CN117930298A - Static orbit satellite positioning error correction method and device based on satellite temperature and attitude error modeling - Google Patents
Static orbit satellite positioning error correction method and device based on satellite temperature and attitude error modeling 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
- G01S19/40—Correcting position, velocity or attitude
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- 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
- G01S19/07—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers providing data for correcting measured positioning data, e.g. DGPS [differential GPS] or ionosphere corrections
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- 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
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Abstract
The invention provides a static orbit satellite positioning error correction method and device based on satellite temperature and attitude error modeling. The static orbit satellite positioning error correction method comprises the following steps: extracting earth surface template data containing land information in the coverage area of the static orbit satellite image; carrying out block matching on the static orbit satellite image and the earth surface template data to obtain a matching point information set; calculating a positioning error between the static orbit satellite image and the earth surface template data by utilizing the matching point information set; acquiring temperature difference and attitude information of the static orbit satellite image at different conditions at the imaging moment, and constructing a static orbit satellite image positioning error correction model according to the temperature difference, the attitude information and the positioning error; training and testing a static orbit satellite image positioning error correction model according to the static orbit satellite image data to obtain an optimal parameter set; and correcting the positioning error of the static orbit satellite image to be corrected based on the static orbit satellite image positioning error correction model and the optimal parameter set.
Description
Technical Field
The invention relates to the technical field of satellite positioning, in particular to a static orbit satellite positioning error correction method and device based on satellite temperature and attitude error modeling.
Background
The accurate positioning of satellite images is a key for ensuring the remote sensing satellite to realize high-precision earth observation tasks, and is one of important technical indexes representing satellite performance and service application. As shown in fig. 1, in the in-orbit operation of the satellite, the load of the platform is subjected to the influence of sun, planet and other space heat radiation sources for a long time, and the difference of the heat radiation influence on different heating surfaces of the satellite is large, so that challenges are brought to structural stability, sensor measurement accuracy and the like. For a static orbit satellite, namely a static orbit satellite, the orbit height of the static orbit satellite is tens of times that of a conventional low orbit satellite, and the tiny variation amount in satellite platform equipment can be amplified by tens of times, so that the positioning of satellite images is greatly unstable. Therefore, spatial heat radiation is an important factor affecting the positioning accuracy of the static orbit satellites.
Analysis of the optical satellite positioning principle proves that the main factors influencing the positioning accuracy comprise multiple aspects such as orbit determination accuracy, attitude measurement accuracy, stability accuracy (thermal deformation) of azimuth elements in a structure and a camera, time synchronization accuracy, ground calibration accuracy and the like, the error generation mechanism is complex, the error sources are multiple and the decoupling is difficult, and the traditional method is difficult to establish a change rule model of the satellite image positioning accuracy. Previous studies have shown that time synchronization accuracy has relatively little effect, while other factors have a great effect on positioning accuracy, especially attitude measurement and structural stability due to spatial thermal environment changes. Currently, most of the research focused on correcting the positioning error of the satellite images by means of in-orbit calibration. However, as the orbit period of the geostationary satellite is long, the cold and hot alternation is severe, the platform geometry structure and the material composition thereof are complex, the existing on-orbit calibration processing is carried out on the basis of a simplified model of the complex process, and the problem that the space temperature change of the used model is not considered enough is unavoidable; on the other hand, the calibration parameter is required to be modified and perfected at random during the satellite operation by the calibration method, the period is long, and the workload is high. The existence of these factors greatly limits the high-precision positioning of the static orbit satellite images.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides a static orbit satellite positioning error correction method and device based on satellite temperature and attitude error modeling.
The invention provides a static orbit satellite positioning error correction method based on satellite temperature and attitude error modeling, which comprises the following steps: extracting earth surface template data containing land information in the coverage area of the static orbit satellite image; carrying out block matching on the static orbit satellite image and the earth surface template data to obtain a matching point information set; calculating a positioning error between the static orbit satellite image and the earth surface template data by utilizing the matching point information set; acquiring temperature difference and attitude information of the static orbit satellite image at different conditions at the imaging moment, and constructing a static orbit satellite image positioning error correction model according to the temperature difference, the attitude information and the positioning error; training and testing a static orbit satellite image positioning error correction model according to the static orbit satellite image data to obtain an optimal parameter set; and correcting the positioning error of the static orbit satellite image to be corrected based on the static orbit satellite image positioning error correction model and the optimal parameter set.
