CN108957499A - Accompanying flying target Relative Navigation based on observed quantity spectrum analysis and optimal estimation - Google Patents
Accompanying flying target Relative Navigation based on observed quantity spectrum analysis and optimal estimation Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO 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
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining 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
- G01S19/42—Determining position
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO 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
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/03—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers
- G01S19/05—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers providing aiding data
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Abstract
The invention discloses a kind of accompanying flying target Relative Navigation and system based on observed quantity spectrum analysis and optimal estimation, this method comprises: determining target relative movement track according to line of sight angle observation amount；The line of sight angle for obtaining matching with the target relative movement track of the determination, which is extracted, from angle of sight biasing linear regression model (LRM) coefficient data library biases linear regression coeffficient；For line of sight angle observation value in observation period, determine that the target actual observation angle of sight biases using optimal estimation method；Line of sight angle is biased into linear regression coeffficient and angle of sight biasing regression model is brought in the biasing of the target actual observation angle of sight into, solution obtains target mean latitude degree argument, to complete accompanying flying improvement of orbit.The present invention is on the basis of traditional Unscented kalman filtering algorithm, according to the spectral characteristic of observed quantity, realizes the real-time amendment to mean latitude degree argument using optimal estimation method, solves the problems, such as that only angle measurement Relative Navigation mean latitude degree argument determines accompanying flying target.
Description
Technical field
The invention belongs to field of navigation technology more particularly to a kind of accompanying flyings based on observed quantity spectrum analysis and optimal estimation
Target Relative Navigation and system.
Background technique
Non- cooperation accompanying flying target Relative Navigation can be all related in fields such as Space Attack, Situation Awareness and in-orbit services to ask
Topic.Due to the non-collaboration properties of target, often only have line of sight angle observation amount available when Relative Navigation resolves, therefore only base
Just become a key technology in above-mentioned field in the accompanying flying target Relative Navigation technology of Angle Information, has extensive and important
Using.
Due to the space-based only poor problem of the intrinsic observability degree of angle measurement Relative Navigation, cause to carry out accompanying flying target opposite
There are mean latitude degree arguments (λ=ω+M, ω are argument of perigee, and M is mean anomaly) to be difficult to determining problem when track resolves.It passes
The solution of system usually utilizes orbit maneuver to change observation geometry, so that accompanying flying line of sight range information is extracted, or
Person uses high-precision Relative Navigation model, in conjunction with accompanying flying orbit perturbation characteristic, is identified using system noise adaptive filter algorithm
Small distance, which perturbs, to be changed.It these methods or needs to consume additional spacecraft fuel, and needs multiple orbit maneuver
It avoids filtering divergence or high requirement is suffered to model accuracy, the stability etc. of filtering algorithm, and calculation amount is relatively
Greatly, it is unfavorable for algorithm on star to realize.
In view of the relative motion feature of accompanying flying target period, line of sight angle observation amount also will be with peri odic spectrum
Characteristic, and the parameters such as angle of sight spectral amplitude, biasing, frequency, initial phase are closely related with accompanying flying target relative orbit
's.It, can be flat to solve accompanying flying target by analysis accompanying flying line of sight angular spectrum parameter with the variation relation of mean latitude degree argument
Latitude argument determines that problem provides a kind of completely new technological means, is of great significance and application prospect.
Summary of the invention
Technology of the invention solves the problems, such as: overcome the deficiencies of the prior art and provide it is a kind of based on observed quantity spectrum analysis with
The accompanying flying target Relative Navigation and system of optimal estimation, on the basis of traditional Unscented kalman filtering algorithm, according to sight
The spectral characteristic of measurement realizes the real-time amendment to mean latitude degree argument using optimal estimation method, solves accompanying flying target and only survey
The problem that angle Relative Navigation mean latitude degree argument determines.This method is according to the frequency spectrum at different accompanying flying relative motion track line of sight angle
Difference realizes the adaptive correction to mean latitude degree argument, wherein calculation amount biggish accompanying flying line of sight angle biasing characteristic statistical
Analysis can be completed offline, only need to be completed using optimal estimation algorithm to mean latitude degree argument parameter according to prior information in line computation
Real-time amendment, improved the determination precision of target mean latitude degree argument, but also not only convenient for Autonomous Relative Navigation application on star.
