CN114547549B - Atmospheric density autonomous estimation method and system based on low-orbit satellite orbit attenuation - Google Patents

Atmospheric density autonomous estimation method and system based on low-orbit satellite orbit attenuation Download PDF

Info

Publication number
CN114547549B
CN114547549B CN202210056286.XA CN202210056286A CN114547549B CN 114547549 B CN114547549 B CN 114547549B CN 202210056286 A CN202210056286 A CN 202210056286A CN 114547549 B CN114547549 B CN 114547549B
Authority
CN
China
Prior art keywords
satellite
track
correction coefficient
orbit
atmospheric density
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202210056286.XA
Other languages
Chinese (zh)
Other versions
CN114547549A (en
Inventor
许海玉
李海生
钱斌
***
王震
王君磊
张钊
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shanghai Institute of Satellite Engineering
Original Assignee
Shanghai Institute of Satellite Engineering
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shanghai Institute of Satellite Engineering filed Critical Shanghai Institute of Satellite Engineering
Priority to CN202210056286.XA priority Critical patent/CN114547549B/en
Publication of CN114547549A publication Critical patent/CN114547549A/en
Application granted granted Critical
Publication of CN114547549B publication Critical patent/CN114547549B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Operations Research (AREA)
  • Probability & Statistics with Applications (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Algebra (AREA)
  • Evolutionary Biology (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

The invention provides an atmospheric density autonomous estimation method and system based on low-orbit satellite orbit attenuation, comprising the following steps: step S1: acquiring effective satellite flight orbit counts; step S2: calculating a recurrence error based on the valid satellite orbital ring count; step S3: calculating the height attenuation of each track; step S4: according to the calculated satellite quality, when the recurrence error is equal to the height attenuation of each circle of orbit, correcting the face ratio deviation to obtain a face ratio correction coefficient, and taking the average value to obtain a final correction coefficient average value; step S5: and calculating an atmospheric density correction coefficient based on the final correction coefficient mean value, and updating and iterating each circle of atmospheric density correction coefficient according to the track circle count increment when the data identification is effective to obtain an atmospheric density correction coefficient sequence.

