CN118816900B - Track jump processing method, electronic equipment and computer program product - Google Patents
Track jump processing method, electronic equipment and computer program productInfo
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- CN118816900B CN118816900B CN202410190535.3A CN202410190535A CN118816900B CN 118816900 B CN118816900 B CN 118816900B CN 202410190535 A CN202410190535 A CN 202410190535A CN 118816900 B CN118816900 B CN 118816900B
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
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Abstract
本发明公开了一种轨道跳变处理方法、电子设备及计算机程序产品，其中，轨道跳变处理方法包括：确定卫星所在的当前轨道与第一轨道拟合的第一中误差，以及当前轨道与第二轨道拟合的第二中误差；第一轨道为卫星所在的当前轨道的前一个轨道，第二轨道为基于当前轨道进行批处理得到的预报轨道；基于第一中误差和第二中误差，确定预设的第一观测方程中的轨道平滑权阵的取值；轨道平滑权阵表征轨道拟合时对当前轨道或第一轨道的依赖程度；基于第一观测方程确定用于轨道更新的轨道值。
This invention discloses an orbital jump processing method, electronic device, and computer program product. The orbital jump processing method includes: determining a first mean square error in fitting the current orbit of the satellite to a first orbit, and a second mean square error in fitting the current orbit to a second orbit; the first orbit is the orbit preceding the current orbit of the satellite, and the second orbit is a predicted orbit obtained by batch processing based on the current orbit; determining the value of the orbital smoothing weight matrix in a preset first observation equation based on the first mean square error and the second mean square error; the orbital smoothing weight matrix characterizes the degree of dependence on the current orbit or the first orbit during orbit fitting; and determining the orbital value used for orbit updating based on the first observation equation.
Description
Technical Field
The present invention relates to the field of transmission technologies, and in particular, to a track jump processing method, an electronic device, and a computer program product.
Background
The batch processing forecasting method is a satellite real-time precise orbit determination method commonly used at present, under the condition of normal stress, the satellite motion is smoothly changed, the motion state of the satellite motion can be expressed through a high-precision dynamic model, and a real-time orbit with higher precision can be obtained based on the orbit forecasting method of batch understanding calculation. When the stress of the satellite changes, such as ground shadow entering, orbit maneuver and other abnormal satellite motion conditions, the accuracy of the dynamic model is obviously reduced, so that the accuracy of the forecast orbit is reduced. And the periodic update of batch processing tracks can cause remarkable track jump near an update epoch, the real-time tracks obtained by the method also have arc segment splicing with a certain update period, so that the problem of discontinuity between adjacent update arc segments exists, and the track fixing precision and stability of the method are seriously influenced.
Disclosure of Invention
In view of this, embodiments of the present invention provide a track jump processing method, an electronic device, and a computer program product, which can accurately measure a link delay.
The technical scheme of the embodiment of the invention is realized as follows:
In one aspect, an embodiment of the present invention provides a track jump processing method, where the method includes:
Determining a first middle error of fitting a current orbit of a satellite with a first orbit and a second middle error of fitting the current orbit with a second orbit, wherein the first orbit is a previous orbit of the current orbit of the satellite, and the second orbit is a forecast orbit obtained by batch processing based on the current orbit;
Determining the value of a track smoothing weight matrix in a preset first observation equation based on the first intermediate error and the second intermediate error, wherein the track smoothing weight matrix characterizes the dependence degree of the track smoothing weight matrix on a current track or the first track during track fitting;
A track value for track update is determined based on the first observation equation.
In the above scheme, the determining the first intermediate error of the fitting of the current orbit of the satellite to the first orbit and the second intermediate error of the fitting of the current orbit to the second orbit includes:
Determining a first residual of the current orbit and the orbit observations of the first orbit in a plurality of epochs based on a second observation equation, and determining a second residual of the current orbit and the orbit observations of the second orbit in a plurality of epochs;
the first medium error is determined based on a first residual of a plurality of epochs and the second medium error is determined based on a second residual of the plurality of epochs.
In the above scheme, the method further comprises:
And constructing the second observation equation by taking satellite positions in the same epoch in adjacent orbits as observation values.
In the above scheme, the method further comprises:
and constructing the first observation equation based on the track smoothing weight array and the second observation equation.
In the above aspect, the determining, based on the second observation equation, a first residual of the current track and the track observations of the first track in a plurality of epochs, and determining a second residual of the track observations of the current track and the second track in a plurality of epochs, includes:
Solving the second observation equation based on a least square method to obtain a first estimated value of a similar transformation parameter and a second estimated value of the position correction of the satellite in a reference epoch;
based on the first and second estimates, first and second residuals for a plurality of epochs are determined.
In the above aspect, the determining the track value for track update based on the first observation equation includes:
The first observation equation is solved based on a least square method to obtain a third estimated value of a similar transformation parameter and a fourth estimated value of the position correction of the satellite in a reference epoch;
Determining a position correction of the track deviation of the first epoch in the second track based on the third estimate and the fourth estimate;
and determining a track value for track update based on the position correction of the track deviation of the first epoch in the second track and the track value of the first epoch in the second track.
