CN112556722A - System error compensation method based on automatic selection of preferred source - Google Patents

System error compensation method based on automatic selection of preferred source Download PDF

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CN112556722A
CN112556722A CN202011262084.8A CN202011262084A CN112556722A CN 112556722 A CN112556722 A CN 112556722A CN 202011262084 A CN202011262084 A CN 202011262084A CN 112556722 A CN112556722 A CN 112556722A
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information source
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information
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CN112556722B (en
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张英静
权晓岚
刘明阳
臧振宇
吴天昊
温嘉奇
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Beijing Institute of Electronic System Engineering
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • 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
    • G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
    • 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
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Abstract

One embodiment of the invention discloses a system error compensation method based on automatic selection of a preferred source, which comprises the following steps: acquiring a measurement value of each information source; performing space-time calibration on the measurement value of the information source; calculating the measurement quality of the information sources, and selecting one of the information sources as a preferred source as a compensation reference; carrying out coordinate conversion on the measurement values of the other information sources according to the compensation reference; and calculating the slope distance, azimuth angle and pitch angle of each information source and the compensation quantity thereof.

Description

System error compensation method based on automatic selection of preferred source
Technical Field
The present invention relates to the field of target tracking. And more particularly, to a systematic error compensation method based on automatically selecting a preferred source.
Background
Different information sources detect the target under respective independent local coordinate systems, and errors can occur when the different information sources detect the same target due to different conditions such as sensor precision, deployment terrain, climate and the like. If the error is too large, the track association fusion fails, so that error compensation is needed before information fusion. The errors mainly comprise random errors and system errors, the random errors can be eliminated through a flight path parameter fusion method, and the traditional system error compensation method is divided into absolute error compensation and relative error compensation. The complexity of absolute error compensation is high, and engineering realization is not facilitated; the relative error compensation needs to select a certain information source as a compensation reference in advance, and the traditional relative error compensation mostly adopts a manual source selection mode, so that the source selection is inaccurate.
Disclosure of Invention
In view of the above, a first embodiment of the present invention provides a method for compensating systematic error based on automatically selecting a preferred source, including:
acquiring a measurement value of each information source;
performing space-time calibration on the measurement value of the information source;
calculating the measurement quality of the information sources, and selecting one of the information sources as a preferred source as a compensation reference;
carrying out coordinate conversion on the measurement values of the other information sources according to the compensation reference;
and calculating the slope distance, azimuth angle and pitch angle of each information source and the compensation quantity thereof.
In a specific embodiment, the obtaining the measurement value of each information source includes:
m information sources view the same target information in the same time slot, and the command control system receives M measured value information, indicated as M measured values, from each information source at time t1
Figure BDA0002774971840000011
Wherein i (i is more than or equal to 1 and less than or equal to M) is the identification number of the information source,
Figure BDA0002774971840000012
the X-direction coordinate of the measurement from the ith source at time t1,
Figure BDA0002774971840000013
the Y-direction coordinate of the measurement from the ith source at time t1,
Figure BDA0002774971840000014
the Z-direction coordinate of the measurement from the ith source at time t 1.
In a specific embodiment, the time-space calibration is performed by calibrating each information source according to the ith information source measurement value time point with high observation frequency;
the ith information source quantity of the high observation frequency is the information source with the highest observation frequency in the M information sources;
if the high observation frequency information source has measurement values at N time points, the time points are t1 and t2 … tN, then the X-direction coordinate of the ith information source at the time point t1 is calculated as
Figure BDA0002774971840000021
Wherein, tk-1、tkAnd tk+1The point in time at which the ith information source has a measurement value, and tk-1≤t1≤tk≤tk+1；
Similarly, the Y-direction coordinate of the ith information source at the time t1 is calculated as
Figure BDA0002774971840000022
Calculating the Z-direction coordinate of the ith information source at the time t1 as
Figure BDA0002774971840000023
In one embodiment, the calculating the metrology quality of the information source includes: computing an innovation covariance matrix for an information source
Figure BDA0002774971840000024
Andpredicting innovation of measured and measured values
Figure BDA0002774971840000025
A normalized distance function is derived from the distance data,
Figure BDA0002774971840000026
thus, the ith source measurement quality at time t2 is obtained
Figure BDA0002774971840000027
Wherein, alpha is a history weight factor,
Figure BDA0002774971840000028
measuring quality for the ith source at time t 1;
information source measurement quality
Figure BDA0002774971840000029
The smaller the better the quality, the better the preferred source is selected from the M sources.
