the inertial system determined by the spacecraft orbit to obtain instantaneous orbit parameters and orbit average number.
The step S5 further includes: and (4) with reference to the position and the speed of the classical inertial system to the orbit transient root, iteratively calculating a short period term by the orbit transient root so as to obtain the orbit flat root. And the subsequent stability judgment of the navigation filtering is mainly carried out based on the track flat root. The specific operation of this step is an industry standard operation, and is not described in detail.
And step S6, judging the stability of the navigation filter aiming at the track flat number.
In step S6, the following data structure design is performed based on the navigation filter stability determination of the number of flat tracks: the attitude and orbit control management unit stores the rail average number, samples the rail average number once every M seconds, and obtains the average value of the average semimajor axis by taking the first N sampling points of the average semimajor axis
Figure BDA0002177700800000084
As the average of the current beat semimajor axis; if the number of the sampling points is less than N, the number of the sampling points of the existing flat semi-major axis is taken to obtain an average value; and clearing all data for recalculation each time the absolute navigation based on the GNSS data is accessed again.
Wherein the absolute navigation stability criterion is as follows: when the N average semi-major axis sampling points are fully collected, if the module value meeting the difference of the average values of the front and back beat semi-major axes in the calculation period of 10 continuous spaceborne computers is smaller than the threshold value, the absolute navigation filtering is judged to be stable; a isdhTo judge the stability threshold, canAnd (5) modifying the notes. The purpose of the absolute navigation stability criterion in this step is to determine absolute navigation stability, for example, a single beat determination is performed in a calculation cycle (0.5s) of each spaceborne computer, and when 10 beats continuously meet the criterion, the determination is made as stable.
Step S7, using an orbit recursion algorithm as a backup scheme for spacecraft orbit determination (i.e. selection when the master scheme fails, and an orbit recursion algorithm is used for general satellite navigation), and providing basic orbit information when GNSS measurement data is invalid for a long time.
In step S7, the track recursion algorithm includes the following steps:
the orbit recursion algorithm is that after a group of initial roots of the in-orbit satellite is obtained (or obtained by other methods) at a ground observation station, the orbit roots of the satellite at the future moment are calculated by utilizing an orbit model of the satellite motion; an appropriate mathematical model is necessary for calculating the orbit number in real time on the satellite, the model is usually based on a plurality of carefully designed fixed parameters, the parameters are fitted by a ground tracking system according to the accurate orbit measurement result and are injected to the satellite periodically, and an orbit recursion algorithm can be used as a backup scheme for determining the orbit of the spacecraft.
Step S8, according to the working state of the GNSS measurement system, a track is designed to determine the switching logic between the master scheme and the backup scheme, and the switching logic is that the track of the satellite-borne computer is determined to be switched from the master scheme to the backup scheme under the condition that the GNSS measurement data is continuously invalid for 1800S.
In step S8, the switching logic between the primary backup schemes is designed as follows according to the operating state of the GNSS measurement system and the data validity thereof: starting a backup scheme determined by a spacecraft orbit when the GNSS receiver data are unavailable for a long time, and restarting absolute navigation filtering if the GNSS receiver has data again and the continuous 10s data are effective; the AOCC determines the track data of an access system according to the current working mode; when the working mode is to forcibly use the GNSS, the result of the navigation filtering is accessed into the system; and when the working mode is on-satellite autonomous, the orbit data access system of the backup scheme is used.
While the present invention has been described in detail with reference to the preferred embodiments, it should be understood that the above description should not be taken as limiting the invention. Various modifications and alterations to this invention will become apparent to those skilled in the art upon reading the foregoing description. Accordingly, the scope of the invention should be determined from the following claims.