In the above aspect, the determining, based on the third estimated value and the fourth estimated value, a position correction of the track deviation of the first epoch in the second track includes:
Determining a position correction of a track deviation of the reference epoch in the second track based on the third estimate and the fourth estimate;
And determining the position correction of the track deviation of the first epoch in the second track based on the position correction of the track deviation of the reference epoch in the second track and the position correction of the track deviation of the last epoch in the second track, wherein the position correction of the track deviation of the last epoch in the second track is constrained to be 0.
In the above scheme, the track smoothing weight matrix is:
wherein p=l·s, l is a predetermined empirical coefficient, s is a predetermined variance threshold, As a result of the error in the first phase,For the second medium error, t e is an arbitrary epoch, (0 is a reference epoch, t i characterizes the second trajectory, t i-1 characterizes the current trajectory, and t i-2 characterizes the first trajectory.
In another aspect, an embodiment of the present invention provides an electronic device, including a processor and a memory, where the processor and the memory are connected to each other, where the memory is configured to store a computer program, and the computer program includes program instructions, and the processor is configured to invoke the program instructions to execute the steps of the track jump processing method provided in the first aspect of the embodiment of the present invention.
In another aspect, embodiments of the present invention provide a computer-readable storage medium including a computer program stored thereon. The computer program when executed by a processor implements the steps of the track jump processing method as provided in the first aspect of the embodiment of the invention.
In another aspect, an embodiment of the present application further provides a computer program product, including a computer program, where the computer program when executed by a processor implements the steps of the track jump processing method described above.
The embodiment of the application determines a first middle error of fitting a current orbit of a satellite with a first orbit and a second middle error of fitting the current orbit with a second orbit, wherein the first orbit is a previous orbit of the current orbit of the satellite, and the second orbit is a forecast orbit obtained by batch processing based on the current orbit. And determining the value of a track smoothing weight matrix in a preset first observation equation based on the first intermediate error and the second intermediate error, wherein the track smoothing weight matrix characterizes the dependence degree of the track smoothing weight matrix on the current track or the first track during track fitting, and determining the track value for track updating based on the first observation equation. According to the embodiment of the application, the first middle error of the fitting of the current orbit of the satellite and the previous orbit is determined, the second middle error of the fitting of the current orbit and the forecast orbit is determined, the value of the orbit smoothing weight array in the first observation equation is determined according to the first middle error and the second middle error, the orbit smoothing degree of the satellite is adjusted based on the value of the orbit smoothing weight array, real-time orbit smoothing is realized, the problem of satellite orbit jump is effectively solved, the stability and the precision of precise orbit determination of the satellite are improved, the problem that the orbit jump of the front arc section and the rear arc section is larger under the conditions of ground shadow entering and exiting of the satellite, fewer observation values and the like in batch processing of the forecast orbit is avoided, so that the orbit precision is seriously reduced, and the self-adaptive robust real-time orbit smoothing is realized.
Drawings
Fig. 1 is a schematic implementation flow diagram of a track jump processing method according to an embodiment of the present invention;
Fig. 2 is a schematic diagram of a track jump processing apparatus according to an embodiment of the present invention;
fig. 3 is a schematic diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The global satellite navigation system (Global Navigation SATELLITE SYSTEM, GNSS) real-time precise positioning service is widely applied to the fields of multiple social production and scientific researches such as precise agriculture, mapping remote sensing, automatic driving, space weather monitoring, disaster monitoring and the like. The stable and reliable real-time high-precision track product is one of important foundations of wide-area, real-time and high-precision positioning services.
Currently, the high-precision GNSS real-time orbit determination technology mainly comprises two methods of batch processing prediction and real-time filtering. The real-time precise orbit products of the navigation satellites commonly used at present are mostly obtained by forecasting a dynamics model, namely an observation file updated in an hour level is used, satellite position speed and dynamics parameters are calculated by adopting a mode of post-batch processing, and then orbit integration is carried out to obtain a forecasting orbit. The overall observation is used to determine the "best" estimate of the track state at a certain epoch, the so-called batch process algorithm track. The real-time filtering orbit determination method is used for calculating and updating orbit state parameters on an epoch-by-epoch basis based on real-time observation data to obtain a real-time orbit product. The method can dynamically adjust random model compensation methods such as weight ratio relation of geometric observation information and dynamic information through adjusting process noise, improves real-time orbit precision and reliability during abnormal period of satellite dynamic model, but has larger system stability and orbit determination error, requires longer time (ten to tens of hours) to realize convergence of filtering orbit precision to centimeter level, and still is difficult to realize centimeter level real-time orbit jump processing under abnormal dynamics. Therefore, the batch forecasting method is a more common method for real-time precise track jump processing of the navigation satellite at present.