In one embodiment, the computing information source calculates an innovation value of the predictive measurements and the metrology values
Figure BDA00027749718400000210
The method comprises the following steps: the state vector for the ith source measurement at time t1 is calculated as
Figure BDA00027749718400000211
Wherein,
Figure BDA00027749718400000212
respectively, the velocity measurement values in the directions of X, Y, Z]' denotes matrix transposition;
the state transition matrix is
Figure BDA0002774971840000031
Wherein T is the time difference between the current time and the last time;
using the state transition matrix, the predicted state matrix at the next time t2 is calculated as
Figure BDA0002774971840000032
The prediction state matrix at the time t2 is used to calculate a prediction measurement matrix as
Figure BDA0002774971840000033
Wherein, H is a measurement matrix,
Figure BDA0002774971840000034
then the measured value is predicted to be new
Figure BDA0002774971840000035
In one embodiment, the innovation covariance matrix of the information source
Figure BDA0002774971840000036
The method comprises the following steps:
the covariance matrix of the predicted state at time t2 is calculated as
Figure BDA0002774971840000037
Wherein,
Figure BDA0002774971840000038
the state covariance matrix is predicted for time t1, and Q is the covariance matrix of the process noiseThe process noise parameters Q1, Q2 and Q3 are set according to actual needs,
Figure BDA0002774971840000039
calculate an innovation covariance matrix of
Figure BDA00027749718400000310
Wherein,
Figure BDA00027749718400000311
to measure the noise matrix, DrX，DrY，DrZStandard deviation at time t2
Figure BDA0002774971840000041
In a specific embodiment, the coordinate transformation includes:
assuming the nth source as the preferred source, the ith source measures the value position vector at time t1
Figure BDA0002774971840000042
After conversion to the north-Tiandong coordinate system, it is recorded as
Figure BDA0002774971840000043
Figure BDA0002774971840000044
Wherein,
Figure BDA0002774971840000045
is the measured component of the ith information source in CGCS-2000 series.
Figure BDA0002774971840000046
For the nth information sourcePosition vector of EGIs a transformation matrix from GCS2000 system to North heaven coordinate system,
Figure BDA0002774971840000047
λ、
Figure BDA0002774971840000048
respectively, the geodetic longitude and the geodetic latitude of the position of the nth information source.
In a specific embodiment, the calculating the compensation amount of the slope, the azimuth and the pitch of each information source comprises:
converting the north-Tiandong xyz coordinate system into RAE direction coordinates, and calculating the slope distance R at the time of t1iT1, azimuth AiT1 and pitch angle Ei_t1，
Figure BDA0002774971840000049
Figure BDA00027749718400000410
Figure BDA00027749718400000411
At time t1, the system error compensation value is
ΔZ(t1)＝[Ri_t1,Ai_t1,Ei_t1]-[Rn_t1,An_t1,En_t1]
As the mean value of random errors is 0 under the condition of data accumulation, the measurement value between T1 and tN is selected for statistical calculation, and the period of the 1 st information source is T
Figure BDA00027749718400000412
Where k is any one of N time points at which the high observation frequency information source has a measurement value.
A second embodiment of the invention provides a computer device comprising a processor and a memory stored with a computer program, the processor implementing the method according to any one of the first embodiment when executing the program.
A third embodiment of the invention provides a computer-readable storage medium, on which a computer program is stored which, when executed by a processor, implements the method according to any one of the first embodiments.
The invention has the following beneficial effects:
the invention aims to provide a system error compensation method based on automatic selection of an optimal source.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a system architecture diagram of a system error compensation method based on automatic selection of a preferred source according to an embodiment of the present invention.
Fig. 2 shows a flow chart of a systematic error compensation method based on automatic selection of preferred sources according to an embodiment of the present invention.
Fig. 3 shows a schematic structural diagram of a computer device according to another embodiment of the present invention.