Claims (4)

1. A method for determining a spacecraft orbit based on multi-source data driving is characterized by comprising the following processes:
track data preprocessing is carried out on GNSS measurement data, and error data are eliminated;
performing coordinate system conversion on the preprocessed GNSS measurement data;
maintaining system time at the filtering moment and the satellite-borne computer running moment;
constructing a navigation filtering algorithm, and using a calculation result of the EKF filter as a master scheme determined by the spacecraft orbit;
determining the position and speed information of an inertial system of the spacecraft orbit, and converting to obtain instantaneous orbit parameters and orbit average number;
judging the stability of navigation filtering aiming at the flat number of the track;
using an orbit recursion algorithm as a backup scheme for spacecraft orbit determination;
providing switching logic between a master scheme and a backup scheme according to the working state of the GNSS measurement system; the orbit data preprocessing comprises the following processes:
according to the dynamic characteristics of the track, a threshold judgment formula is set as follows:
6.79×106m≤||r||≤7.05×106m and 7.46X 103m/s≤||v||≤7.75×103m/s
Figure FDA0002900916310000011
Wherein, x, y and z are triaxial position data measured by the GNSS receiver respectively; vx, vy and vz are triaxial speed data measured by the GNSS receiver respectively;
the measurement input exceeding the threshold value range is taken as error data rejection; the coordinate system conversion refers to converting WGS84 coordinates obtained by measurement of a GNSS receiver into J2000.0 coordinates required by filtering, and the coordinate conversion process comprises time conversion and calculation of the time difference RPNutating RNPolar motion RMAnd a rotation matrix RSThe following can be obtained:
RJ2000=(RMRSRNRP)-1R84
Figure FDA0002900916310000012
in the formula, RJ2000Position data in the J2000.0 coordinate system; v. ofJ2000Velocity data for the J2000.0 coordinate system; r84Position data in WGS84 coordinate system; v. of84Velocity data in WGS84 coordinate system; the navigation filtering algorithm comprises:
the standard EKF filtering algorithm is used, and the absolute navigation filtering operation of each beat comprises the position and the speed of the previous beat in the inertial system
Figure FDA0002900916310000021
Error covariance matrix P of previous beat statek-1Absolute position and speed data Z measured in real time by a system state noise covariance matrix Q and a measurement noise covariance matrix R, GNSSkThe output is the position and the speed of the current beat under the inertial system
Figure FDA0002900916310000022
Covariance matrix P with current beat state errorkThe calculation process is as follows:
(1) from the previous beat state
Figure FDA0002900916310000023
Performing state quantity prediction
Figure FDA0002900916310000024
Previous beat state of algorithm input
Figure FDA0002900916310000025
Is position and velocity under the inertial system
Figure FDA0002900916310000026
Is recorded as [ x y z v ]x vyvz]TAnd dX ═ f (x) expression is as follows:
Figure FDA0002900916310000027
wherein,
Figure FDA0002900916310000028
Figure FDA0002900916310000029
Figure FDA0002900916310000031
Figure FDA0002900916310000032
Figure FDA0002900916310000033
Figure FDA0002900916310000034
Figure FDA0002900916310000035
in the formula, r is a position module value of the satellite J2000.0 in an inertial coordinate system; x ═ X y z vx vy vz]TRefers to the position and the speed of the satellite J2000.0 in an inertial coordinate system; μ represents the earth gravity constant; a isJ2、aJ3、aJ4Represents perturbation accelerations of J2, J3 and J4 items respectively; rEIs the radius of the earth; Δ t means a time difference;
(2) solving for Pk/k-1The following are:
Figure FDA0002900916310000036
Φk,k-1=I+Fk-1Δt;
Figure FDA0002900916310000037
in the formula, I is a unit array; phik,k-1Representing a state matrix; q represents a system state noise covariance matrix; pk-1Representing a state error matrix;
(3) calculating a filter gain KK,KKIs equal to Pk/k-1(Pk/k-1+R)-1
(4) Completion state quantity estimation
Figure FDA0002900916310000038
Is equal to
Figure FDA0002900916310000039
(5) Completion state error matrix PkUpdate, PkIs equal to (I-K)k)Pk/k-1
2. The multi-source data-driven-based spacecraft orbit determination method of claim 1,
in the process of determining the stability of the navigation filtering for the track flat number, the method further includes:
storing the average number of the track, sampling every M seconds, taking the first N average semi-major axis sampling points, and calculating the average value of the average semi-major axis
Figure FDA0002900916310000041
As the average of the current beat semimajor axis; when the number of the points is less than N, the average value of the current number of the flat semi-major axes is obtained;
and clearing all data for recalculation each time the absolute navigation based on the GNSS data is accessed again.
3. The multi-source data-driven-based spacecraft orbit determination method of claim 2,
the stability criterion of absolute navigation is: when the N average semimajor axis sampling points are fully collected, if the module value meeting the difference of the average values of the front and back beat semimajor axes in the calculation period of 10 continuous spaceborne computers is smaller than the stability judgment threshold value adhIf so, judging that the absolute navigation filtering is stable; stability judgment threshold value a for note number modificationdh
4. The multi-source data-driven-based spacecraft orbit determination method of claim 3,
in the logic process of switching between the master scheme and the backup scheme, the method further comprises:
starting a backup scheme determined by a spacecraft orbit when the GNSS receiver data are unavailable for a long time, and restarting absolute navigation filtering if the GNSS receiver has data again and the data are valid within a certain continuous time;
determining orbit data of an access system according to the current working mode; when the working mode is to forcibly use the GNSS, the result of the navigation filtering is accessed into the system; and if the working mode is on-satellite autonomous, accessing the orbit data of the backup scheme into the system.
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