According to an embodiment of the present invention, in a coverage area of a static orbit satellite image, extracting earth surface template data containing land information includes: extracting reference image data corresponding to the latitude and longitude range from historical reference image data according to the latitude and longitude range of the coverage area of the static orbit satellite image; acquiring sea-land segmentation template data corresponding to the longitude and latitude range according to the global sea-land segmentation template; and extracting ground surface template data of the static orbit satellite image by utilizing sea-land segmentation template data.
According to an embodiment of the present invention, after extracting the earth surface template data containing land information in the coverage area of the geostationary satellite image, the geostationary satellite positioning error correction method further comprises: calculating the ratio of the overlapping area of the earth surface template data and the static orbit satellite image, and determining the effectiveness of the earth surface template data by comparing the ratio with a preset value.
According to the embodiment of the invention, the magnitude of the preset value is 0.25, and when the ratio is greater than or equal to 0.25, the surface template data is valid.
According to an embodiment of the present invention, block matching is performed on a static orbit satellite image and ground surface template data, and a matching point information set is obtained, including: resampling the earth surface template data according to the ground sampling interval of the static orbit satellite image to obtain resampled earth surface template data; matching the block-processed static orbit satellite image with resampled earth surface template data by adopting a normalized cross-correlation algorithm to obtain an image space matching point coordinate pair between the static orbit satellite image and the earth surface template data; and converting the image space matching point coordinate pair into an object space matching point coordinate pair according to the affine transformation six-parameter model to obtain a matching point information set.
According to the embodiment of the invention, temperature difference and attitude information of the static orbit satellite image under different conditions at the imaging moment are obtained, and a static orbit satellite image positioning error correction model is constructed according to the temperature difference, the attitude information and the positioning error, and the method comprises the following steps: acquiring a temperature difference variation set of the static orbit satellite image at different temperature measuring points at the imaging moment; and constructing a static orbit satellite image positioning error correction model based on satellite temperature and attitude error modeling according to the three-axis attitude angle at the imaging moment, the temperature difference change quantity sets at different temperature measuring points and the positioning error between the static orbit satellite image and the ground surface template data.
According to the embodiment of the invention, a static orbit satellite image positioning error correction model is constructed based on a BP neural network architecture.
According to the embodiment of the invention, according to the static orbit satellite image data, a static orbit satellite image positioning error correction model is trained and tested to obtain an optimal parameter set, and the method comprises the following steps: dividing static orbit satellite image data into a training set and a testing set according to a proportion; parameter training is carried out on the static orbit satellite image positioning error correction model through a training set, and result testing is carried out on the static orbit satellite image positioning error correction model through a testing set; and obtaining an optimal parameter set by optimizing an objective function based on the training set and the test set.
According to the embodiment of the invention, effective earth surface template data does not exist in the coverage range of the static orbit satellite image to be corrected; based on the static orbit satellite image positioning error correction model and the optimal parameter set, correcting the positioning error of the static orbit satellite image to be corrected, comprising: acquiring imaging time, three-axis attitude angle and temperature difference variation sets under different temperature measuring points of a static orbit satellite image to be corrected to form input parameters; inputting the input parameters into a static orbit satellite image positioning error correction model, and obtaining an output positioning error result by means of an optimal parameter set; and updating the positioning model parameters of the static orbit satellite image to be corrected according to the output positioning error result to obtain the static orbit satellite image subjected to positioning error correction.