In order to solve the above-mentioned technical problem, the invention discloses a kind of companion based on observed quantity spectrum analysis and optimal estimation
Fly target Relative Navigation, comprising:
(1) target relative movement track is determined using Unscented kalman filtering algorithm according to line of sight angle observation amount；
(2) it is extracted from angle of sight biasing linear regression model (LRM) coefficient data library and obtains fortune opposite with the target of the determination
The line of sight angle that dynamic rail road matches biases linear regression coeffficient；
(3) for line of sight angle observation value in observation period, target actual observation is determined using optimal estimation method
Angle of sight biasing；
(4) line of sight angle is biased into linear regression coeffficient and angle of sight biasing is brought in the biasing of the target actual observation angle of sight into
Regression model, solution obtains target mean latitude degree argument, to complete accompanying flying improvement of orbit.
In the above-mentioned accompanying flying target Relative Navigation based on observed quantity spectrum analysis and optimal estimation, by walking as follows
Suddenly angle of sight biasing linear regression model (LRM) coefficient data library is established:
For different accompanying flying relative motion tracks, the resolving of line of sight angle is carried out with preset step-length, obtains an accompanying flying
Line of sight angle change curve in orbital period；
According to line of sight angle change curve, the corresponding view of each accompanying flying relative motion track is determined using optimal estimation method
Line angle frequency spectrum parameter；
It is extracted respectively from each accompanying flying relative motion orbit parameter and angle of sight frequency spectrum parameter and obtains mean latitude degree argument and right
The angle of sight biasing answered；
According to obtained mean latitude degree argument and the biasing of the corresponding angle of sight is extracted, using least squares estimate, determine each
The corresponding angle of sight of accompanying flying relative motion track biases linear regression coeffficient, and saves, and obtains angle of sight biasing linear regression mould
Type coefficient data library.
In the above-mentioned accompanying flying target Relative Navigation based on observed quantity spectrum analysis and optimal estimation, for different
Accompanying flying relative motion track carries out the resolving of line of sight angle with preset step-length, obtains the target view in an accompanying flying orbital period
Line angle change curve, comprising:
If the orbital tracking of observation satellite is σo=[a, e, i, Ω, ω, M]T, wherein a, e, i, Ω, ω, M respectively indicate sight
Survey satellite orbit semi-major axis, eccentricity, orbit inclination angle, right ascension of ascending node, argument of perigee and mean anomaly；δe,δi,δΩ,δ
ω, δ M respectively indicate the deviation of observation satellite eccentricity, orbit inclination angle, right ascension of ascending node, argument of perigee and mean anomaly；Companion
The orbital tracking for flying satellite is σt=σo+ δ σ, wherein δ σ=[0, δ e, δ i, δ Ω, δ ω, δ M]T；Indicate accompanying flying satellite and observation
The deviation of satellite respective carter radical；
By σoAnd σtBy ephemeris computation, the shape of observation satellite and accompanying flying satellite under the J2000 coordinate system of the earth's core is respectively obtained
State vector Xo=[ro,vo]TAnd Xt=[rt,vt]T, wherein ro,voRespectively indicate position, the velocity vector of observation satellite, rt,vtPoint
It Biao Shi not the position of accompanying flying satellite, velocity vector；
For given σoIt is combined with δ σ, respectively using Δ t as step-length, calculates the line of sight angle in a cycle, obtain
Line of sight angle change curve in one accompanying flying orbital period.
In the above-mentioned accompanying flying target Relative Navigation based on observed quantity spectrum analysis and optimal estimation,
By off-line calculation, angle of sight biasing linear regression model (LRM) coefficient data library is established.