The batch processing forecasting orbit has the characteristics of high stability and orbit precision, under the condition of normal stress, the satellite motion is smoothly changed, the motion state of the satellite motion can be expressed through a high-precision dynamics model, and a real-time orbit product with higher precision can be obtained based on an orbit forecasting method of batch understanding. However, once the satellite stress situation changes abnormally, such as entering ground shadows, and abnormal satellite motion conditions such as orbit maneuver, the accuracy of the dynamic model is obviously reduced, and the obtained forecast orbit accuracy is obviously reduced or even not available. In addition, the periodic update (1 hour, 3 hours, 6 hours, etc.) of the batch track can cause remarkable track jump near the update epoch, the real-time track obtained by the method also has the arc segment splicing of a certain update period, and the discontinuous problem exists between the adjacent update arc segments, thereby seriously affecting the track fixing precision and stability of the method.
Aiming at the defects of the related technology, the embodiment of the invention provides an orbit jump processing method which can improve the stability and the precision of precise orbit determination of a satellite. In order to illustrate the technical scheme of the invention, the following description is made by specific examples.
Fig. 1 is a schematic implementation flow diagram of a track jump processing method according to an embodiment of the present invention, where an execution body of the track jump processing method is an electronic device. Referring to fig. 1, the track jump processing method includes:
S101, determining a first middle error of fitting a current orbit of a satellite with a first orbit and a second middle error of fitting the current orbit with a second orbit, wherein the first orbit is a previous orbit of the current orbit of the satellite, and the second orbit is a forecast orbit obtained by batch processing based on the current orbit.
It will be appreciated that the second orbit is a predicted orbit obtained using batch processing techniques in the related art, and that satellites have not yet been brought into the second orbit.
The application refers to the update time of the interval between two adjacent batch processing tracks, wherein the interval is 6 hours, 3 hours or 1 hour, and the two batch processing tracks are also called as adjacent arc sections. Typically batch tracks are resolved for 40-48 hours and forecast for 24 hours. For an arc segment with an initial epoch of t i-2, the arc length of the track jump processing part is t arc, the batch understanding time is Δt slv, the track with the duration of Δt hours is updated, and the real-time track period available to the user is [ t i-2+Δt,ti-2 +2Δt ]. For the i-1 th track update, the real track can use the i-2 th or i-1 th track, and the two tracks are different due to the influence of geometric and dynamic factors, so that track jump is generated.
The middle error is a digital standard for measuring the accuracy of observation, and is the square root of the ratio of the square sum of the observed value and the true value deviation to the number of observation times n, and the size of the middle error reflects the accuracy of the group of observed values.
Here, the middle error of the two orbit fits refers to the median of the orbit residual error after the orbit is fitted according to dynamics, and the middle error can be calculated according to the corresponding orbit observation value residual error.
For example, a batch track before and after the ith update is determinedAndAlthough the satellite positions should be equal for any of the same epoch t e for the two sets of orbits, there is a difference Δo (t e) between them due to orbit dynamics and geometrical observation errors:
In the middle of AndRespectively as railsAndSatellite position at t e epoch.
Batch track before and after the ith updateAndSatellite position at the same epoch tAndConstructing a track fitting equation for the pseudo-observed values:
Where x is a parameter to be estimated, which includes similar transformation parameters H such as translation, rotation, and scale, and the epoch satellite orbit correction value dO (t). It is considered that dO (t) can be obtained from the state transition matrix Φ (t, t i0) and the satellite position correction dO (t i0) of the reference epoch t i0:
dO(t)=Φ(t,ti0)dO(ti0) (3)
thus, formula (2) can be expressed as follows:
wherein the method comprises the steps of Is in orbit for satelliteX, Y and the Z direction at the time of the medium t epoch.
Equation (4) can be solved directly by using least squares algorithm to obtain the estimated values of the similar transformation parameters H and the satellite position correction dO (t i0) of the satellite at the reference epoch t i0 AndThe least squares solution may employ equal weights.
Bringing this into equation (4), the corresponding orbit observations residuals at any instant can be obtained:
From the multiple moment orbit observations residuals v (t e), the middle error σ AB of the orbit fit can be calculated according to:
wherein N is the number of observed values.
According to the method, the track can be calculatedAndMiddle error of fitting if the current track isThe calculated σ AB is the second median error, and the first median error can be calculated similarly.
S102, determining the value of a track smoothing weight matrix in a preset first observation equation based on the first intermediate error and the second intermediate error, wherein the track smoothing weight matrix represents the dependence degree of the track smoothing weight matrix on the current track or the first track during track fitting.
In the related art, when the reference time is selected as the track jump time t u, the estimated similarity transformation parameter is usedAndThe track can be calculated according to the followingAnd a trackJump at time t u
Adding it to the trackAnd (3) the satellite positions at the subsequent time of t u in the sequence can realize adjacent real-time orbit connection.
The related art forces the next trackConnected to the previous trackAnd (3) upper part. The method is influenced by a dynamic model, geometric observation errors and the like, and particularly, the track jump of the front arc section and the rear arc section is larger under the conditions of satellite ground shadow entering and exiting, fewer observation values and the like.