Another aspect of the present invention provides a static orbit satellite positioning error correction device based on satellite temperature and attitude error modeling, comprising: the data extraction module is used for extracting earth surface template data containing land information in the coverage area of the static orbit satellite image; the block matching module is used for carrying out block matching on the static orbit satellite image and the earth surface template data to obtain a matching point information set; the error calculation module is used for calculating the positioning error between the static orbit satellite image and the earth surface template data by utilizing the matching point information set; the model construction module is used for acquiring temperature difference information of the static orbit satellite image under different conditions at the imaging moment and constructing a static orbit satellite image positioning error correction model according to the temperature difference information and the positioning error; the model optimization module is used for training and testing the static orbit satellite image positioning error correction model according to the static orbit satellite image data to obtain an optimal parameter set; and the error correction module corrects the positioning error of the static orbit satellite image to be corrected based on the static orbit satellite image positioning error correction model and the optimal parameter set.
According to the static orbit satellite positioning error correction method and device based on satellite temperature and attitude error modeling, when static orbit satellite image positioning error correction is carried out, the influence rule of space temperature change and attitude information at imaging time on the static orbit satellite image positioning error can be fully utilized and mined, and an error correction model of the static orbit satellite image positioning error influenced by space environment is trained and optimized, so that high-precision positioning of the static orbit satellite image is better realized.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
For a more complete understanding of the present invention, and the advantages thereof, reference is now made to the following descriptions taken in conjunction with the accompanying drawings, in which:
FIG. 1 schematically illustrates an earth orbit satellite space thermal environment effect diagram;
FIG. 2 schematically illustrates a flow chart of a method for static orbit satellite positioning error correction based on satellite temperature and attitude error modeling, in accordance with an embodiment of the present invention;
FIG. 3 schematically shows a flow chart of a data extraction process according to an embodiment of the invention;
FIG. 4 schematically illustrates a flow diagram of a block matching process according to an embodiment of the invention;
FIG. 5 schematically shows a flow chart of a model building process according to an embodiment of the invention;
FIG. 6 schematically illustrates a block diagram of a static orbit satellite image positioning error correction model based on satellite temperature and attitude error modeling, according to an embodiment of the invention;
FIG. 7 schematically illustrates a flow chart of a model optimization process according to an embodiment of the invention;
FIG. 8 schematically illustrates a flow chart of an error correction process according to an embodiment of the invention;
Fig. 9 schematically shows a block diagram of a static orbit satellite positioning error correction device based on satellite temperature and attitude error modeling according to an embodiment of the present invention.
Detailed Description
Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. It should be understood that the description is only illustrative and is not intended to limit the scope of the invention.
Fig. 2 schematically shows a flow chart of a static orbit satellite positioning error correction method based on satellite temperature and attitude error modeling according to an embodiment of the invention.
As shown in FIG. 2, the static orbit satellite positioning error correction method based on satellite temperature and attitude error modeling according to the embodiment of the invention can comprise steps S210-S260.
In step S210, earth surface template data containing land information is extracted in the coverage area of the geostationary satellite image.
In step S220, the static orbit satellite image and the earth surface template data are subjected to block matching, and a matching point information set is obtained.
In step S230, a positioning error between the satellite image and the earth surface template data is calculated using the matching point information set.
In step S240, temperature difference and attitude information of the static orbit satellite image under different conditions at the imaging moment are obtained, and a static orbit satellite image positioning error correction model is constructed according to the temperature difference, the attitude information and the positioning error.
In step S250, the static orbit satellite image positioning error correction model is trained and tested according to the static orbit satellite image data, so as to obtain an optimal parameter set.
In step S260, the positioning error of the satellite image to be corrected is corrected based on the satellite image positioning error correction model and the optimal parameter set.
Wherein, effective earth surface template data does not exist in the coverage area of the static orbit satellite image to be corrected. The manner in which the validity of the surface template data is determined will be described later.
Through the embodiment, the static orbit satellite positioning error correction method based on satellite temperature and attitude error modeling can fully mine the influence rule of space temperature environment on the static orbit satellite positioning error when the static orbit satellite image positioning error correction and lifting are carried out, update training and optimization are carried out on model parameters along with the increase of samples, and high-precision positioning of the static orbit satellite image is better realized.
Fig. 3 schematically shows a flow chart of a data extraction process according to an embodiment of the invention.
As shown in fig. 3, the step S210 may include, for example, a substep S211 to a substep S213.