Description

Atmospheric density autonomous estimation method and system based on low-orbit satellite orbit attenuation
Technical Field
The invention relates to the technical field of atmospheric density estimation, in particular to an autonomous atmospheric density estimation method and an autonomous atmospheric density estimation system based on low-orbit satellite orbit attenuation.
Background
For a low-orbit aircraft, four kinds of perturbation effects are mainly caused in the on-orbit running process, namely, global aspheric perturbation, atmospheric damping perturbation, solar-lunar attraction perturbation and solar-light pressure perturbation. Of the four types of perturbation forces, the precision of the non-spherical perturbation of the earth depends on the order of spherical harmonics, and the precision of the non-spherical perturbation acceleration can be ensured only by ensuring enough order in the track forecasting process. The solar-lunar gravitational perturbation and solar pressure perturbation are mainly influenced by the absolute positions of the sun and the moon relative to the earth, obvious deviation cannot exist because the positions of the solar-lunar gravitational perturbation and the solar pressure perturbation are read through ephemeris, and the influence of the solar-lunar gravitational perturbation and the solar pressure perturbation on a low-orbit aircraft is far less than that of the non-spherical perturbation and the atmospheric damping perturbation, so that even if a small amount of deviation exists, the rail forecasting precision cannot be obviously influenced.
Thus, low-rail aircraft orbit predictions are affected by uncertainty factors that are primarily manifested in atmospheric damping perturbation. Because the key parameter of the atmospheric damping perturbation acceleration is the atmospheric density, the atmospheric density is influenced by various factors such as solar activity, geomagnetic activity, seasons and the like, obvious fluctuation change of the atmospheric density can occur within a certain time, and the change has certain randomness. In addition, the deviation of the on-orbit aerodynamic characteristics of the aircraft is large, and the uncertainty of the atmospheric damping perturbation acceleration can cause the off-satellite point of the aircraft to drift to a certain extent. The invention provides an automatic atmospheric density estimation method according to the attenuation condition of a low-orbit satellite orbit, which is particularly important to the automatic on-orbit atmospheric density estimation, and improves the atmospheric estimation precision by continuously iterating correction coefficients on the orbit.
Patent document CN103076257a (application number: 201110328334.8) discloses a fly-along type atmospheric density measuring apparatus, which describes a fly-along type atmospheric density measuring apparatus including a skeleton in which sheet metal reinforcement is added for fixing internal devices. The direct measurement method is used, and the case of the aircraft track attenuation caused by the change of the atmospheric density and the indirect measurement method using the track attenuation are not introduced.
Patent document CN104568652a (application number 201510008294.7) discloses a method and a measuring device for measuring the atmospheric density in the near space with high accuracy, which comprises a reentrant sphere, a first antenna, a second antenna, an internal test system, a lighter weight and a heavier weight. The calculation is performed according to the reentry equation of motion of the sphere flying at hypersonic speed, but the influence factors of the satellite aspect ratio are not considered and the correction method is not involved.
Patent document CN107132155A (application number: 201710299136.0) discloses a short-time atmospheric model correction method based on measured atmospheric density, which comprises the steps of selecting an atmospheric density model, collecting and calculating the measured atmospheric density for a set time period, and respectively performing linear fitting on an atmospheric model density value and a measured density value to obtain a measured atmospheric density fitting curve and a model density fitting curve. The current atmosphere model and the historical data are utilized for fitting, the number of the track quasi-flat root and the recurrence error are not introduced, and the on-orbit autonomous correction of the atmosphere density model by utilizing the history is not considered.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide an atmospheric density autonomous estimation method and an atmospheric density autonomous estimation system based on low-orbit satellite orbit attenuation.
The invention provides an atmospheric density autonomous estimation method based on low-orbit satellite orbit attenuation, which comprises the following steps:
Step S1: acquiring effective satellite flight orbit counts;
Step S2: calculating a recurrence error based on the valid satellite orbital ring count;
Step S3: calculating the height attenuation of each track;
Step S4: according to the calculated satellite quality, when the recurrence error is equal to the height attenuation of each circle of orbit, correcting the face ratio deviation to obtain a face ratio correction coefficient, and taking the average value to obtain a final correction coefficient average value;