It leads correspondingly, the invention also discloses a kind of based on observed quantity spectrum analysis is opposite with the accompanying flying target of optimal estimation
Boat system, comprising:
Determining module, for using Unscented kalman filtering algorithm, determining that target is opposite according to line of sight angle observation amount
Tracks；
Extraction module obtains and the determination for extracting from angle of sight biasing linear regression model (LRM) coefficient data library
The line of sight angle that target relative movement track matches biases linear regression coeffficient；
Module is resolved, for determining mesh using optimal estimation method for line of sight angle observation value in observation period
Mark the biasing of the actual observation angle of sight；
Correction module, for bringing line of sight angle biasing linear regression coeffficient and the biasing of the target actual observation angle of sight into
The angle of sight biases regression model, and solution obtains target mean latitude degree argument, to complete accompanying flying improvement of orbit.
The invention has the following advantages that
(1) the present invention is based on the Analysis of Spectrum of observed quantity, joint least-squares (OLS) estimation is filtered with Unscented kalman
Wave algorithm, efficiently solve the problems, such as accompanying flying target only angle measurement Relative Navigation mean latitude degree argument be difficult to it is determining.
(2) present invention completes the optimal estimation to angle of sight frequency spectrum parameter, tool using simplex-simulated annealing
There is the characteristics of high computational efficiency, fast convergence rate.
(3) present invention need to only be obtained according to the line of sight angle biasing regression model established offline in line computation actual observation
To the angle of sight biasing adaptive correction to mean latitude degree argument can be realized, computation burden is small, is conducive to algorithm on star and realizes.
Detailed description of the invention
Fig. 1 is a kind of accompanying flying target Relative Navigation based on observed quantity spectrum analysis and optimal estimation in the embodiment of the present invention
The step flow chart of method；
Fig. 2 is line of sight angle schematic diagram under a kind of horizontal coordinates of satellite velocities local in the embodiment of the present invention；
Fig. 3 is a kind of optimal angle of sight frequency spectrum parameter flow chart of calculating in the embodiment of the present invention.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with attached drawing to disclosed by the invention
Embodiment is described in further detail.
Referring to Fig.1, a kind of accompanying flying mesh based on observed quantity spectrum analysis and optimal estimation in the embodiment of the present invention is shown
Mark the step flow chart of Relative Navigation.In the present embodiment, the companion based on observed quantity spectrum analysis and optimal estimation
Fly target Relative Navigation, comprising:
Step 101, target relative movement is determined using Unscented kalman filtering algorithm according to line of sight angle observation amount
Track.
Step 102, it is extracted from angle of sight biasing linear regression model (LRM) coefficient data library and obtains the target with the determination
The line of sight angle that relative motion track matches biases linear regression coeffficient.
Step 103, for line of sight angle observation value in observation period, target reality is determined using optimal estimation method
Observe angle of sight biasing.
Step 104, line of sight angle is biased into linear regression coeffficient and sight is brought in the biasing of the target actual observation angle of sight into
Angle biases regression model, and solution obtains target mean latitude degree argument, to complete accompanying flying improvement of orbit.
In the preferred embodiment of the present invention, angle of sight biasing linear regression model (LRM) system can be established as follows
Number database: for different accompanying flying relative motion tracks, the resolving of line of sight angle is carried out with preset step-length, obtains an accompanying flying
Line of sight angle change curve in orbital period；According to line of sight angle change curve, determined using optimal estimation method each
The corresponding angle of sight frequency spectrum parameter of accompanying flying relative motion track；From each accompanying flying relative motion orbit parameter and angle of sight frequency spectrum parameter
Middle extract respectively obtains mean latitude degree argument and the biasing of the corresponding angle of sight；The mean latitude degree argument and corresponding view obtained according to extraction
Line angle biasing determines each accompanying flying relative motion track corresponding angle of sight biasing linear regression system using least squares estimate
Number, and save, obtain angle of sight biasing linear regression model (LRM) coefficient data library.
Preferably, in the present embodiment, described to be directed to different accompanying flying relative motion tracks, target is carried out with preset step-length
The angle of sight resolves, and obtains the line of sight angle change curve in an accompanying flying orbital period, can specifically include:
If the orbital tracking of observation satellite is σo=[a, e, i, Ω, ω, M]T, wherein a, e, i, Ω, ω, M respectively indicate sight
Survey satellite orbit semi-major axis, eccentricity, orbit inclination angle, right ascension of ascending node, argument of perigee and mean anomaly；δe,δi,δΩ,δ
ω, δ M respectively indicate the deviation of observation satellite eccentricity, orbit inclination angle, right ascension of ascending node, argument of perigee and mean anomaly；Companion
The orbital tracking for flying satellite is σt=σo+ δ σ, wherein δ σ=[0, δ e, δ i, δ Ω, δ ω, δ M]T；Indicate accompanying flying satellite and observation
The deviation of satellite respective carter radical.