In sub-step S211, reference image data corresponding to the latitude and longitude range is extracted from the historical reference image data according to the latitude and longitude range of the coverage area of the geostationary satellite image.
For example, let i=1, 2, …, N where i Jing Jing th orbital satellite image, assume that the orbital satellite image data for model training shares N viewsThe latitude and longitude range of the coverage area of (c) can be expressed as [ lon min~lonmax,latmin~latmax ], and the reference image data/>, which have the same latitude and longitude range, can be extracted from the accumulated historical reference image data。
In sub-step S212, sea-land segmentation template data corresponding to the latitude and longitude range is obtained according to the global sea-land segmentation template.
For example, the current i Jing Jing satellite image can be obtained according to the existing global sea Liu Fenge template S L Sea-land segmentation template data/>, corresponding to latitude and longitude ranges of coverage areas of (a)。
In sub-step S213, land surface template data of the static orbit satellite image is extracted by using sea-land segmentation template data.
For example, sea-land segmentation template data using ith sceneExtracting to obtain an i Jing Jing th orbit satellite image/>Surface template data/>This can be expressed as:
wherein, Representing dot product in the matrix operation. Sea Liu Fenge template S L land area may be labeled 1 and sea water area 0 to obtain surface template data containing land information.
As shown in fig. 3, after sub-step S213, a sub-step S214 may further be included.
In sub-step S214, a ratio of the overlapping area of the earth surface template data and the static orbit satellite image is calculated, and the validity of the earth surface template data is determined by comparing the ratio with a preset value.
The size of the preset value can be set to be 0.25, and when the ratio is greater than or equal to 0.25, the surface template data are valid.
For example, surface template dataAnd the i Jing Jing th orbital satellite image/>The ratio r at of the overlapping area land portions of (c) can be expressed as:
when r at is greater than or equal to 0.25, the ith Jing Jing th orbital satellite image can be considered Surface template data/>And if not, the earth surface template data of the image of the static orbit satellite is considered to be invalid, namely the offset information of the image of the static orbit satellite cannot be calculated through the earth surface template data.
Fig. 4 schematically shows a flow chart of a block matching process according to an embodiment of the invention.
As shown in fig. 4, the step S220 may include, for example, a substep S221 to a substep S223.
In sub-step S221, the earth surface template data is resampled according to the ground sampling interval of the geostationary satellite image, so as to obtain resampled earth surface template data.
For example, the surface template data is acquired based on the above step S210And the i Jing Jing th orbital satellite image/>I Jing Jing th orbital satellite image/>The width and height of the surface template data are W S,HS Is [ W R,HR ], and the ground sampling interval of the ground template data is Res S. Then for the surface template data/>Resampling to obtain resampled ground sampling intervalThe method comprises the following steps:
Resampled surface template data Is of the width, height and ground sampling interval/>And the ith Jing Jing th orbital satellite image/>Having the same parameters, i.e
In sub-step S222, a normalized cross-correlation algorithm is used to match the block-processed static orbit satellite image with the resampled earth surface template data, so as to obtain an image space matching point coordinate pair between the static orbit satellite image and the earth surface template data.
For example, the ith Jing Jing th orbit satellite imageThe earth surface is segmented, and the ith Jing Jing th orbit satellite image/>The data is divided into l image blocks with the size of [ W B,HB ], and then a normalized cross-correlation algorithm and resampled earth surface template data/>, are adoptedMatching to obtain the ith Jing Jing th orbit satellite image/>And surface template data/>And the matching point pairs are l matching point pairs, namely image space matching point coordinate pairs. For the j-th matching point, let i Jing Jing th orbital satellite image/>The image space matching point coordinate of (1) is p j(xj,yj), and the corresponding earth surface template data/>The image side matching point coordinates of (1) are/>。
In sub-step S223, the image side matching point coordinate pair is converted into the object side matching point coordinate pair according to the affine transformation six-parameter model, and a matching point information set is obtained.
For example, for the ith Jing Jing th orbital satellite imageFor example, the i Jing Jing th orbital satellite image/>, can be transformed into a six-parameter model according to affineImage-side matching point coordinates p j(xj,yj) into object-side matching point coordinates/>The following formula is shown:
wherein, Static orbit satellite image for ith scene image/>Is provided.