step S5: and calculating an atmospheric density correction coefficient based on the final correction coefficient mean value, and updating and iterating each circle of atmospheric density correction coefficient according to the track circle count increment when the data identification is effective to obtain an atmospheric density correction coefficient sequence.
Preferably, the step S1 employs: and calculating the latitude of the satellite lower point, counting satellite flight track circles according to the change of the latitude of the satellite lower point, increasing the track circle count when the satellite passes through the equator and is in ascending track, and recording that the circle data are invalid when the satellite posture of the circle is abnormal or the track is regulated.
Preferably, the step S2 employs: and calculating the orbit parameter of the satellite system clock relative to J2000.0 as the current t moment according to the initial orbit parameter, introducing GPS quasi-flat root orbit determination data, and comparing the orbit height errors at the same moment to obtain a recurrence error da num, wherein num is the orbit circle count.
Preferably, the step S3 employs: calculating the track height attenuation dh i of each circle;
Where dh i represents the amount of track decay per turn; t represents the track cycle time; c d represents a drag coefficient; ρ 0 represents an atmospheric density initial value; m t denotes satellite mass; a represents a windward area; a gps represents the orbit quasi-flat root semi-long axis obtained by GPS; mu represents the gravitational constant; k j denotes an atmospheric density correction coefficient, The face quality ratio correction coefficient mean value is represented.
Preferably, the step S4 employs: obtaining the mass m t of the satellite after the satellite consumes fuel by using an ideal gas state equation and a gas mass conservation equation; when the recursive error da num data is valid, da num＝dhi obtains the face quality ratio correction coefficient K k, and the average value is taken to obtain the final correction coefficient
Preferably, the step S5 employs:
Wherein K j represents an atmospheric density correction coefficient, and the initial value is 1; ρ 0 represents an initial value of the atmospheric density, and the injection is carried out through the ground; t is the track cycle time; c d is the resistance coefficient; The face quality ratio correction coefficient mean value is obtained; da num is the recurrence error; num is the track circle count; a is the windward area; mu is the gravitational constant; a gps is the semi-long axis of the GPS pseudo-flat root track; m t is satellite mass;
When the data mark is valid, according to the increase of the track circle count num, updating the iteration per circle atmospheric density correction coefficient K j, and estimating the atmospheric density at the time t as rho t＝Kj·ρ0.
According to the invention, an atmospheric density autonomous estimation system based on low-orbit satellite orbit attenuation comprises:
module M1: acquiring effective satellite flight orbit counts;
Module M2: calculating a recurrence error based on the valid satellite orbital ring count;
module M3: calculating the height attenuation of each track;
Module M4: according to the calculated satellite quality, when the recurrence error is equal to the height attenuation of each circle of orbit, correcting the face ratio deviation to obtain a face ratio correction coefficient, and taking the average value to obtain a final correction coefficient average value;
module M5: and calculating an atmospheric density correction coefficient based on the final correction coefficient mean value, and updating and iterating each circle of atmospheric density correction coefficient according to the track circle count increment when the data identification is effective to obtain an atmospheric density correction coefficient sequence.
Preferably, the module M1 employs: calculating the latitude of a satellite lower point, counting satellite flight track circles according to the change of the latitude of the satellite lower point, increasing the track circle count when the satellite passes through the equator and is in ascending track, and recording that the circle is invalid when the satellite attitude of the circle is abnormal or the track is regulated;
the module M2 employs: and calculating the orbit parameter of the satellite system clock relative to J2000.0 as the current t moment according to the initial orbit parameter, introducing GPS quasi-flat root orbit determination data, and comparing the orbit height errors at the same moment to obtain a recurrence error da num, wherein num is the orbit circle count.
Preferably, the module M3 employs: calculating the track height attenuation dh i of each circle;
Where dh i represents the amount of track decay per turn; t represents the track cycle time; c d represents a drag coefficient; ρ 0 represents an atmospheric density initial value; m t denotes satellite mass; a represents a windward area; a gps represents the orbit quasi-flat root semi-long axis obtained by GPS; mu represents the gravitational constant; k j denotes an atmospheric density correction coefficient, Representing the average value of the face quality ratio correction coefficients;
The module M4 employs: obtaining the mass m t of the satellite after the satellite consumes fuel by using an ideal gas state equation and a gas mass conservation equation; when the recursive error da num data is valid, da num＝dhi obtains the face quality ratio correction coefficient K k, and the average value is taken to obtain the final correction coefficient