Detailed Description
In order to make the technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
As shown in fig. 1, for a system framework diagram of a method for compensating system error based on automatically selecting a preferred source according to an embodiment of the present invention, the system architecture may include an information source data set 101 and an instruction control system 103. The information source data set 101 includes measurement values of a plurality of information sources, the information sources may be any flying objects such as airplanes and drones, and the command control system 103 provides a server for providing various services, for example, a background server for providing support for automatically selecting a preferred source.
It should be noted that the information source data set 101 may be stored on other devices, on a network, or directly in the command control system 103, which is not limited in this application.
As shown in fig. 2, a method for compensating systematic error based on automatically selecting a preferred source includes:
acquiring a measurement value of each information source;
m information sources view the same target information in the same time slot, and the command control system receives M measured value information, indicated as M measured values, from each information source at time t1
Figure BDA0002774971840000061
Wherein i (i is more than or equal to 1 and less than or equal to M) is the identification number of the information source,
Figure BDA0002774971840000062
the X-direction coordinate of the measurement from the ith source at time t1,
Figure BDA0002774971840000063
the Y-direction coordinate of the measurement from the ith source at time t1,
Figure BDA0002774971840000064
the Z-direction coordinate of the measurement from the ith source at time t 1.
Performing space-time calibration on the measurement value of the information source;
each information source is calibrated according to the ith information source measurement value time point with high observation frequency;
the ith information source quantity of the high observation frequency is the information source with the highest observation frequency in the M information sources;
if the high observation frequency information source has measurement values at N time points, the time points are t1 and t2 … tN, then the X-direction coordinate of the ith information source at the time point t1 is calculated as
Figure BDA0002774971840000065
Wherein, tk-1、tkAnd tk+1The time point of the jth information source with the measured value, and tk-1≤t1≤tk≤tk+1；
Similarly, the Y-direction coordinate of the ith information source at the time t1 is calculated as
Figure BDA0002774971840000066
Calculating the Z-direction coordinate of the ith information source at the time t1 as
Figure BDA0002774971840000067
Calculating the measurement quality of the information sources, and selecting one of the information sources as a preferred source as a compensation reference;
the state vector for the ith source measurement at time t1 is calculated as
Figure BDA0002774971840000068
Wherein,
Figure BDA0002774971840000069
respectively, the velocity measurement values in the directions of X, Y, Z]' denotes matrix transposition;
the state transition matrix is
Figure BDA0002774971840000071
Wherein T is the time difference between the current time and the last time;
using the state transition matrix, the predicted state matrix at the next time t2 is calculated as
Figure BDA0002774971840000072
The prediction state matrix at the time t2 is used to calculate a prediction measurement matrix as
Figure BDA0002774971840000073
Wherein, H is a measurement matrix,
Figure BDA0002774971840000074
then the measured value is predicted to be new
Figure BDA0002774971840000075
The covariance matrix of the predicted state at time t2 is calculated as
Figure BDA0002774971840000076
Wherein,
Figure BDA0002774971840000077
predicting state covariance matrix at t1, Q is covariance matrix of process noise, process noise parameters Q1, Q2 and Q3 are set as required,
Figure BDA0002774971840000078
calculate an innovation covariance matrix of
Figure BDA0002774971840000079
Wherein,
Figure BDA00027749718400000710
to measure the noise matrix, DrX，DrY，DrZStandard deviation at time t2
Figure BDA00027749718400000711
A normalized distance function is calculated that is,
Figure BDA0002774971840000081
thus, the ith source measurement quality at time t2 is obtained
Figure BDA0002774971840000082
Wherein, alpha is a history weight factor,
Figure BDA0002774971840000083
measuring quality for the ith source at time t 1;
in one specific example, α is 0.5.
Information source measurement quality
Figure BDA0002774971840000084
The smaller the better the quality, the better the preferred source is selected from the M sources.
Carrying out coordinate conversion on the measurement values of the other information sources according to the compensation reference;
suppose that the nth information source isThe preferred source, the ith information source, measures the value position vector at time t1
Figure BDA0002774971840000085
After conversion to the north-Tiandong coordinate system, it is recorded as
Figure BDA0002774971840000086
Figure BDA0002774971840000087
Wherein,
Figure BDA0002774971840000088
is the measured component of the ith information source in CGCS-2000 series.