Similarly, according to the surface template dataCan also calculate and obtain the earth surface template data/>Corresponding geographical coordinates/>I.e.
Wherein,For the surface template data/>Is provided.
Through the conversion, jing Jing th orbit satellite image can be obtainedData/>, with the earth's surface templateThe matching point object space coordinate set P (Lon, lat) is obtained.
Next, step S230 is performed to calculate a positioning error between the satellite image and the earth surface template data by using the matching point information set.
For example, the ith Jing Jing th orbital satellite image obtained based on step S220And surface template data/>The matching point object space coordinate set P (Lon, lat) can construct the ith Jing Jing orbit satellite image/>Is shown in the following formula:
Wherein F (Lon, lat) represents the ith Jing Jing th orbital satellite image Is described.
Solving the equation to calculate the ith Jing Jing th orbit satellite imageIs of the positioning deviation of (2)。
FIG. 5 schematically shows a flow chart of a model building process according to an embodiment of the invention; fig. 6 schematically shows a block diagram of a model for correcting positioning errors of an image of a static orbit satellite based on modeling of satellite temperature and attitude errors according to an embodiment of the invention.
As shown in fig. 5, step S240 may include, for example, sub-steps S241 to S242.
In sub-step S241, a set of temperature difference variation amounts of the imaging moment of the static orbit satellite image at different temperature measurement points is acquired.
For example, based on step S210 to step S230, the positioning deviation of the static orbit satellite images acquired under different conditions under the condition of the earth surface reference template can be obtained. Assume that Q temperature measuring points are shared in the initial stage of the design of the static orbit satellite platform, and the standard working temperature of each temperature measuring point isThe temperature measurement information set of a certain imaging moment T acquired during the in-orbit operation of the static orbit satellite is as follows:
The temperature variation at each temperature measurement point at the imaging time T can be obtained as follows:
based on the above, the set of temperature change amounts Δk at a certain imaging time T acquired during the orbiting of the static satellite can be expressed as:
In sub-step S242, a model for correcting positioning errors of an image of a static orbit satellite based on modeling of satellite temperature and attitude errors is constructed according to three-axis attitude angles at imaging time, temperature difference change amount sets at different temperature measuring points and positioning errors between the image of the static orbit satellite and surface template data.
For example, for the acquired ith Jing Jing th orbital satellite imageIn other words, the three-axis attitude angle according to the imaging time T thereofAnd the change quantity set delta K i of each temperature measuring point and the calculated positioning deviation delta D i of the satellite image can be used for constructing a static orbit satellite image positioning error correction model based on satellite temperature and attitude error modeling based on a BP (Back Propagation) neural network architecture.
For example, as shown in fig. 6, the model is a structure diagram of a static orbit satellite image positioning error correction model based on a BP neural network architecture, where L represents the number of hidden layers in the model structure, and the number of model input nodes is N, that is, the number of attitude angles and satellite temperature information sets at the imaging moment of an N Jing Jing orbit satellite image; a weight parameter and a bias parameter representing a first node in the layer 1 hidden layer; /(I) Representing the i Jing Jing th orbital satellite image/>The acquired input data, which is composed of three elements of imaging time, temperature difference information and attitude angle information, can be expressed as:
y i is the positioning deviation of the static orbit satellite image obtained after model training.
For the model structure shown in fig. 6, L hidden layers are provided, and the number of nodes R of each hidden layer can be determined as follows according to the Kolmogorov principle:
R=2·N+1
For the above model structure, the output of the nth node of the L-th hidden layer By the output of layer L-1/>Weight parameter of layer L/>Calculated together with the bias parameters, i.e
Wherein μ (x) is a ReLU activation function, which can be described as
For the network model, the connection weight can be adjusted by adopting an error back propagation method, and the objective function is as follows:
FIG. 7 schematically shows a flow chart of a model optimization process according to an embodiment of the invention.
As shown in fig. 7, the step S250 may include, for example, a substep S251 to a substep S253.