Preferably, the module M5 employs:
Wherein K j represents an atmospheric density correction coefficient, and the initial value is 1; ρ 0 represents an initial value of the atmospheric density, and the injection is carried out through the ground; t is the track cycle time; c d is the resistance coefficient; The face quality ratio correction coefficient mean value is obtained; da num is the recurrence error; num is the track circle count; a is the windward area; mu is the gravitational constant; a gps is the semi-long axis of the GPS pseudo-flat root track; m t is satellite mass;
When the data mark is valid, according to the increase of the track circle count num, updating the iteration per circle atmospheric density correction coefficient K j, and estimating the atmospheric density at the time t as rho t＝Kj·ρ0.
Compared with the prior art, the invention has the following beneficial effects: the invention considers the orbit recurrence error caused by the change of the atmospheric density of the orbit recurrence of the low orbit satellite, corrects the face value ratio according to the orbit recurrence error, estimates the atmospheric density of the altitude of the satellite, can improve the orbit recurrence precision of the satellite by using the estimation result, and the correction method is suitable for solar activity flat year and high years, and the correction coefficient can be adaptively adjusted on orbit.
Drawings
Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, given with reference to the accompanying drawings in which:
FIG. 1 is a flow chart of an autonomous estimation method of atmospheric density based on low-orbit satellite orbit attenuation.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the present invention, but are not intended to limit the invention in any way. It should be noted that variations and modifications could be made by those skilled in the art without departing from the inventive concept. These are all within the scope of the present invention.
Example 1
According to the invention, as shown in fig. 1, the method for autonomously estimating the atmospheric density based on the attenuation of the low-orbit satellite orbit comprises the following steps:
Step S1: acquiring effective satellite flight orbit counts;
Step S2: calculating a recurrence error based on the valid satellite orbital ring count;
Step S3: calculating the height attenuation of each track;
Step S4: according to the calculated satellite quality, when the recurrence error is equal to the height attenuation of each circle of orbit, correcting the face ratio deviation to obtain a face ratio correction coefficient, and taking the average value to obtain a final correction coefficient average value;
step S5: and calculating an atmospheric density correction coefficient based on the final correction coefficient mean value, and updating and iterating each circle of atmospheric density correction coefficient according to the track circle count increment when the data identification is effective to obtain an atmospheric density correction coefficient sequence.
Specifically, the step S1 employs: and calculating the latitude of the satellite lower point, counting satellite flight track circles according to the change of the latitude of the satellite lower point, increasing the track circle count when the satellite passes through the equator and is in ascending track, and recording that the circle data are invalid when the satellite posture of the circle is abnormal or the track is regulated.
Specifically, the step S2 employs: and calculating the orbit parameter of the satellite system clock relative to J2000.0 as the current t moment according to the initial orbit parameter, introducing GPS quasi-flat root orbit determination data, and comparing the orbit height errors at the same moment to obtain a recurrence error da num, wherein num is the orbit circle count.
Specifically, the step S3 employs: calculating the track height attenuation dh i of each circle;
Where dh i represents the amount of track decay per turn; t represents the track cycle time; c d represents a drag coefficient; ρ 0 represents an atmospheric density initial value; m t denotes satellite mass; a represents a windward area; a gps represents the orbit quasi-flat root semi-long axis obtained by GPS; mu represents the gravitational constant; k j denotes an atmospheric density correction coefficient, The face quality ratio correction coefficient mean value is represented.
Specifically, the step S4 employs: obtaining the mass m t of the satellite after the satellite consumes fuel by using an ideal gas state equation and a gas mass conservation equation; when the recursive error da num data is valid, da num＝dhi obtains the face quality ratio correction coefficient K k, and the average value is taken to obtain the final correction coefficient
Specifically, the step S5 employs:
Wherein K j represents an atmospheric density correction coefficient, and the initial value is 1; ρ 0 represents an initial value of the atmospheric density, and the injection is carried out through the ground; t is the track cycle time; c d is the resistance coefficient; The face quality ratio correction coefficient mean value is obtained; da num is the recurrence error; num is the track circle count; a is the windward area; mu is the gravitational constant; a gps is the semi-long axis of the GPS pseudo-flat root track; m t is satellite mass;
When the data mark is valid, according to the increase of the track circle count num, updating the iteration per circle atmospheric density correction coefficient K j, and estimating the atmospheric density at the time t as rho t＝Kj·ρ0.