By σoAnd σtBy ephemeris computation, the shape of observation satellite and accompanying flying satellite under the J2000 coordinate system of the earth's core is respectively obtained
State vector Xo=[ro,vo]TAnd Xt=[rt,vt]T, wherein ro,voRespectively indicate position, the velocity vector of observation satellite, rt,vtPoint
It Biao Shi not the position of accompanying flying satellite, velocity vector.
For given σoIt is combined with δ σ, respectively using Δ t as step-length, calculates the line of sight angle in a cycle, obtain
Line of sight angle change curve in one accompanying flying orbital period.
Wherein, it should be noted that the foundation that the angle of sight biases linear regression model (LRM) coefficient data library can be by offline
It calculates to realize；Above-mentioned steps 101-104 can be an online calculating process.
Based on the above embodiment, it is illustrated below with reference to a specific example.
(1) orbital tracking of observation satellite is set as σo=[a, e, i, Ω, ω, M]T, the orbital tracking of accompanying flying satellite is σt=
σo+ δ σ, by σoAnd σtBy ephemeris computation, the position vector of observation satellite and accompanying flying satellite under the J2000 coordinate system of the earth's core is obtained
Xo=[ro,vo]T, velocity vector Xt=[rt,vt]T。
In the present embodiment, δ σ=[0, δ e, δ i, δ Ω, δ ω, δ M]T.For given σoIt is combined with δ σ, respectively with Δ t
For step-length, the line of sight angle in a cycle is calculated.Here line of sight angle observation amount is local horizontal with observation satellite speed
(VVLH) azimuth angle alpha of line of sight vector and elevation angle β indicate (it defines as shown in Figure 2) under coordinate system.
According to vector XoAnd Xt, line of sight vector r under VVLH coordinate system can be calculated to obtain by following formulaVVLH:
In formula,
The coordinate value of x, y, z expression observation satellite.
Then the expression formula of line of sight angle observation amount can be written as:
(2) according to the relative track movement feature of accompanying flying target period, angle of sight observed quantity can be expressed as week
The form of phase function:
Wherein, α0、β0Indicate angle of sight biasing；δ α, δ β indicate the amplitude of angle of sight variation；N indicates angle of sight variation frequency
Rate；θα、θβIndicate angle of sight initial phase.
According to the angle of sight variation of accompanying flying target in a cycle, the frequency spectrum in above formula is solved using optimal estimation method and is joined
Number, so that line of sight angle residual error reaches minimum in a cycle, it may be assumed that
Here the optimal solution of the above problem is solved using simplex-simulated annealing.Simplex-simulated annealing is mixed
Hop algorithm combines simplex algorithm fast convergence rate and simulated annealing avoids falling into the excellent feature of office, has computational efficiency
The characteristics of height, fast convergence rate.Specific calculation process about the algorithm about simplex algorithm and simulation as shown in figure 3, move back
The principle and algorithm of fiery algorithm realize 2.1 sections and 8.1 sections that can be found in " intelligent optimization algorithm and its application " (Wang Lingzhu) book,
Details are not described herein.
(3) it for different accompanying flying tracks, solves angle of sight frequency spectrum parameter as procedure described above respectively, obtains and every group of [σo,
δσ]TCorresponding optimal [α0,β0,δα,δβ,n,θα,θβ]TCombination.
In conjunction with dynamics of orbits specificity analysis it is found that the biasing of accompanying flying line of sight angle can be expressed as the letter of δ Ω, δ ω, δ M
Number:
When δ Ω is determined, [α0,β0]TMeet linear relationship with the variation approximation of δ M, δ ω, therefore can be by [α0,β0]T
It is further represented as the linear function of δ M, δ ω:
According to above-mentioned relation, can be determined and any one group of (σ using OLS estimationo, δ σ) and the biasing of the corresponding angle of sight returns
Coefficient A0、A1、A2、B0、B1、B2
In formula,Respectively indicate α0、β0, δ M, δ ω sample average.As procedure described above, may be used
Calculate offline different accompanying flying tracks angle of sight biasing regression coefficient, with use when on-line amending mean latitude degree argument after facilitating.