In sub-step S251, the static orbital satellite image data is proportionally divided into a training set and a test set.
For example, N sets of acquired static orbit satellite image data are commonly acquired, and the N sets of data may be divided into a training set S T and a test set S V according to a ratio of 8:2. Wherein the training set S T comprisesGroup input/output data, test set S V contains/>Group input/output data, and has
For the ith Jing Jing th orbit satellite imageThe input/output of the training/testing data is defined as
In sub-step S252, parameter training is performed on the satellite positioning error correction model by using the training set, and result testing is performed on the satellite positioning error correction model by using the testing set.
For example, it willThe training data set is used as a training set S T for training the static orbit satellite image positioning error correction model constructed in the step S240, and the model prediction result is tested through a testing set S V.
In sub-step S253, an optimal parameter set is obtained by optimizing the objective function based on the training set and the test set.
For example, based on the training set S T and the test set S V, an optimal parameter set C is obtained by optimizing the objective function G, as shown in the following formula:
fig. 8 schematically shows a flow chart of an error correction procedure according to an embodiment of the invention.
As shown in fig. 8, the step S260 may include, for example, sub-steps S261 to S263.
In sub-step S261, an imaging time, a three-axis attitude angle, and a temperature difference variation set at different temperature measurement points of the static orbit satellite image to be corrected are obtained to form an input parameter.
For example, no valid earth surface template data exists in the coverage area of the newly acquired p Jing Jing th orbit satellite image, i.e. the p Jing Jing th orbit satellite image is the static orbit satellite image to be corrected. Imaging time T p and three-axis attitude angle of the p-th scene image can be obtainedTemperature change amount set of each temperature measuring point/>Together, the input parameters X p are composed as follows:
In sub-step S262, the input parameters are input into the geostationary satellite image positioning error correction model, and the output positioning error result is obtained by means of the optimal parameter set.
For example, input parameter X p is input into the static orbit satellite image positioning error correction model constructed in step S250, and the output positioning error result is obtained by training the obtained optimal parameter set C。
In sub-step S263, according to the output positioning error result, the positioning model parameters of the satellite image to be corrected are updated to obtain the satellite image after the positioning error correction.
For example, the positioning model parameters of the p Jing Jing th orbit satellite image areBased on the obtained positioning error resultThe positioning model parameters of the p Jing Jing th orbit satellite image are corrected, and the formula is as follows:
And updating the positioning model parameters of the p Jing Jing th orbit satellite image to finish the positioning error correction of the p Jing Jing th orbit satellite image.
Through the above processing, the static orbit satellite image with the positioning error corrected can be obtained.
Through the embodiment, the static orbit satellite image positioning error correction method based on satellite temperature and attitude error modeling provided by the invention can fully utilize and mine the influence rule of the space temperature change and the attitude information at the imaging moment on the static orbit satellite image positioning error, and train and optimize the error correction model of the static orbit satellite image positioning error influenced by the space environment, thereby better realizing the high-precision positioning of the static orbit satellite image.
Based on the static orbit satellite positioning error correction method based on satellite temperature and attitude error modeling, the invention also provides a static orbit satellite positioning error correction device based on satellite temperature and attitude error modeling. The device will be described in detail below in connection with fig. 9.
Fig. 9 schematically shows a block diagram of a static orbit satellite positioning error correction device based on satellite temperature and attitude error modeling according to an embodiment of the present invention.
As shown in fig. 9, the static orbit satellite positioning error correction apparatus 900 based on satellite temperature and attitude error modeling may include a data extraction module 910, a block matching module 920, an error calculation module 930, a model construction module 940, a model optimization module 950, and an error correction module 960.
The data extraction module 910 is configured to extract earth surface template data containing land information in a coverage area of the geostationary satellite image.
The block matching module 920 is configured to perform block matching on the satellite image and the earth surface template data, and obtain a matching point information set.
The error calculation module 930 calculates the positioning error between the satellite image and the earth surface template data by using the matching point information set.
The model construction module 940 acquires temperature difference information of the static orbit satellite image at different imaging moments, and constructs a static orbit satellite image positioning error correction model according to the temperature difference information and the positioning error.