It can be seen that the mandatory connection will severely reduce the real-time track accuracy, so that a corresponding adaptation factor needs to be set to dynamically control the degree of current real-time track smoothness. The track smoothing weight matrix P (t e) composed of the adaptive factors P can be calculated according to the above-mentioned middle error of track fitting.
The dependence degree of the current arc section on the front and back adjacent arc sections (the current track and the first track) in the smoothing process can be controlled through the track smoothing weight matrix. When the middle error (second middle error) of the current arc fitting is relatively large, the smooth track is mainly calculated according to the previous arc, otherwise, the current arc information is mainly adopted for fitting and smoothing. Here, the arc section refers to a track.
For example, the values of different track smoothing weight arrays can be set according to the magnitudes of the first middle error and the second middle error, the corresponding relation is pre-stored in a database, and the values of the corresponding track smoothing weight arrays are read according to the magnitudes of the first middle error and the second middle error when the track smoothing weight array is used.
In an embodiment, the track smoothing weight matrix is:
wherein p=l·s, l is a predetermined empirical coefficient, s is a predetermined variance threshold, As a result of the error in the first phase,The second error, t e, is any time, t i0 is a reference time, t i represents the second track, t i-1 represents the current track, and t i-2 represents the first track.
L is an empirical coefficient to adjust the weight of different fitting epoch t observation values in the formula (2), s is a front-back adjacent arc segment orbit variance threshold, a global positioning system (Global Positioning System, GPS) and a global satellite navigation system (Global Navigation SATELLITE SYSTEM, GLONASS) can be set to 3, and a Beidou satellite navigation system (BeiDou Navigation SATELLITE SYSTEM, BDS) and a Galileo satellite navigation system (Galileo satellite navigation system, galileo) can be set to 5. The dependence degree of the current arc section on the adjacent arc sections in the smoothing process can be controlled through the track smoothing weight array P (t e). Error in fitting when the current arc isAnd when the error in the second process is relatively large, the smooth track is mainly calculated according to the previous arc segment, and otherwise, the current arc segment information is mainly adopted for fitting and smoothing.
S103, determining a track value for track updating based on the first observation equation.
For example, the track smoothing weight matrix is denoted as P (t e), then the first observation equation can be expressed as:
The value of the orbit smoothing weight matrix can dynamically control the current real-time orbit smoothing degree, and the situation that the orbit jump of the front arc section and the rear arc section is larger under the conditions of satellite ground shadow entering and exiting, fewer observation values and the like of a batch processing forecast orbit is avoided.
Based on the first observation equation, the track values for track update are re-forecasted and applied to the subsequently updated track to achieve real-time track smoothing.
The related art batch process can be used for forecasting the track, and the difference is that the application sets the weight parameter for controlling the smooth degree of the track, so that the track jump of the front arc section and the rear arc section is avoided to be larger.
The embodiment of the application determines a first middle error of fitting a current orbit of a satellite with a first orbit and a second middle error of fitting the current orbit with a second orbit, wherein the first orbit is a previous orbit of the current orbit of the satellite, and the second orbit is a forecast orbit obtained by batch processing based on the current orbit. And determining the value of a track smoothing weight matrix in a preset first observation equation based on the first intermediate error and the second intermediate error, wherein the track smoothing weight matrix characterizes the dependence degree of the track smoothing weight matrix on the current track or the first track during track fitting, and determining the track value for track updating based on the first observation equation. According to the embodiment of the application, the first middle error of the fitting of the current orbit of the satellite and the previous orbit is determined, the second middle error of the fitting of the current orbit and the forecast orbit is determined, the value of the orbit smoothing weight array in the first observation equation is determined according to the first middle error and the second middle error, the orbit smoothing degree of the satellite is adjusted based on the value of the orbit smoothing weight array, real-time orbit smoothing is realized, the problem of satellite orbit jump is effectively solved, the stability and the precision of precise orbit determination of the satellite are improved, the problem that the orbit jump of the front arc section and the rear arc section is larger under the conditions of ground shadow entering and exiting of the satellite, fewer observation values and the like in batch processing of the forecast orbit is avoided, so that the orbit precision is seriously reduced, and the self-adaptive robust real-time orbit smoothing is realized.
In an embodiment, the determining the first intermediate error of the current orbit of the satellite to fit to the first orbit and the second intermediate error of the current orbit to fit to the second orbit includes:
Determining a first residual of the current orbit and the orbit observations of the first orbit in a plurality of epochs based on a second observation equation, and determining a second residual of the current orbit and the orbit observations of the second orbit in a plurality of epochs;
the first medium error is determined based on a first residual of a plurality of epochs and the second medium error is determined based on a second residual of the plurality of epochs.
Before this, the method further comprises:
And constructing the second observation equation by taking satellite positions in the same epoch in adjacent orbits as observation values.
For example, batch tracks before and after the ith updateAndSatellite position at the same epoch tAndConstructing a second observation equation for the pseudo-observations:
For example, the number of the cells to be processed, For the current track to be a current track,Is the second track.