According to the invention, an atmospheric density autonomous estimation system based on low-orbit satellite orbit attenuation comprises:
module M1: acquiring effective satellite flight orbit counts;
Module M2: calculating a recurrence error based on the valid satellite orbital ring count;
module M3: calculating the height attenuation of each track;
Module M4: according to the calculated satellite quality, when the recurrence error is equal to the height attenuation of each circle of orbit, correcting the face ratio deviation to obtain a face ratio correction coefficient, and taking the average value to obtain a final correction coefficient average value;
module M5: and calculating an atmospheric density correction coefficient based on the final correction coefficient mean value, and updating and iterating each circle of atmospheric density correction coefficient according to the track circle count increment when the data identification is effective to obtain an atmospheric density correction coefficient sequence.
Specifically, the module M1 employs: calculating the latitude of a satellite lower point, counting satellite flight track circles according to the change of the latitude of the satellite lower point, increasing the track circle count when the satellite passes through the equator and is in ascending track, and recording that the circle is invalid when the satellite attitude of the circle is abnormal or the track is regulated;
the module M2 employs: and calculating the orbit parameter of the satellite system clock relative to J2000.0 as the current t moment according to the initial orbit parameter, introducing GPS quasi-flat root orbit determination data, and comparing the orbit height errors at the same moment to obtain a recurrence error da num, wherein num is the orbit circle count.
Specifically, the module M3 employs: calculating the track height attenuation dh i of each circle;
Where dh i represents the amount of track decay per turn; t represents the track cycle time; c d represents a drag coefficient; ρ 0 represents an atmospheric density initial value; m t denotes satellite mass; a represents a windward area; a gps represents the orbit quasi-flat root semi-long axis obtained by GPS; mu represents the gravitational constant; k j denotes an atmospheric density correction coefficient, Representing the average value of the face quality ratio correction coefficients;
The module M4 employs: obtaining the mass m t of the satellite after the satellite consumes fuel by using an ideal gas state equation and a gas mass conservation equation; when the recursive error da num data is valid, da num＝dhi obtains the face quality ratio correction coefficient K k, and the average value is taken to obtain the final correction coefficient
Specifically, the module M5 employs:
Wherein K j represents an atmospheric density correction coefficient, and the initial value is 1; ρ 0 represents an initial value of the atmospheric density, and the injection is carried out through the ground; t is the track cycle time; c d is the resistance coefficient; The face quality ratio correction coefficient mean value is obtained; da num is the recurrence error; num is the track circle count; a is the windward area; mu is the gravitational constant; a gps is the semi-long axis of the GPS pseudo-flat root track; m t is satellite mass;
When the data mark is valid, according to the increase of the track circle count num, updating the iteration per circle atmospheric density correction coefficient K j, and estimating the atmospheric density at the time t as rho t＝Kj·ρ0.
Example 2
Example 2 is a preferred example of example 1
The invention provides an atmospheric density autonomous estimation method based on low-orbit satellite orbit attenuation, which comprises the following steps:
Step S1: judging the validity of the data by taking the track ring count as a unit;
step S2: calculating the number of the track quasi-flat roots at the moment t and a recurrence error;
Step S3: calculating the track height change rate;
Step S4: correcting the deviation of the facial quality ratio;
step S5: calculating an atmospheric density correction coefficient sequence;
Specifically, the step S1 includes:
Step S1.1: the positioning information of the satellite in the WGS-84 coordinate system is obtained from the positioning information of the satellite in the J2000.0 inertial coordinate system, wherein the positioning information R xyz of the satellite in the J2000.0 inertial coordinate system is calculated as follows:
Wherein R x,ry,rz is the coordinate axis component of positioning information R xyz under the J2000.0 inertial coordinate system, R z,Rx is a matrix function respectively, and the expression is Omega s is the right ascent point, i s is the orbit inclination angle, omega s near-spot angular distance, r s is the position satellite position vector magnitude, and f s is the true near-spot angle.
Step S2: the WGS-84 coordinate system satellite positioning information R wxwywz is calculated as:
Wherein R HG is a conversion matrix, ,RPR＝Rz(-zA)Ry(θA)Rz(-ζA),RHG＝REPRz(SG)RNRRPR, can be obtained from the following relation, in which ζ A,θA,zA is a matrix conversion system, whose size is:
wherein TT is the century number of Ru, R y is a matrix function, and the expression is R EP,RNR is nutation matrix, polar motion matrix, and takes the value as/>Polar motion matrix/>S G is the Greenwich mean star, its size is/>