(4) Relative Navigation online resolution: according to line of sight angle observation amount, using Unscented kalman filtering (UKF) algorithm
Complete the initial estimation to accompanying flying target relative movement track.Specific calculation process about UKF algorithm can be found in " optimum state
Estimation-Kalman, H∞And nonlinear filtering " (Zhang Yonggang, Li Ning are translated to Guangdong sun) book 14.3 sections, which is not described herein again.
Target state vector to be estimated uses the relative light intensity of following form, to be suitable for the track of random eccentric rate.
Wherein, [at,et,it,Ωt,ωt,Mt]TIndicate the orbital tracking of accompanying flying satellite, [ao,eo,io,Ωo,ωo,Mo]TTable
Show the orbital tracking of observation satellite.
(5) target relative light intensity [δ a, δ i, δ Ω, the δ e determined according to UKF algorithmx,δey]T, defended in conjunction with observation
Star reference orbit σo, the line of sight angle filtered out under respective carter in library of factors is returned from the angle of sight biasing that step 3 is established
Bias coefficient C (σo,δa,δi,δΩ,δex,δey)=[A0,A1,A2,B0,B1,B2]T。
(6) for line of sight angle observation value in the given period, according to identical process in step (2), utilize list
Pure shape-simulated annealing determines that accompanying flying line of sight angle biases [α0,β0]opt；
(7) angle of sight is biased into [α0,β0]optWith linearisation coefficient [A0,A1,A2,B0,B1,B2]TBring equation group (8) into, by
This solves the corrected Calculation result of accompanying flying target mean latitude degree argument
Based on the above embodiment, the invention also discloses a kind of accompanying flying mesh based on observed quantity spectrum analysis and optimal estimation
Mark relative navigation system, comprising: determining module, for according to line of sight angle observation amount, using Unscented kalman filtering algorithm,
Determine target relative movement track；Extraction module, for being extracted from angle of sight biasing linear regression model (LRM) coefficient data library
The line of sight angle to match to the target relative movement track with the determination biases linear regression coeffficient；Module is resolved, is used
The line of sight angle observation value in for observation period determines that the target actual observation angle of sight is inclined using optimal estimation method
It sets；Correction module, for bringing line of sight angle biasing linear regression coeffficient and the biasing of the target actual observation angle of sight into sight
Angle biases regression model, and solution obtains target mean latitude degree argument, to complete accompanying flying improvement of orbit.
For system embodiments, since it is corresponding with embodiment of the method, so be described relatively simple, correlation
Place referring to embodiment of the method part explanation.
Various embodiments are described in a progressive manner in this explanation, the highlights of each of the examples are with its
The difference of his embodiment, the same or similar parts between the embodiments can be referred to each other.
The above, optimal specific embodiment only of the invention, but scope of protection of the present invention is not limited thereto,
In the technical scope disclosed by the present invention, any changes or substitutions that can be easily thought of by anyone skilled in the art,
It should be covered by the protection scope of the present invention.
The content that description in the present invention is not described in detail belongs to the well-known technique of professional and technical personnel in the field.
Claims (5)
1. a kind of accompanying flying target Relative Navigation based on observed quantity spectrum analysis and optimal estimation characterized by comprising
(1) target relative movement track is determined using Unscented kalman filtering algorithm according to line of sight angle observation amount；
(2) it is extracted from angle of sight biasing linear regression model (LRM) coefficient data library and obtains the target relative movement rail with the determination
The line of sight angle that road matches biases linear regression coeffficient；
(3) for line of sight angle observation value in observation period, target actual observation sight is determined using optimal estimation method
Angle biasing；
(4) line of sight angle is biased into linear regression coeffficient and the biasing of the target actual observation angle of sight is brought angle of sight biasing into and returned
Model, solution obtains target mean latitude degree argument, to complete accompanying flying improvement of orbit.