Where x is a parameter to be estimated, which includes similar transformation parameters H such as translation, rotation, and scale, and the epoch satellite orbit correction value dO (t). It is considered that dO (t) can be obtained from the state transition matrix Φ (t, t i0) and the satellite position correction dO (t i0) of the reference epoch t i0:
dO(t)=Φ(t,ti0)dO(ti0)
Thus, the second observation equation may be expressed as follows:
wherein the method comprises the steps of Is in orbit for satelliteX, Y and the Z direction at the time of the medium t epoch.
In an embodiment, the determining, based on the second observation equation, a first residual of the current track and the track observations of the first track over a plurality of epochs, and determining a second residual of the current track and the track observations of the second track over a plurality of epochs, includes:
Solving the second observation equation based on a least square method to obtain a first estimated value of a similar transformation parameter and a second estimated value of the position correction of the satellite in a reference epoch;
based on the first and second estimates, first and second residuals for a plurality of epochs are determined.
The second observation equation can be directly solved by using least squares algorithm to obtain the estimated values of the similar transformation parameters H and the satellite position correction dO (t i0) of the satellite at the reference epoch t i0 AndThe least squares solution may employ equal weights.
Bringing this into equation (4), any epoch corresponding orbit observations residual can be obtained:
From the orbit observations residuals v (t e) for multiple epochs, the medium error σ AB of the orbit fit can be calculated according to:
wherein N is the number of observed values.
According to the above method, the first medium error and the second medium error can be calculated.
In an embodiment, the method further comprises:
and constructing the first observation equation based on the track smoothing weight array and the second observation equation.
And adding the track smoothing weight matrix as a weight parameter into the second observation equation, thereby obtaining a weighted first observation equation.
In the above embodiment, the second observation equation is expressed as follows:
The track smoothing weight matrix is denoted as P (t e), then the first observation equation can be expressed as:
In an embodiment, the track smoothing weight matrix is:
wherein p=l·s, l is a predetermined empirical coefficient, s is a predetermined variance threshold, As a result of the error in the first phase,The second error, t e, is an arbitrary epoch and t i0 is a reference epoch. t i characterizes the second trajectory, t i-1 characterizes the current trajectory, and t i-2 characterizes the first trajectory.
The dependence degree of the current track on the front and back adjacent tracks (the current track and the first track) in the track smoothing process can be controlled through the track smoothing weight array. When the middle error (second middle error) of the current track fitting is relatively large, the smooth track is mainly calculated according to the previous track, otherwise, the current track information is mainly adopted for fitting smoothing.
In an embodiment, the determining a track value for track update based on the first observation equation includes:
The first observation equation is solved based on a least square method to obtain a third estimated value of a similar transformation parameter and a fourth estimated value of the position correction of the satellite in a reference epoch;
Determining a position correction of the track deviation of the first epoch in the second track based on the third estimate and the fourth estimate;
and determining a track value for track update based on the position correction of the track deviation of the first epoch in the second track and the track value of the first epoch in the second track.
The least square adjustment is adopted to obtain the latest estimated value of the similar transformation parameter H and the satellite position correction dO (t i0) of the satellite at the reference time t i0, and the orbit can be obtained by using the formula (4)Correction of track deviation at medium t e epochCan be used for track updating, and each component isThe corrected track value may be calculated using the following equation:
wherein t e is a first epoch, For the position correction of the track deviation of the first epoch in the second track,Is the track value of the first epoch in the second track. Original track value in second trackBased on the correction of track deviationFor the original track valueCorrecting to obtain corrected track valueThe corrected track value is applied to the subsequent updated track to achieve real-time track smoothing.
In an embodiment, the determining the position correction of the track deviation of the first epoch in the second track based on the third estimate and the fourth estimate includes:
Determining a position correction of a track deviation of the reference epoch in the second track based on the third estimate and the fourth estimate;
And determining the position correction of the track deviation of the first epoch in the second track based on the position correction of the track deviation of the reference epoch in the second track and the position correction of the track deviation of the last epoch in the second track, wherein the position correction of the track deviation of the last epoch in the second track is constrained to be 0.
Calculating the position correction of the orbit deviation of the reference epoch according to the above formula (4) based on the third estimated value and the fourth estimated valueThe correction constraint at the last epoch t i1 is 0, at this time, the current arc is at any time the track prior deviation correctionCan be expressed as:
wherein, the The position component at t i1 epoch isUsing the above formulaTrack values that are available to the user for track updates may be obtained.
According to the embodiment of the application, transformation parameters are introduced when the adjacent arc segment orbits are fitted by using a dynamic model, so that the orbit residual error median represents the fitting precision, and an orbit smoothing weight matrix is constructed according to the fitting precision to adjust the smoothing weight, so that real-time orbit smoothing is realized, the problem that the orbit precision is seriously reduced due to larger track jumping of front and rear arc segments under the conditions of satellite ground shadow entering and exiting, fewer observation values and the like of a batch processing forecast orbit is avoided, and self-adaptive robust real-time orbit smoothing is realized. The problem of track jump is effectively solved, and the stability and the precision of precise orbit determination of the satellite are improved. The jump of the adjacent arc segments at the track updating moment is estimated and applied to the subsequent updated track to realize real-time track smoothing.