Step S1.3: the latitude of the earth center of the point below the satellite is calculated as phi cw:
Wherein, phi cw is required to be E [ -pi/2, pi/2 ]), and R wx,rwy,rwz is the WGS-84 coordinate axis component of the positioning information R wxwywz.
Step S1.4: the geographical latitude of the point below the satellite is phi w:
Wherein phi w is required to be changed into E < -pi/2, pi/2 >; r e,Rp takes the value R e＝6378.137km,Rp = 6356.752km.
Step S1.5: track ring calculation:
The initial value of the track turn count num is 0; phi w0 represents the satellite latitude of the previous period, and the initial value is 3.141592; phi wi is the current latitude of the satellite, and when the relation phi w0 is smaller than 0 and phi wi is more than or equal to 0, the track turn count is increased.
Step S1.6: data invalidation identification:
Satellite state information is obtained from satellite bus communication, and when the satellite bus informs the satellite to perform orbit adjustment or attitude Data is not available, the current Data is recorded to be invalid, namely, data num =nan.
Specifically, the step S2 includes:
Step S2.1: the unit of the satellite system clock t relative to J2000.0 is 0.1ms, the time difference relative to the initial value t0 of the track is deltat, and the semi-long axis of the track at the moment t is: a t＝a0+a2 delta t, wherein a 0 is the quasi-flat root number semi-major axis at the time t0, the initial value is the ground surface injection initial value, a 2 is the satellite semi-major axis flat root number correction value, and the initial value is 100m according to the orbit height of 400 km.
Step S2.2: from the orbit recursion position vector (J2000.0 inertial coordinate system) at time t gps and the position vector calculated from the latest received GPS orbit root (J2000.0 inertial coordinate system), a recursion error da i is obtained:
danum＝[(rgpsx-rx)2+(rgpsy-ry)2+(rgpsz-rz)2]1/2
Wherein R x,ry,rz is a coordinate axis component of the positioning information R xyz under the J2000.0 inertial coordinate system, R gpsx,rgpsy,rgpsz is a coordinate axis component of the GPS positioning information received by R gpsx,rgpsy,rgpsz under the J2000.0 inertial coordinate system, and num is a track circle count.
Specifically, the step S3 includes:
Step S3.1: calculating the height attenuation of each track;
Wherein dh i is the attenuation of each circle of orbit, m, T is the orbit period time, s, C d is the resistance coefficient, ρ 0 is the initial value of the atmospheric density, kg/m 3,mt is the satellite mass, kg, A is the windward area, m, a gps is the semi-long axis of the GPS quasi-flat root orbit, km, mu is the gravitational constant, 3.986 x 10 5,Kj is the correction coefficient of the atmospheric density, The face quality ratio is the mean value of correction coefficients.
Specifically, the step S4 includes:
step S4.1: because the compression coefficient of the liquid is smaller, the influence of the pressure on the liquid volume is ignored in calculation; the change of the volume of the storage tank is not considered when the pressure is changed, and the satellite mass m t after fuel consumption is obtained by utilizing an ideal gas state equation and a gas mass conservation equation;
mt＝(Vt-Vq)·f(t)；
wherein f (t) = 1023.432-0.8279 ×t-0.0004×t 2, t is the tank temperature in degrees celsius, V t,Vq is the tank effective volume and the tank air cushion volume, respectively, a known quantity is the floor tank design value, and f (t) is a temperature dependent tank internal pressure function.
When the data is identified as being valid, then,I.e. to a group of facial mass ratio correction coefficients whose correction coefficient mean value is/>
Specifically, the step S5 includes:
the atmospheric density correction coefficient K j, the initial value of which is 1, is calculated by using the formula An atmospheric density correction coefficient K j is obtained, wherein the initial value ρ 0 can be injected up through the ground.
When the data identification is valid, according to the increase of the track circle count num, updating the iteration per circle air density correction coefficient K j, and estimating the air density at the time t as rho t＝Kj·ρ0.
Those skilled in the art will appreciate that the systems, apparatus, and their respective modules provided herein may be implemented entirely by logic programming of method steps such that the systems, apparatus, and their respective modules are implemented as logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc., in addition to the systems, apparatus, and their respective modules being implemented as pure computer readable program code. Therefore, the system, the apparatus, and the respective modules thereof provided by the present invention may be regarded as one hardware component, and the modules included therein for implementing various programs may also be regarded as structures within the hardware component; modules for implementing various functions may also be regarded as being either software programs for implementing the methods or structures within hardware components.
The foregoing describes specific embodiments of the present application. It is to be understood that the application is not limited to the particular embodiments described above, and that various changes or modifications may be made by those skilled in the art within the scope of the appended claims without affecting the spirit of the application. The embodiments of the application and the features of the embodiments may be combined with each other arbitrarily without conflict.