The model optimization module 950 trains and tests the positioning error correction model of the static orbit satellite image according to the static orbit satellite image data to obtain an optimal parameter set.
The error correction module 960 corrects the positioning error of the satellite image to be corrected based on the positioning error correction model and the optimal parameter set.
It should be noted that, the apparatus portion in the embodiment of the present invention corresponds to the method portion in the embodiment of the present invention, and the description of the apparatus portion specifically refers to the method portion and is not described herein again.
Any number of the modules, sub-modules, units, sub-units, or at least part of the functionality of any number of the sub-units according to embodiments of the invention may be implemented in one module. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present invention may be implemented as a split into multiple modules. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the invention may be implemented at least in part as hardware circuitry, such as a Field Programmable Gate Array (FPGA), programmable Logic Array (PLA), system-on-chip, system-on-substrate, system-on-package, application Specific Integrated Circuit (ASIC), or in hardware or firmware in any other reasonable manner of integrating or packaging circuitry, or in any one of, or in any suitable combination of, software, hardware, and firmware. Or one or more of the modules, sub-modules, units, sub-units according to embodiments of the invention may be at least partly implemented as computer program modules which, when run, may perform the corresponding functions.
For example, any number of the data extraction module 910, the block matching module 920, the error calculation module 930, the model construction module 940, the model optimization module 950, and the error correction module 960 may be combined in one module/unit/subunit, or any one of the modules/units/subunits may be split into a plurality of modules/units/subunits. Or at least some of the functionality of one or more of these modules/units/sub-units may be combined with at least some of the functionality of other modules/units/sub-units and implemented in one module/unit/sub-unit. According to embodiments of the invention, at least one of the data extraction module 910, the block matching module 920, the error calculation module 930, the model construction module 940, the model optimization module 950, and the error correction module 960 may be implemented at least in part as hardware circuitry, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system-on-chip, a system-on-substrate, a system-on-package, an Application Specific Integrated Circuit (ASIC), or as hardware or firmware in any other reasonable way of integrating or packaging the circuitry, or as any one of or a suitable combination of any of the three. Or at least one of the data extraction module 910, the block matching module 920, the error calculation module 930, the model construction module 940, the model optimization module 950, and the error correction module 960 may be at least partially implemented as computer program modules, which, when executed, may perform the corresponding functions.
The embodiments of the present invention are described above. These examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Although the embodiments are described above separately, this does not mean that the measures in the embodiments cannot be used advantageously in combination. Various alternatives and modifications can be made by those skilled in the art without departing from the scope of the invention, and such alternatives and modifications are intended to fall within the scope of the invention.
Claims (10)
1. A static orbit satellite positioning error correction method based on satellite temperature and attitude error modeling is characterized by comprising the following steps:
Extracting earth surface template data containing land information in the coverage area of the static orbit satellite image;
Carrying out block matching on the static orbit satellite image and the earth surface template data to obtain a matching point information set;
calculating a positioning error between the static orbit satellite image and the earth surface template data by using the matching point information set;
acquiring temperature difference and attitude information of the static orbit satellite image under different conditions at the imaging moment, and constructing a static orbit satellite image positioning error correction model according to the temperature difference, the attitude information and the positioning error;
training and testing the static orbit satellite image positioning error correction model according to the static orbit satellite image data to obtain an optimal parameter set;
and correcting the positioning error of the static orbit satellite image to be corrected based on the static orbit satellite image positioning error correction model and the optimal parameter set.
2. The method for correcting positioning error of a geostationary satellite of claim 1, wherein said extracting earth template data comprising terrestrial information in a coverage area of the geostationary satellite image comprises:
extracting reference image data corresponding to the longitude and latitude range from historical reference image data according to the longitude and latitude range of the coverage area of the static orbit satellite image;
Obtaining sea-land segmentation template data corresponding to the longitude and latitude range according to a global sea-land segmentation template;
And extracting the earth surface template data of the static orbit satellite image by using the sea-land segmentation template data.