2. the accompanying flying target Relative Navigation according to claim 1 based on observed quantity spectrum analysis and optimal estimation,
It is characterized in that, establishing angle of sight biasing linear regression model (LRM) coefficient data library as follows:
For different accompanying flying relative motion tracks, the resolving of line of sight angle is carried out with preset step-length, obtains an accompanying flying track
Line of sight angle change curve in period；
According to line of sight angle change curve, the corresponding angle of sight of each accompanying flying relative motion track is determined using optimal estimation method
Frequency spectrum parameter；
It is extracted respectively from each accompanying flying relative motion orbit parameter and angle of sight frequency spectrum parameter and obtains mean latitude degree argument and corresponding
Angle of sight biasing；
According to obtained mean latitude degree argument and the biasing of the corresponding angle of sight is extracted, using least squares estimate, each accompanying flying is determined
The corresponding angle of sight of relative motion track biases linear regression coeffficient, and saves, and obtains angle of sight biasing linear regression model (LRM) system
Number database.
3. the accompanying flying target Relative Navigation according to claim 2 based on observed quantity spectrum analysis and optimal estimation,
It is characterized in that, being directed to different accompanying flying relative motion tracks, the resolving of line of sight angle is carried out with preset step-length, obtains a companion
Fly the line of sight angle change curve in the orbital period, comprising:
If the orbital tracking of observation satellite is σo=[a, e, i, Ω, ω, M]T, wherein a, e, i, Ω, ω, M respectively indicate observation and defend
Star orbital road semi-major axis, eccentricity, orbit inclination angle, right ascension of ascending node, argument of perigee and mean anomaly；δe,δi,δΩ,δω,δM
Respectively indicate the deviation of observation satellite eccentricity, orbit inclination angle, right ascension of ascending node, argument of perigee and mean anomaly；Accompanying flying is defended
The orbital tracking of star is σt=σo+ δ σ, wherein δ σ=[0, δ e, δ i, δ Ω, δ ω, δ M]T；Indicate accompanying flying satellite and observation satellite
The deviation of respective carter radical；
By σoAnd σtBy ephemeris computation, the state arrow of observation satellite and accompanying flying satellite under the J2000 coordinate system of the earth's core is respectively obtained
Measure Xo=[ro,vo]TAnd Xt=[rt,vt]T, wherein ro,voRespectively indicate position, the velocity vector of observation satellite, rt,vtTable respectively
Show position, the velocity vector of accompanying flying satellite；
For given σoIt is combined with δ σ, respectively using Δ t as step-length, calculates the line of sight angle in a cycle, obtain a companion
Fly the line of sight angle change curve in the orbital period.
4. the accompanying flying target Relative Navigation according to claim 2 based on observed quantity spectrum analysis and optimal estimation,
It is characterized in that,
By off-line calculation, angle of sight biasing linear regression model (LRM) coefficient data library is established.
5. a kind of accompanying flying target relative navigation system based on observed quantity spectrum analysis and optimal estimation characterized by comprising
Determining module, for determining target relative movement using Unscented kalman filtering algorithm according to line of sight angle observation amount
Track；
Extraction module obtains the target with the determination for extracting from angle of sight biasing linear regression model (LRM) coefficient data library
The line of sight angle that relative motion track matches biases linear regression coeffficient；
Module is resolved, for determining target reality using optimal estimation method for line of sight angle observation value in observation period
Angle of sight biasing is observed on border；
Correction module, for bringing line of sight angle biasing linear regression coeffficient and the biasing of the target actual observation angle of sight into sight
Angle biases regression model, and solution obtains target mean latitude degree argument, to complete accompanying flying improvement of orbit.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109725648A (en) * | 2018-12-07 | 2019-05-07 | 北京空间飞行器总体设计部 | A kind of motor-driven window calculation method, apparatus of Relative Navigation satellite accompanying flying and medium |
| CN109725648B (en) * | 2018-12-07 | 2020-09-18 | 北京空间飞行器总体设计部 | Method, device and medium for calculating moving window of satellite-satellite vehicle |
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