According to the embodiment of the application, the precision of GNSS satellite orbit determination is provided, the error of GNSS satellite orbit prediction is corrected, and high-precision precise orbit data is obtained. In the satellite-based enhanced service, the precise orbit is broadcast to the user terminal as one of the precise corrections, and the positioning accuracy can be greatly improved because the satellite orbit error is basically eliminated.
The technical scheme provided by the embodiment of the application can be applied to the future new product star-based enhanced positioning, provides high-precision positioning service for the fields of intelligent driving, unmanned aerial vehicle, ocean construction, measurement and mapping and the like, and has wider market prospect and commercial value.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.
It should be understood that the terms "comprises" and "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The technical schemes described in the embodiments of the present invention may be arbitrarily combined without any collision.
In addition, in the embodiments of the present invention, "first", "second", etc. are used to distinguish similar objects and are not necessarily used to describe a particular order or precedence.
Referring to fig. 2, fig. 2 is a schematic diagram of a track jump processing apparatus according to an embodiment of the present invention, as shown in fig. 2, the apparatus includes:
The system comprises a first determining module, a second determining module and a first determining module, wherein the first determining module is used for determining a first middle error of fitting a current orbit of a satellite with a first orbit and a second middle error of fitting the current orbit with a second orbit, the first orbit is a previous orbit of the current orbit of the satellite, and the second orbit is a forecast orbit obtained by batch processing based on the current orbit;
the second determining module is used for determining the value of a track smoothing weight matrix in a preset first observation equation based on the first middle error and the second middle error, wherein the track smoothing weight matrix characterizes the dependence degree of the track smoothing weight matrix on a current track or the first track during track fitting;
and a third determining module for determining a track value for track update based on the first observation equation.
In an embodiment, the first determining module is specifically configured to:
Determining a first residual of the current orbit and the orbit observations of the first orbit in a plurality of epochs based on a second observation equation, and determining a second residual of the current orbit and the orbit observations of the second orbit in a plurality of epochs;
the first medium error is determined based on a first residual of a plurality of epochs and the second medium error is determined based on a second residual of the plurality of epochs.
In an embodiment, the device further comprises:
And the first construction module is used for constructing the second observation equation by taking satellite positions in the same epoch in adjacent orbits as observation values.
In an embodiment, the device further comprises:
And the second construction module is used for constructing the first observation equation based on the track smoothing weight array and the second observation equation.
In one embodiment, the first determining module is specifically configured to calculate the second observation equation based on a least square algorithm to obtain a first estimated value of a similar transformation parameter and a second estimated value of a position correction of the satellite in a reference epoch;
based on the first and second estimates, first and second residuals for a plurality of epochs are determined.
In an embodiment, the third determining module is specifically configured to:
The first observation equation is solved based on a least square method to obtain a third estimated value of a similar transformation parameter and a fourth estimated value of the position correction of the satellite in a reference epoch;
Determining a position correction of the track deviation of the first epoch in the second track based on the third estimate and the fourth estimate;
and determining a track value for track update based on the position correction of the track deviation of the first epoch in the second track and the track value of the first epoch in the second track.
In an embodiment, the third determining module is specifically configured to:
Determining a position correction of a track deviation of the reference epoch in the second track based on the third estimate and the fourth estimate;
And determining the position correction of the track deviation of the first epoch in the second track based on the position correction of the track deviation of the reference epoch in the second track and the position correction of the track deviation of the last epoch in the second track, wherein the position correction of the track deviation of the last epoch in the second track is constrained to be 0.
In an embodiment, the track smoothing weight matrix is:
wherein p=l·s, l is a predetermined empirical coefficient, s is a predetermined variance threshold, As a result of the error in the first phase,For the second medium error, t e is an arbitrary epoch, t i0 is a reference epoch, t i characterizes the second track, t i-1 characterizes the current track, and t i-2 characterizes the first track.
In practical applications, the first determining module, the second determining module and the third determining module may be implemented by a Processor in the electronic device, such as a central processing unit (CPU, central Processing Unit), a digital signal Processor (DSP, digital Signal Processor), a micro control unit (MCU, microcontroller Unit), or a Programmable gate array (FPGA, field-Programmable GATE ARRAY), etc.
It should be noted that, when the track jump processing device provided in the above embodiment performs track jump processing, only the division of the above modules is used for illustration, in practical application, the processing and allocation may be performed by different modules according to needs, that is, the internal structure of the device is divided into different modules, so as to complete all or part of the processing described above. In addition, the track jump processing device and the track jump processing method provided in the foregoing embodiments belong to the same concept, and specific implementation processes thereof are detailed in the method embodiments, which are not repeated herein.