Claims (2)

1. An autonomous estimation method of atmospheric density based on low-orbit satellite orbit attenuation, comprising the steps of:
Step S1: acquiring effective satellite flight orbit counts;
Step S2: calculating a recurrence error based on the valid satellite orbital ring count;
Step S3: calculating the height attenuation of each track;
Step S4: according to the calculated satellite quality, when the recurrence error is equal to the height attenuation of each circle of orbit, correcting the face ratio deviation to obtain a face ratio correction coefficient, and taking the average value to obtain a final correction coefficient average value;
Step S5: calculating an atmospheric density correction coefficient based on the final correction coefficient mean value, and updating and iterating each circle of atmospheric density correction coefficient according to track circle count increment when the data identification is effective to obtain an atmospheric density correction coefficient sequence;
The step S1 adopts: calculating the latitude of a satellite lower point, counting satellite flight track circles according to the change of the latitude of the satellite lower point, increasing the track circle count when the satellite passes through the equator and is in ascending track, and recording that the circle is invalid when the satellite attitude of the circle is abnormal or the track is regulated;
the step S2 adopts: calculating the orbit parameter of the satellite system clock relative to J2000.0 as the current t moment according to the initial orbit parameter, introducing GPS quasi-flat root orbit determination data, and comparing the orbit height errors at the same moment to obtain a recurrence error Wherein num is the track circle count;
The step S3 adopts: calculating the height attenuation of each track ；
；
Wherein,Representing the amount of attenuation per turn of track; /(I)Representing the track cycle time; /(I)Representing the resistance coefficient; /(I)Representing an initial value of the atmospheric density; /(I)Representing satellite quality; /(I)Representing a windward area; /(I)Representing the quasi-flat root semi-long axis of the orbit obtained by the GPS; /(I)Representing the gravitational constant; /(I)Represents the atmospheric density correction coefficient,/>Representing the average value of the face quality ratio correction coefficients;
the step S4 employs: obtaining the mass of the satellite after the satellite consumes fuel by using an ideal gas state equation and a gas mass conservation equation ; When recurrence error/>When data is valid,/>Obtain the facial quality ratio correction coefficient/>Obtaining the final correction coefficient/>, by taking the average value；
The step S5 employs:
Wherein, The atmospheric density correction coefficient is represented, and the initial value is 1; /(I)Representing an initial value of the atmospheric density, and performing uploading through the ground; Is the track cycle time; /(I) Is the resistance coefficient; /(I)The face quality ratio correction coefficient mean value is obtained; /(I)Is a recursive error; num is the track circle count; /(I)Is the windward area; /(I)Is the gravitational constant; /(I)The method comprises the steps of (1) setting a semi-long axis of a root track for GPS; /(I)Is satellite mass;
When the data identification is valid, updating the iteration per-turn barometric density correction coefficient according to the increase of the track turn count num Estimating the atmospheric density at the time t as/>。
2. An autonomous estimation system of atmospheric density based on low-orbit satellite orbital attenuation, comprising:
module M1: acquiring effective satellite flight orbit counts;
Module M2: calculating a recurrence error based on the valid satellite orbital ring count;
module M3: calculating the height attenuation of each track;
Module M4: according to the calculated satellite quality, when the recurrence error is equal to the height attenuation of each circle of orbit, correcting the face ratio deviation to obtain a face ratio correction coefficient, and taking the average value to obtain a final correction coefficient average value;
module M5: calculating an atmospheric density correction coefficient based on the final correction coefficient mean value, and updating and iterating each circle of atmospheric density correction coefficient according to track circle count increment when the data identification is effective to obtain an atmospheric density correction coefficient sequence;
The module M1 employs: calculating the latitude of a satellite lower point, counting satellite flight track circles according to the change of the latitude of the satellite lower point, increasing the track circle count when the satellite passes through the equator and is in ascending track, and recording that the circle is invalid when the satellite attitude of the circle is abnormal or the track is regulated;
The module M2 employs: calculating the orbit parameter of the satellite system clock relative to J2000.0 as the current t moment according to the initial orbit parameter, introducing GPS quasi-flat root orbit determination data, and comparing the orbit height errors at the same moment to obtain a recurrence error Wherein num is the track circle count;
The module M3 employs: calculating the height attenuation of each track ；
；
Wherein,Representing the amount of attenuation per turn of track; /(I)Representing the track cycle time; /(I)Representing the resistance coefficient; /(I)Representing an initial value of the atmospheric density; /(I)Representing satellite quality; /(I)Representing a windward area; /(I)Representing the quasi-flat root semi-long axis of the orbit obtained by the GPS; /(I)Representing the gravitational constant; /(I)Represents the atmospheric density correction coefficient,/>Representing the average value of the face quality ratio correction coefficients;
The module M4 employs: obtaining the mass of the satellite after the satellite consumes fuel by using an ideal gas state equation and a gas mass conservation equation ; When recurrence error/>When data is valid,/>Obtain the facial quality ratio correction coefficient/>Obtaining the final correction coefficient/>, by taking the average value；
The module M5 employs:
Wherein, The atmospheric density correction coefficient is represented, and the initial value is 1; /(I)Representing an initial value of the atmospheric density, and performing uploading through the ground; Is the track cycle time; /(I) Is the resistance coefficient; /(I)The face quality ratio correction coefficient mean value is obtained; /(I)Is a recursive error; num is the track circle count; /(I)Is the windward area; /(I)Is the gravitational constant; /(I)The method comprises the steps of (1) setting a semi-long axis of a root track for GPS; /(I)Is satellite mass;
When the data identification is valid, updating the iteration per-turn barometric density correction coefficient according to the increase of the track turn count num Estimating the atmospheric density at the time t as/>。
CN202210056286.XA 2022-01-18 2022-01-18 Atmospheric density autonomous estimation method and system based on low-orbit satellite orbit attenuation Active CN114547549B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210056286.XA CN114547549B (en) 2022-01-18 2022-01-18 Atmospheric density autonomous estimation method and system based on low-orbit satellite orbit attenuation