Figure BDA0002774971840000089
Is the position vector of the nth information source, EGIs a transformation matrix from GCS2000 system to North heaven coordinate system,
Figure BDA00027749718400000810
λ、
Figure BDA00027749718400000811
respectively, the geodetic longitude and the geodetic latitude of the position of the nth information source.
Calculating the slope, azimuth and pitch angles of each information source and the compensation quantity thereof
Converting the north-Tiandong xyz coordinate system into RAE direction coordinates, and calculating the slope distance R at the time of t1iT1, azimuth AiT1 and pitch angle Ei_t1，
Figure BDA00027749718400000812
Figure BDA00027749718400000813
Figure BDA00027749718400000814
At time t1, the system error compensation value is
ΔZ(t1)＝[Ri_t1,Ai_t1,Ei_t1]-[Rn_t1,An_t1,En_t1]
As the mean value of random errors is 0 under the condition of data accumulation, the measurement value between T1 and tN is selected for statistical calculation, and the period of the 1 st information source is T
Figure BDA0002774971840000091
Where k is any one of N time points at which the high observation frequency information source has a measurement value.
Another embodiment of the present invention provides a computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements any combination of one or more computer readable media in a practical application. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present embodiment, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
As shown in fig. 3, another embodiment of the present invention provides a schematic structural diagram of a computer device. The computer device 12 shown in FIG. 3 is only an example and should not impose any limitation on the scope of use or functionality of embodiments of the present invention.
As shown in FIG. 3, computer device 12 is in the form of a general purpose computing device. The components of computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Computer device 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. Computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 3, and commonly referred to as a "hard drive"). Although not shown in FIG. 3, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
Computer device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with computer device 12, and/or with any devices (e.g., network card, modem, etc.) that enable computer device 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. Also, computer device 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via network adapter 20. As shown in FIG. 3, the network adapter 20 communicates with the other modules of the computer device 12 via the bus 18. It should be understood that although not shown in FIG. 3, other hardware and/or software modules may be used in conjunction with computer device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processor unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, implementing a system error compensation method based on automatically selecting a preferred source provided by an embodiment of the present invention.
It should be understood that the above-mentioned embodiments of the present invention are only examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention, and it will be obvious to those skilled in the art that other variations or modifications may be made on the basis of the above description, and all embodiments may not be exhaustive, and all obvious variations or modifications may be included within the scope of the present invention.

Claims (10)

1. A system error compensation method based on automatic selection of preferred sources is characterized by comprising the following steps:
acquiring a measurement value of each information source;
performing space-time calibration on the measurement value of the information source;
calculating the measurement quality of the information sources, and selecting one of the information sources as a preferred source as a compensation reference;
carrying out coordinate conversion on the measurement values of the other information sources according to the compensation reference;
and calculating the slope distance, azimuth angle and pitch angle of each information source and the compensation quantity thereof.
2. The method of claim 1, wherein obtaining a measurement value for each information source comprises:
m information sources view the same target information in the same time slot, and the command control system receives M measured value information, indicated as M measured values, from each information source at time t1
Figure FDA0002774971830000011
Wherein i (i is more than or equal to 1 and less than or equal to M) is the identification number of the information source,
Figure FDA0002774971830000012
the X-direction coordinate of the measurement from the ith source at time t1,
Figure FDA0002774971830000013
the Y-direction coordinate of the measurement from the ith source at time t1,
Figure FDA0002774971830000014
the Z-direction coordinate of the measurement from the ith source at time t 1.
3. The method of claim 2, wherein the spatio-temporal calibration is performed for each source based on an ith source measurement time point of a high observation frequency;
the ith information source quantity of the high observation frequency is the information source with the highest observation frequency in the M information sources;
if the high observation frequency information source has measurement values at N time points, the time points are t1 and t2 … tN, then the X-direction coordinate of the ith information source at the time point t1 is calculated as
Figure FDA0002774971830000015
Wherein, tk-1、tkAnd tk+1The point in time at which the ith information source has a measurement value, and tk-1≤t1≤tk≤tk+1；
Calculating the Y-direction coordinate of the ith information source at the time t1 as
Figure FDA0002774971830000016
Calculating the Z-direction coordinate of the ith information source at the time t1 as
Figure FDA0002774971830000017
4. The method of claim 3, wherein the calculating a metrology quality of the information source comprises: of information sourcesInnovation covariance matrix
Figure FDA0002774971830000018
And predicting the innovation of the measured and measured values
Figure FDA0002774971830000021
A normalized distance function is derived from the distance data,
Figure FDA0002774971830000022
thus, the ith source measurement quality at time t2 is obtained
Figure FDA0002774971830000023
Wherein, alpha is a history weight factor,
Figure FDA0002774971830000024
measuring quality for the ith source at time t 1;
information source measurement quality
Figure FDA0002774971830000025
The smaller the better the quality, the better the preferred source is selected from the M sources.
5. The method of claim 4, wherein the calculating the innovation value of the predictive measurements and the metrology values of the information sources
Figure FDA0002774971830000026
The method comprises the following steps: the state vector for the ith source measurement at time t1 is calculated as
Figure FDA0002774971830000027
Wherein,
Figure FDA0002774971830000028
respectively, the velocity measurement values in the directions of X, Y, Z]' denotes matrix transposition;
the state transition matrix is
Figure FDA0002774971830000029
Wherein T is the time difference between the current time and the last time;
using the state transition matrix, the predicted state matrix at the next time t2 is calculated as
Figure FDA00027749718300000210
The prediction state matrix at the time t2 is used to calculate a prediction measurement matrix as
Figure FDA00027749718300000211
Wherein, H is a measurement matrix,
Figure FDA00027749718300000212
then the measured value is predicted to be new
Figure FDA00027749718300000213
6. The method of claim 1, wherein the innovation covariance matrix of the information source
Figure FDA00027749718300000214
The method comprises the following steps:
the covariance matrix of the predicted state at time t2 is calculated as
Figure FDA0002774971830000031
Wherein,
Figure FDA0002774971830000032
predicting state covariance matrix at t1, Q is covariance matrix of process noise, process noise parameters Q1, Q2 and Q3 are set as required,
Figure FDA0002774971830000033
calculate an innovation covariance matrix of
Figure FDA0002774971830000034
Wherein,
Figure FDA0002774971830000035
to measure the noise matrix, DrX，DrY，DrZStandard deviation at time t2
Figure FDA0002774971830000036
7. The method of claim 6, wherein the coordinate transformation comprises:
assuming the nth source as the preferred source, the ith source measures the value position vector at time t1
Figure FDA0002774971830000037
After conversion to the north-Tiandong coordinate system, it is recorded as
Figure FDA0002774971830000038
Figure FDA0002774971830000039
Wherein,
Figure FDA00027749718300000310
is the measured component of the ith information source in CGCS-2000 system,
Figure FDA00027749718300000311
is the position vector of the nth information source, EGIs a transformation matrix from GCS2000 system to North heaven coordinate system,
Figure FDA00027749718300000312
λ、
Figure FDA00027749718300000313
respectively, the geodetic longitude and the geodetic latitude of the position of the nth information source.
8. The method of claim 7, wherein calculating the skew, azimuth and pitch compensation for each information source comprises:
converting the north-Tiandong xyz coordinate system into RAE direction coordinates, and calculating the slope distance R at the time of t1iT1, azimuth AiT1 and pitch angle Ei_t1，
Figure FDA00027749718300000314
Figure FDA0002774971830000041
Figure FDA0002774971830000042
At time t1, the system error compensation value is
ΔZ(t1)＝[Ri_t1,Ai_t1,Ei_t1]-[Rn_t1,An_t1,En_t1]
As the mean value of random errors is 0 under the condition of data accumulation, the measurement value between T1 and tN is selected for statistical calculation, and the period of the 1 st information source is T
Figure FDA0002774971830000043
Where k is any one of N time points at which the high observation frequency information source has a measurement value.
9. A computer device comprising a processor and a memory having stored thereon a computer program, characterized in that the processor, when executing the program, implements the method according to any of claims 1-8.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-8.
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