3. The method for correcting positioning errors of a static orbit satellite according to claim 2, wherein after extracting the earth template data containing land information in the coverage area of the static orbit satellite image, the method for correcting positioning errors of a static orbit satellite further comprises:
and calculating the ratio of the overlapping area of the earth surface template data and the static orbit satellite image, and determining the effectiveness of the earth surface template data by comparing the ratio with a preset value.
4. A static orbit satellite positioning error correction method according to claim 3, wherein the magnitude of the preset value is 0.25, and the earth surface template data is valid when the ratio is greater than or equal to 0.25.
5. The method for correcting positioning errors of a static orbit satellite according to claim 1, wherein the block matching the static orbit satellite image with the earth surface template data to obtain the matching point information set comprises:
resampling the earth surface template data according to the ground sampling interval of the static orbit satellite image to obtain resampled earth surface template data;
Matching the block-processed static orbit satellite image with resampled earth surface template data by adopting a normalized cross-correlation algorithm to obtain an image space matching point coordinate pair between the static orbit satellite image and the earth surface template data;
And converting the image space matching point coordinate pair into an object space matching point coordinate pair according to an affine transformation six-parameter model to obtain the matching point information set.
6. The method for correcting positioning errors of a geostationary satellite according to claim 1, wherein said obtaining temperature difference and attitude information of the imaging moment of the geostationary satellite image under different conditions, and constructing a model for correcting positioning errors of the geostationary satellite image according to the temperature difference, the attitude information and the positioning errors, comprises:
acquiring a temperature difference variation set of the static orbit satellite image at different temperature measuring points at the imaging moment;
and constructing a static orbit satellite image positioning error correction model based on satellite temperature and attitude error modeling according to the three-axis attitude angle at the imaging moment, the temperature difference variable quantity sets at different temperature measuring points and the positioning error between the static orbit satellite image and the earth surface template data.
7. The method for correcting positioning errors of a static orbit satellite according to claim 6, wherein the static orbit satellite image positioning error correction model is constructed based on a BP neural network architecture.
8. The method for correcting positioning errors of a geostationary satellite of claim 1, wherein training and testing the positioning error correction model of the geostationary satellite based on the geostationary satellite image data to obtain an optimal parameter set comprises:
Dividing the static orbit satellite image data into a training set and a testing set according to a proportion;
performing parameter training on the static orbit satellite image positioning error correction model through the training set, and performing result testing on the static orbit satellite image positioning error correction model through the testing set;
and obtaining the optimal parameter set by optimizing an objective function based on the training set and the testing set.
9. The method for correcting positioning errors of a static orbit satellite according to claim 1, wherein effective earth surface template data does not exist in a coverage area of the static orbit satellite image to be corrected;
the correcting the positioning error of the static orbit satellite image to be corrected based on the static orbit satellite image positioning error correction model and the optimal parameter set comprises the following steps:
Acquiring imaging time, three-axis attitude angle and temperature difference variation sets under different temperature measuring points of a static orbit satellite image to be corrected to form input parameters;
inputting the input parameters into the static orbit satellite image positioning error correction model, and obtaining an output positioning error result by means of the optimal parameter set;
And updating the positioning model parameters of the static orbit satellite image to be corrected according to the output positioning error result to obtain the static orbit satellite image with the corrected positioning error.
10. The utility model provides a static orbit satellite positioning error correction device based on satellite temperature and attitude error modeling which characterized in that includes:
The data extraction module is used for extracting earth surface template data containing land information in the coverage area of the static orbit satellite image;
The block matching module is used for carrying out block matching on the static orbit satellite image and the earth surface template data to obtain a matching point information set;
the error calculation module is used for calculating the positioning error between the static orbit satellite image and the earth surface template data by utilizing the matching point information set;
The model construction module is used for acquiring temperature difference information of the static orbit satellite image at different imaging moments and constructing a static orbit satellite image positioning error correction model according to the temperature difference information and the positioning error;
the model optimization module is used for training and testing the static orbit satellite image positioning error correction model according to the static orbit satellite image data to obtain an optimal parameter set;
and the error correction module corrects the positioning error of the static orbit satellite image to be corrected based on the static orbit satellite image positioning error correction model and the optimal parameter set.
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