The track jump processing device can be in the form of an image file, and the image file can be operated in the form of a container or a virtual machine after being executed so as to realize the track jump processing method. Of course, the method is not limited to the image file form, and any software form capable of implementing the track jump processing method of the application is within the scope of the application.
Based on the hardware implementation of the program modules, and in order to implement the method of the embodiment of the present application, the embodiment of the present application further provides an electronic device. Fig. 3 is a schematic diagram of a hardware composition structure of an electronic device according to an embodiment of the present application, where, as shown in fig. 3, the electronic device includes:
A communication interface 301 capable of information interaction with other devices such as a network device and the like;
and the processor 302 is connected with the communication interface 301 to realize information interaction with other devices, and is used for executing the method provided by one or more technical schemes on the electronic device side when running the computer program. And the computer program is stored on the memory 303.
Of course, in actual practice, the various components in the electronic device are coupled together by bus system 304. It is understood that bus system 304 is used to enable connected communications between these components. The bus system includes a power bus, a control bus, and a status signal bus in addition to the data bus. But for clarity of illustration the various buses are labeled as bus system 304 in fig. 3.
The memory 303 in embodiments of the present application is used to store various types of data to support the operation of the electronic device. Examples of such data include any computer program for operating on an electronic device.
It will be appreciated that the memory 303 can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. The non-volatile Memory may be, among other things, a Read Only Memory (ROM), a programmable Read Only Memory (PROM, programmable Read-Only Memory), erasable programmable Read-Only Memory (EPROM, erasable Programmable Read-Only Memory), electrically erasable programmable Read-Only Memory (EEPROM, ELECTRICALLY ERASABLE PROGRAMMABLE READ-Only Memory), Magnetic random access Memory (FRAM, ferromagnetic random access Memory), flash Memory (Flash Memory), magnetic surface Memory, optical disk, or compact disk-Only Memory (CD-ROM, compact Disc Read-Only Memory), which may be disk Memory or tape Memory. The volatile memory may be random access memory (RAM, random Access Memory) which acts as external cache memory. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM, static Random Access Memory), synchronous static random access memory (SSRAM, synchronous Static Random Access Memory), dynamic random access memory (DRAM, dynamic Random Access Memory), synchronous dynamic random access memory (SDRAM, synchronous Dynamic Random Access Memory), and, Double data rate synchronous dynamic random access memory (DDRSDRAM, double Data Rate Synchronous Dynamic Random Access Memory), enhanced synchronous dynamic random access memory (ESDRAM, enhanced Synchronous Dynamic Random Access Memory), synchronous link dynamic random access memory (SLDRAM, syncLink Dynamic Random Access Memory), Direct memory bus random access memory (DRRAM, direct Rambus Random Access Memory). the memory described by embodiments of the present application is intended to comprise, without being limited to, these and any other suitable types of memory.
The method disclosed in the above embodiment of the present application may be applied to the processor 302 or implemented by the processor 302. The processor 302 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or by instructions in the form of software. The processor 302 described above may be a general purpose processor, DSP, or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. The processor may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present application. The general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed in the embodiment of the application can be directly embodied in the hardware of the decoding processor or can be implemented by combining hardware and software modules in the decoding processor. The software modules may be located in a storage medium having a memory, and the processor reads the program in the memory and performs the steps of the method in combination with its hardware.
Optionally, when the processor executes the program, a corresponding flow implemented by the electronic device in each method of the embodiment of the present application is implemented, and for brevity, will not be described herein.
In an exemplary embodiment, the present application also provides a storage medium, i.e. a computer storage medium, in particular a computer readable storage medium, for example comprising a first memory storing a computer program, which is executable by a processor of an electronic device to perform the steps of the aforementioned method. The computer readable storage medium may be FRAM, ROM, PROM, EPROM, EEPROM, flash Memory, magnetic surface Memory, optical disk, or CD-ROM.
In an exemplary embodiment, the present application also provides a computer program product, which includes a computer program, where the computer program is executable by the processor 302 of the electronic device to perform the steps described in the track jump processing method according to the embodiment of the present application.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus, electronic device, and method may be implemented in other manners. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is merely a logical function division, and there may be additional divisions of actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described as separate components may or may not be physically separate, and components displayed as units may or may not be physical units, may be located in one place, may be distributed on a plurality of network units, and may select some or all of the units according to actual needs to achieve the purpose of the embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of hardware plus a form of software functional unit.
It will be appreciated by those of ordinary skill in the art that implementing all or part of the steps of the above method embodiments may be accomplished by hardware associated with program instructions, and that the above program may be stored on a computer readable storage medium which, when executed, performs the steps comprising the above method embodiments, where the above storage medium includes various media that can store program code, such as removable storage devices, ROM, RAM, magnetic or optical disks.
Or the above-described integrated units of the application may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solution of the embodiments of the present application may be embodied essentially or in a part contributing to the related art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the methods described in the embodiments of the present application. The storage medium includes various media capable of storing program codes such as a removable storage device, a ROM, a RAM, a magnetic disk or an optical disk.
The technical schemes described in the embodiments of the present application may be arbitrarily combined without any collision.
In addition, in the present examples, "first," "second," etc. are used to distinguish similar objects and not necessarily to describe a particular order or sequence.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (11)
1. A track jump processing method, the method comprising:
Determining a first middle error of fitting a current orbit of a satellite with a first orbit and a second middle error of fitting the current orbit with a second orbit, wherein the first orbit is a previous orbit of the current orbit of the satellite, and the second orbit is a forecast orbit obtained by batch processing based on the current orbit;
Determining the value of a track smoothing weight matrix in a preset first observation equation based on the first intermediate error and the second intermediate error, wherein the track smoothing weight matrix characterizes the dependence degree of the track smoothing weight matrix on a current track or the first track during track fitting;
A track value for track update is determined based on the first observation equation.
2. The method of claim 1, wherein determining a first intermediate error in the fit of the current orbit of the satellite to the first orbit and a second intermediate error in the fit of the current orbit to the second orbit comprises:
Determining a first residual of the current orbit and the orbit observations of the first orbit in a plurality of epochs based on a second observation equation, and determining a second residual of the current orbit and the orbit observations of the second orbit in a plurality of epochs;
the first medium error is determined based on a first residual of a plurality of epochs and the second medium error is determined based on a second residual of the plurality of epochs.
3. The method according to claim 2, wherein the method further comprises:
And constructing the second observation equation by taking satellite positions in the same epoch in adjacent orbits as observation values.
4. A method according to claim 3, characterized in that the method further comprises:
and constructing the first observation equation based on the track smoothing weight array and the second observation equation.
5. The method of claim 2, wherein the determining a first residual of the current trajectory and the trajectory observations of the first trajectory over a plurality of epochs based on the second observation equation, and determining a second residual of the trajectory observations of the current trajectory and the second trajectory over a plurality of epochs, comprises:
Solving the second observation equation based on a least square method to obtain a first estimated value of a similar transformation parameter and a second estimated value of the position correction of the satellite in a reference epoch;
based on the first and second estimates, first and second residuals for a plurality of epochs are determined.
6. The method of claim 1, wherein the determining a track value for track update based on the first observation equation comprises:
The first observation equation is solved based on a least square method to obtain a third estimated value of a similar transformation parameter and a fourth estimated value of the position correction of the satellite in a reference epoch;
Determining a position correction of the track deviation of the first epoch in the second track based on the third estimate and the fourth estimate;
and determining a track value for track update based on the position correction of the track deviation of the first epoch in the second track and the track value of the first epoch in the second track.
7. The method of claim 6, wherein the determining a position correction for the track deviation for the first epoch in the second track based on the third estimate and the fourth estimate comprises:
Determining a position correction of a track deviation of the reference epoch in the second track based on the third estimate and the fourth estimate;
And determining the position correction of the track deviation of the first epoch in the second track based on the position correction of the track deviation of the reference epoch in the second track and the position correction of the track deviation of the last epoch in the second track, wherein the position correction of the track deviation of the last epoch in the second track is constrained to be 0.
8. The method of claim 1, wherein the track smoothing weight matrix is:
wherein p=l·s, l is a predetermined empirical coefficient, s is a predetermined variance threshold, As a result of the error in the first phase,For the second medium error, t e is an arbitrary epoch, t i0 is a reference epoch, t i characterizes the second track, t i-1 characterizes the current track, and t i-2 characterizes the first track.
9. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, realizes the steps of the method according to any one of claims 1 to 8.
10. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the track jump processing method according to any one of claims 1 to 8 when executing the computer program.
11. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program comprising program instructions which, when executed by a processor, cause the processor to perform the track jump processing method according to any of claims 1 to 8.
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| CN108761505A (en) * | 2018-06-04 | 2018-11-06 | 北京未来导航科技有限公司 | A kind of processing method and system of navigation satellite prediction orbit |
| CN110231037A (en) * | 2019-05-24 | 2019-09-13 | 武汉大学 | A kind of GNSS maneuvering satellite orbit determination method of additional clock bias model constraint |
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| JP2013190335A (en) * | 2012-03-14 | 2013-09-26 | Seiko Epson Corp | Position calculation method and position calculation device |
| CN109387859B (en) * | 2017-08-14 | 2023-05-30 | 千寻位置网络有限公司 | Method and apparatus for generating long-term satellite orbit and clock bias based on ground tracking station |
| CN114912367A (en) * | 2022-06-09 | 2022-08-16 | 江西日月明测控科技股份有限公司 | Method and system for predicting static irregularity trend of track, electronic device and storage medium |
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| CN108761505A (en) * | 2018-06-04 | 2018-11-06 | 北京未来导航科技有限公司 | A kind of processing method and system of navigation satellite prediction orbit |
| CN110231037A (en) * | 2019-05-24 | 2019-09-13 | 武汉大学 | A kind of GNSS maneuvering satellite orbit determination method of additional clock bias model constraint |
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