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210056286.XA CN114547549B (en) 2022-01-18 2022-01-18 Atmospheric density autonomous estimation method and system based on low-orbit satellite orbit attenuation

Publications (2)

Publication Number Publication Date
CN114547549A CN114547549A (en) 2022-05-27
CN114547549B true CN114547549B (en) 2024-06-21

Family

ID=81672252

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210056286.XA Active CN114547549B (en) 2022-01-18 2022-01-18 Atmospheric density autonomous estimation method and system based on low-orbit satellite orbit attenuation

Country Status (1)

Country Link
CN (1) CN114547549B (en)

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103793618B (en) * 2014-02-28 2017-01-18 北京航天飞行控制中心 Thermosphere atmospheric density correction method
CN109765141B (en) * 2018-12-18 2021-09-14 电子科技大学 Method for extracting atmospheric density based on SWARM-C satellite
CN112257343B (en) * 2020-10-22 2023-03-17 上海卫星工程研究所 High-precision ground track repetitive track optimization method and system
CN112711736B (en) * 2021-01-28 2024-05-10 中国人民解放军63920部队 Method and device for calibrating atmospheric density detection data, storage medium and processor

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
GEO卫星图像定位配准技术及仿真验证研究;许海玉、王皓、沈毅力、边志强、钱勇;《航天器工程》;20150815;第24卷(第04期);全文 *
Research on the Availability Analysis Method of Navigation Satellite Based on Petri Nets;Haisheng Li等;《Springer Link》;20180504;全文 *

Also Published As

Publication number Publication date
CN114547549A (en) 2022-05-27

Similar Documents

Publication Publication Date Title
CN110487301B (en) Initial alignment method of radar-assisted airborne strapdown inertial navigation system
CN110132261B (en) High-precision on-satellite orbit forecasting method based on numerical fitting
CN112257343B (en) High-precision ground track repetitive track optimization method and system
CN108548542B (en) Near-earth orbit determination method based on atmospheric resistance acceleration measurement
CN104501804B (en) A kind of in-orbit orbit prediction method of satellite based on gps measurement data
Zurek et al. Application of MAVEN accelerometer and attitude control data to Mars atmospheric characterization
CN108021138B (en) Simplified design method of geomagnetic field model
CN104048664A (en) Autonomous orbit determination method of navigation satellite constellation
CN109708663B (en) Star sensor online calibration method based on aerospace plane SINS assistance
CN112713922A (en) Visibility rapid forecasting algorithm of multi-beam communication satellite
CN112461262A (en) Device and method for correcting errors of three-axis magnetometer
CN116401833A (en) Satellite orbit calculation method based on SGP4 model
CN110703355B (en) Calibration method and device of satellite-borne accelerometer
CN115314101A (en) Low-orbit communication satellite constellation rapid modeling method based on parallel computing
CN114547549B (en) Atmospheric density autonomous estimation method and system based on low-orbit satellite orbit attenuation
CN104567868B (en) Method of airborne long-endurance astronomical navigation system based on INS correction
CN111814313B (en) Regression orbit design method in high-precision gravitational field
CN113916217A (en) Star positioning method based on partitioned stratosphere atmospheric refraction model
CN105180928B (en) A kind of boat-carrying star sensor localization method based on inertial system gravity characteristic
Tynis et al. Reconstruction of the Adaptable Deployable Entry and Placement Technology Sounding Rocket One Flight Test
CN113776527B (en) Integrated navigation system and navigation method for civil aircraft full time and space
CN111272336B (en) Method for realizing mass center displacement estimation of large-scale low-orbit spacecraft based on GNSS observation
CN115392540A (en) Rapid forecasting method for lunar orbit rendezvous guidance
CN114771873A (en) Autonomous and accurate maintaining method for ultra-low-orbit satellite orbit
CN114002710A (en) On-satellite orbit position autonomous prediction method for small-eccentricity low-orbit satellite

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant