CN114972875A - Multi-frame combination-based non-refracted star and refracted star classification method and device - Google Patents
Multi-frame combination-based non-refracted star and refracted star classification method and device Download PDFInfo
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Abstract
The invention discloses a multiframe association-based classification method and device for non-refracted stars and refracted stars. The method comprises the following steps: performing inter-frame star point matching according to inter-frame star point displacement, and calculating an inter-frame attitude matrix; constructing multi-frame star point projection characteristics according to the interframe attitude matrix; and constructing a refracted star classifier by using different projection characteristic properties between the refracted star and the non-refracted star, and obtaining a classification result. The invention only uses the multi-frame star point position information to classify the non-refraction star and the refraction star, has high classification accuracy, does not need to carry out star map identification, and does not need any prior pose information.
Description
Technical Field
The invention relates to the technical field of refraction star navigation sensors, in particular to a multiframe association-based non-refraction star and refraction star classification method and device.
Background
The single view field refraction star astronomical navigation sensor is a high-precision position and attitude measuring instrument. The instrument uses a single sensor to observe the non-refraction star and the refraction star simultaneously, and achieves measurement and calculation of the attitude and the position. The method has complete autonomy, does not accumulate pose strategy errors along with time, has high navigation precision, and is a navigation scheme with great potential at present. The classification and identification of the non-refraction stars and the refraction stars which are observed simultaneously in the visual field are the precondition for realizing the high-precision navigation method. In recent years, the refracted star navigation technology has been developed to some extent, but most of research focuses on the method research for calculating the position of a carrier by using the measured refracted star angle, and neglects the importance of classifying non-refracted stars and refracted stars which appear simultaneously in a field of view. Summarizing the existing methods for classifying non-refracted stars and refracted stars, the following methods are mainly used. Qian et al in their article (QIAN H M, SUN L, CAI J N, et al. A starlight reflection scheme with single star sensor used in auto-nomous satellite navigation system [ J ]. Acta advanced 2014, 96:45-52.) consider that the star map recognition algorithm cannot recognize refracted stars whose positions are shifted, and therefore the star points that are not recognized by the star map recognition algorithm are refracted stars. In fact, small angle refracted stars can be identified by most star map identification algorithms, since star map identification can tolerate a certain degree of position error. This method therefore introduces additional errors into the pose calculation and also affects the angle of refraction measurement. Ningxialin et al, in their article (NING X, SUN X, FANG J, et al, Satellite stellate ladder reconstruction using star pixel coordinates [ J ]. Navigation, 2019, 66(1): 129) 138.) define that the visual axis of the simulation platform observer always points in the direction of orbital motion, which directly identifies stars appearing in the upper half of the image as non-refracting stars and stars as refracting stars. However, this identification method is also not feasible because the boresight orientation does not always follow the expectation due to the presence of external environmental disturbances when the satellite is actually operating in orbit. The existing non-refraction star and refraction star classification methods can be carried out only by depending on the pose prior information of a navigation sensor and matching with a star map identification method of a non-refraction star, and the methods cannot be operated normally when the problems of prior information loss of the pose or failure of a star map identification algorithm and the like occur in practical application.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The invention provides a multi-frame combination-based classification method and device for non-refracted stars and refracted stars, which at least solve the technical problem of classifying non-refracted stars and refracted stars which simultaneously appear in a view field of a single-view field refracted star astronomical navigation sensor when the navigation sensor cannot obtain pose prior information and a star map identification result.
According to an aspect of the embodiments of the present invention, there is provided a method for classifying non-refracted stars and refracted stars based on multi-frame association, including: performing inter-frame star point matching according to inter-frame star point displacement, and calculating an inter-frame attitude matrix; constructing multi-frame star point projection characteristics according to the interframe attitude matrix; and constructing a refracted star classifier by using different projection characteristic properties between the refracted star and the non-refracted star, and obtaining a classification result.
Further, the step S100 includes:
step S110, obtainThe star vectors of the camera coordinate system of all the star points in the frame image form a setIn the formulaThe vector of the star vector is used as the vector of the star,the number of the symbols is an asterisk,is as followsThe total number of stars in the frame image; get the firstIn a frame imageThe star vectors of the camera coordinate system of all the star points form a setIn the formulaThe vector of the star vector is used as the vector of the star,the number of the star marks is the same as the star number,is as followsThe total number of stars in the frame image;
step S120, according to the second stepFrame and secondFinding all matched star points by using the star vectors in the frame;
and S130, calculating an interframe attitude matrix according to the matched star points.
Further, the step S200 includes:
respectively calculating to obtain the second one according to the inter-frame star point matching and the inter-frame attitude matrix calculation methodFrame and preambleAn inter-frame attitude matrix between frames;
through the calculated secondFrame and preambleThe posture matrix between frames projects the star point position at any time to the current timeTime of day;
calculating the coordinates of the projection star vector under an image coordinate system according to a pinhole camera model to obtain two-dimensional coordinates of projection star points, and constructing star point projection characteristics。
Further, the step S300 includes:
according to the linear regression matrixCalculating the eigenvector corresponding to the minimum eigenvalue, and recording as,Is a column vector of 2x1,is a column vectorAnd calculating its vertical vector from the vector;
According to the vectorAnd vectorSeparately calculating the linear regression residualAndthe calculation formula isAndand calculating the index of refraction star;
According to the index of said refraction starClassifying the star points into two categories and definingThe star point of (A) is a non-refracting star, definingThe star point of (A) is a refraction star, whereinIs a classification threshold.
According to another aspect of the embodiments of the present invention, there is provided a multi-frame combination-based classification apparatus for non-refracted stars and refracted stars, including:
the matching module is used for matching star points among multiple frames and calculating an interframe attitude matrix;
the characteristic module is used for constructing star point projection characteristics according to the matched star point and the inter-frame attitude matrix;
and the classification module is used for classifying the non-refraction stars and the refraction stars according to the star point projection characteristics.
Further, the matching module comprises:
an acquisition unit for acquiringThe star vectors of the camera coordinate system of all the star points in the frame image form a setIn the formulaThe vector of the star vector is used as the vector of the star,the number of the star marks is the same as the star number,is as followsThe total number of stars in the frame image; get the firstThe star vectors of the camera coordinate system of all the star points in the frame image form a setIn the formulaThe vector of the star vector is used as the vector of the star,the number of the star marks is the same as the star number,is as followsThe total number of stars in the frame image;
a matching unit for searching all matching star points according to the star vectors of the two frames,
and the computing unit is used for computing the interframe attitude matrix according to the matched star points.
Further, the feature module includes:
the projection unit is used for calculating the coordinates of the projection star vector under the image coordinate system according to the pinhole camera model;
a construction unit for constructing star point projection characteristics according to the projection star point two-dimensional coordinates。
Further, the classification module comprises:
a regression unit for projecting the characteristics according to the star pointsCalculating a linear regression matrixIn the formulaAndare respectively asAndaverage value of (d); and also for use in accordance with the linear regression matrixCalculating the eigenvector corresponding to the minimum eigenvalue, and recording asAnd calculating its vertical vector from the vector;
A decision unit for determining a vector based on the vectorAnd vectorSeparately calculating linear regression residualsAndthe calculation formula isAndand calculate the discountIndex of shooting star(ii) a And also for determining the star index of refractionClassifying the star points into two categories and definingThe star point of (A) is a non-refracting star, definedThe star point of (A) is a refraction star, whereinIs a classification threshold.
According to another aspect of the embodiments of the present invention, there is also provided a non-volatile storage medium including a stored program, wherein the program when running controls an apparatus in which the non-volatile storage medium is located to perform a multi-frame association-based non-refracted star and refracted star classification method.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including a processor and a memory; the memory has stored therein computer readable instructions for execution by the processor, wherein the computer readable instructions when executed perform a multi-frame joint based non-refracted star and refracted star classification method.
The technical scheme of the invention can realize the following beneficial technical effects:
in the embodiment of the invention, inter-frame star point matching is carried out according to inter-frame star point displacement, and an inter-frame attitude matrix is calculated; constructing multi-frame star point projection characteristics according to the interframe attitude matrix; the invention only uses the multi-frame star point position information to classify the non-refraction star and the refraction star, has high classification accuracy, does not need to carry out star map identification, and does not need any prior pose information. When the satellite in orbit loses prior information of the attitude and the position, the method can still correctly classify the non-refraction star and the refraction star in the star map, ensure the capability of the satellite in orbit to process emergency and improve the safety of the satellite in orbit.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a simulated star map for a plurality of frames according to an embodiment of the present invention;
FIG. 2 is a diagram of multi-frame star point projection features and classification results according to an embodiment of the present invention;
FIG. 3 is a flowchart of a method for classifying non-refracted stars and refracted stars based on multi-frame association according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to an embodiment of the present invention, there is provided an embodiment of a method for classifying non-refracted stars and refracted stars based on a multi-frame association, it should be noted that the steps shown in the flowchart of the drawings may be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that shown.
Examples
Fig. 3 is a flowchart of a method for classifying non-refracted stars and refracted stars based on multi-frame association according to an embodiment of the present invention, as shown in fig. 3, the method includes the following steps:
s100, performing inter-frame star point matching according to inter-frame star point displacement, and calculating an inter-frame attitude matrix;
specifically, the inter-frame star point matching according to the inter-frame star point displacement and calculating the inter-frame attitude matrix includes the following steps:
step S110, obtainThe star vectors of the camera coordinate system of all the star points in the frame image form a setIn the formulaThe vector of the star vector is used as the vector of the star,the number of the star marks is the same as the star number,is as followsThe total number of stars in the frame image; get the firstThe star vectors of the camera coordinate system of all the star points in the frame image form a setIn the formulaThe vector of the star vector is used as the vector of the star,the number of the star marks is the same as the star number,is as followsThe total number of stars in the frame image;
step S120, according to the second stepFrame and secondFinding all matched star points by using the star vectors in the frame;
specifically, when it comes toFirst of frameIndividual star vectorAnd a firstFirst of frameIndividual star vectorSatisfy the requirement ofAnd is andand is andthen it is considered as the firstFirst of frameIndividual star vectorAnd a firstFirst of frameIndividual star vectorFor matching stars, operators in the equationThe included angle between the two vectors is calculated,angular threshold, operator for star point matchingWhich represents a set subtraction of the sets,is a set of camera coordinate system star vectors for all the star points in the t-k frame images,is the set of camera coordinate system star vectors for all the star points in the t-th frame image.
For arbitrary two vectorsAndwith an included angle ofFor any two setsAndthe difference set thereof satisfiesIn the formulaRepresenting elements in an arbitrary collection; x, y generally refer to any two vectors used to describe the operatorSet X, Y broadly refers to any two sets used to describe an operator。
And S130, calculating an interframe attitude matrix according to the matched star points.
Specifically, it is assumed that after the star point matching between frames, the second stepFrame and the firstBetween frames haveThe same star point is recordedFirst of frameThe individual star points are exactly respectively connected withFirst of frameThe matching of the individual star points can be calculated according to the matching star points through an attitude calculation algorithmFrame and the secondInter-frame attitude matrix between frames, denotedSatisfy the following requirements。
S200, constructing multi-frame star point projection characteristics according to the inter-frame attitude matrix;
specifically, the construction of the multi-frame star point projection characteristics according to the interframe attitude matrix comprises the following steps:
respectively calculating to obtain the second frame according to the inter-frame star point matching and the inter-frame attitude matrix calculation method in the step S100Frame and preambleThe inter-frame attitude matrix between frames is respectively recorded asIn the formulaThe total frame number used when calculating the multi-frame star point projection characteristics in the step is set at the same timeFrame to firstAggregation between framesAll star points in the frame with corresponding matching haveAm et al (1)The individual star point isThe star vector in the frame isObtained by said calculationFrame and preambleThe posture matrix between frames can project the star point position at any time to the current timeTime, star vectorThe projected star vector isThe projection formula isIn the formulaThe number of the star marks is the same as the star number,is a frame number in the formulaWhen it is used, orderIn the formulaIs an identity matrix; calculating the coordinates of the projection star vector under the image coordinate system according to a pinhole camera model, and recordingThe corresponding two-dimensional vector of the image coordinate system isIn the formulaAndtwo coordinate values of the projected star point image coordinate are respectively; constructing star point projection characteristics according to the projection star point two-dimensional coordinates。
And step S300, constructing a refracted star classifier by using different projection characteristic properties between the refracted star and the non-refracted star, and obtaining a classification result.
Specifically, the construction of the refracted star classifier by using different projection characteristic properties between the refracted star and the non-refracted star and the obtaining of the classification result include the following steps:
according to the star point projection characteristics in the step S200Calculating a linear regression matrixIn the formulaAndare respectively asAndaverage value of (d); according to the linear regression matrixCalculating the eigenvector corresponding to the minimum eigenvalue, and recording as,Is a column vector of 2x1,is a column vectorAnd calculating its vertical vector from the vector(ii) a According to the vectorAnd vectorSeparately calculating linear regression residualsAndthe calculation formula isAndand calculating the index of refraction star(ii) a According to the index of said refraction starClassifying the star points into two categories and definingThe star point of (A) is a non-refracting star, definedThe star point of (A) is a refraction star, whereinIs a classification threshold.
The following describes the specific implementation process of the classification method of the present invention in detail by using specific examples:
1. and performing inter-frame star point matching according to the inter-frame star point displacement, and calculating an inter-frame attitude matrix.
Definition ofFrame (currently isTime of day) ofThe camera coordinate system star vector of each star point is as follows:
in the formulaIs as followsThe set of camera coordinate system star vectors for all the star points in the frame,is as followsIn the frame ofThe individual camera coordinate system star vector.
in the formulaIs as followsThe set of camera coordinate system star vectors for all the star points in the frame,is as followsIn the frame ofThe individual camera coordinate system star vector.
When it comes toFirst of frameIndividual star vectorAnd a firstFirst of frameIndividual star vectorSatisfies the following conditions:
and:
and:
then it is considered asFirst of frameIndividual star vectorAnd a firstFirst of frameIndividual star vectorAre the same star point. Operator in formulaThe included angle between the two vectors is calculated. In particular, for any two vectorsAndand the included angle satisfies:
in the formulaAngular threshold, operator for star point matchingRepresenting aggregate subtraction. In particular, for any two setsAndand the difference set thereof satisfies:
Finding out the star point matching between framesFrame and the secondBetween frames haveThe same star point. And do not markFirst of frameThe individual star points are exactly respectively connected withFirst of frameAnd matching the individual star points. Then the first one can be calculated by the attitude calculation algorithm based on the above-mentioned matching starsFrame and the secondInter-frame attitude matrix between frames, denotedAnd satisfies the following conditions:
2. and constructing multi-frame star point projection characteristics according to the interframe attitude matrix.
According to the above calculation, the first and secondFrame and preambleThe inter-frame attitude matrix between frames is respectively recorded as. WhereinAnd calculating the total frame number used when the multi-frame star point characteristics are calculated for the step. At the same time, the above-mentioned slave stage is not providedFrame to firstAggregation between framesAll star points in the frame with corresponding matching haveAnd (4) granulating. And do not markThe individual star point is atThe star vector in the frame is. By the aid of the inter-frame projection matrix, the star point position at any moment can be projected to the current timeTime, star vectorThe projected star vector is. The projection formula is:
wherein whenWhen the temperature of the water is higher than the set temperature,. WhereinIs an identity matrix.
At the moment, the coordinates of the projection star vector under the image coordinate system are calculated according to the pinhole camera model, and the coordinates are recordedThe corresponding two-dimensional vector of the image coordinate system is。
The multi-frame projection star vector of each star point can form the projection characteristics of the star point。
3. And constructing a refracted star classifier by using different projection characteristic properties between the refracted star and the non-refracted star, and obtaining a classification result.
Since the non-refracted star vector between frames is only rotated by the different poses between frames, the projected star vectors of their different frames should coincide. And the refraction star vector is influenced by atmospheric refraction besides different postures among the multiframes. Due to the movement of the carrier, the observation heights of the refracted rays of different frames are changed, and then the projected star vectors of different frames are obtained. In a short time, it can be considered that the projected star vector of the refracted star is rotated about a fixed axis. Therefore, the star point projection characteristics of the non-refracting stars should be coincident scatter points, and the star point projection characteristics of the refracting stars should be scatter points distributed along a straight line.
Considering the single star positioning error and the attitude estimation error of the navigation sensor, the actual star point projection characteristic of the non-refraction star is scattered points randomly distributed near the true star point position, and the star point projection characteristic of the refraction star is scattered points randomly distributed near the straight line of the actual refraction star point projection track.
When the classifier is constructed, firstly, the projection characteristics of certain star points to be classified are projectedA linear fit is performed. The scatter coordinates in the projection features are not made to beFrom it to the fitted line, it is noted:
whereinAre the fitted estimated points. And the residue defining the fitted line is the scatter-to-line distance, then the sum of the squared errors can be calculated as:
While,Andare respectively asAndaverage value of (a).Is solved asAfter the solution of the eigenvector corresponding to the minimum eigenvalue is substituted into the above formula, the residual error can be obtained. At the same time willAfter bringing into the above formula, can obtain. The index of the star point projection characteristic satisfying the refraction rule can be defined as。
By calculating the index of refraction star corresponding to each starAnd are classified as follows:
The method is verified through simulation experiments. The generated multi-frame simulated star map simultaneously containing the non-refraction star and the refraction star is shown in fig. 1, wherein a dot in the map is a real non-refraction star point, a cross point is a real refraction star point, the star point type is only marked in the map as an illustration, and only position information of the star point is used when star point classification is carried out. By using the method of the invention to track the star points, the constructed star point projection characteristics are shown in fig. 2, and the number on each sub-graph is the refractive star index corresponding to each star. It can be seen that the star point projection of the non-refracted star is characterized by a scatter point scattered randomly at the center, and the index of the refracted star is notAnd the star point projection characteristics of the refraction star are distributed along a straight line, and the index of the refraction star is relatively large. By setting classification threshold valuesAccurate classification of non-refracted stars and refracted stars in the map can be achieved.
According to another aspect of the embodiments of the present invention, there is also provided a multi-frame combination-based classification apparatus for non-refracted stars and refracted stars, including: the matching module is used for matching star points among multiple frames and calculating an interframe attitude matrix; the characteristic module is used for constructing star point projection characteristics according to the matched star point and the inter-frame attitude matrix; and the classification module is used for classifying the non-refraction stars and the refraction stars according to the star point projection characteristics.
Optionally, the matching module includes: an acquisition unit for acquiringThe star vectors of the camera coordinate system of all the star points in the frame image form a setIn the formulaThe vector of the star vector is used as the vector of the star,the number of the star marks is the same as the star number,is as followsThe total number of stars in the frame image; and the matching unit is used for searching all matched star points according to the star vectors of the two frames. When it comes toFirst of frameIndividual star vectorAnd a firstFirst of frameIndividual star vectorSatisfy the requirement ofAnd is andand is made ofThen it is considered as the firstFirst of frameIndividual star vectorAnd a first step ofFirst of frameIndividual star vectorAre the matching stars. Operator in formulaThe included angle between the two vectors is calculated. In particular, for any two vectorsAndwith an included angle ofIn the formulaAngular threshold, operator for star point matchingRepresenting aggregate subtraction. Specifically, for any two setsAndthe difference set thereof satisfiesIn the formulaRepresenting elements in an arbitrary collection; and the computing unit is used for computing the interframe attitude matrix according to the matched star points. Does not set the star point after the inter-frame matchingFrame and the secondBetween frames haveThe same star point. And do not markFirst of frameThe individual star points are exactly the same asFirst of frameAnd matching the individual star points. Then the second can be calculated by the attitude solution algorithm based on the above mentioned matching starsFrame and the secondInter-frame attitude matrix between frames, denotedTo satisfy。
Optionally, the feature module includes: a projection unit for calculating the coordinates of the projection star vector in the image coordinate system according to the pinhole camera model and recordingThe corresponding two-dimensional vector of the image coordinate system isIn the formulaAndtwo coordinate values of the projected star point image coordinate are respectively;a construction unit for constructing star point projection characteristics according to the projection star point two-dimensional coordinates。
Optionally, the classification module includes: a regression unit for projecting the characteristics according to the star pointsCalculating a linear regression matrixIn the formulaAndare respectively asAndaverage value of (d); a regression unit for further performing linear regression on the basis of the linear regression matrixCalculating the eigenvector corresponding to the minimum eigenvalue, and recording asAnd calculating its vertical vector from the vector(ii) a A decision unit for determining a vector based on the vectorAnd vectorSeparately calculating linear regression residualsAndthe calculation formula isAndand calculating the index of refraction star(ii) a A decision unit for further determining the index of the star of refractionClassifying the star points into two categories and definingThe star point of (A) is a non-refracting star, definedThe star point of (A) is a refraction star, whereinIs a classification threshold.
According to another aspect of the embodiments of the present invention, there is also provided a non-volatile storage medium including a stored program, wherein the program when running controls an apparatus in which the non-volatile storage medium is located to perform a multi-frame association-based non-refracted star and refracted star classification method.
According to another aspect of the embodiments of the present invention, there is also provided an electronic apparatus, including a processor and a memory; the memory has stored therein computer readable instructions for execution by the processor, wherein the computer readable instructions when executed perform a multi-frame joint based non-refracted star and refracted star classification method.
Through the embodiment, the non-refraction stars and the refraction stars are classified only by using the multi-frame star point position information, the classification accuracy is high, star map identification is not needed, and any prior pose information is not needed. The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In summary, in the embodiment of the present invention, inter-frame star point matching is performed according to inter-frame star point displacement, and an inter-frame attitude matrix is calculated; constructing multi-frame star point projection characteristics according to the interframe attitude matrix; the invention only uses the multi-frame star point position information to classify the non-refraction star and the refraction star, has high classification accuracy, does not need to carry out star map identification, and does not need any prior pose information. When the satellite in orbit loses prior information of the attitude and the position, the method can still correctly classify the non-refraction star and the refraction star in the star map, ensure the capability of the satellite in orbit to process emergency and improve the safety of the satellite in orbit.
In the embodiments provided in the present application, it should be understood that the disclosed technical content can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A non-refracted star and refracted star classification method based on multi-frame combination is characterized by comprising the following steps:
s100, performing inter-frame star point matching according to inter-frame star point displacement, and calculating an inter-frame attitude matrix;
s200, constructing a multi-frame star point projection characteristic according to the inter-frame attitude matrix;
and S300, constructing a refraction star classifier by using different projection characteristic properties between the refraction star and the non-refraction star, and obtaining a classification result.
2. The method for classifying a non-refraction star and a refraction star based on multi-frame association according to claim 1, wherein the step S100 comprises:
step S110, obtainThe star vectors of the camera coordinate system of all the star points in the frame image form a setIn the formulaThe vector of the star vector is used as the vector of the star,the number of the star marks is the same as the star number,is as followsThe total number of stars in the frame image; get the firstThe star vectors of the camera coordinate system of all the star points in the frame image form a setIn the formulaThe vector of the star vector is used as the vector of the star,the number of the star marks is the same as the star number,is as followsThe total number of stars in the frame image;
step S120, according to the second stepFrame and the firstFinding all matched star points by using the star vectors in the frame;
and S130, calculating an interframe attitude matrix according to the matched star points.
3. The method for classifying non-refraction stars and refraction stars based on multi-frame association as claimed in claim 2, wherein said step S200 comprises:
respectively calculating to obtain the second frame star point matching and the frame attitude matrix calculating methodFrame and preambleAn inter-frame attitude matrix between frames;
obtained by said calculationFrame and preambleThe posture matrix between frames projects the star point position at any time to the current timeTime of day;
4. The method for classifying a non-refracted star and a refracted star based on multi-frame association as claimed in claim 3, wherein said step S300 includes:
according to the linear regression matrixCalculating the eigenvector corresponding to the minimum eigenvalue, and recording as,Is a column vector of 2x1,is a column vectorAnd calculating its vertical vector from the vector;
According to the vectorAnd vectorSeparately calculating linear regression residualsAndthe calculation formula isAndand calculating the index of refraction star;
5. A multiframe combined non-refracted star and refracted star classification device, comprising:
the matching module is used for matching star points among multiple frames and calculating an interframe attitude matrix;
the characteristic module is used for constructing star point projection characteristics according to the matched star point and the inter-frame attitude matrix;
and the classification module is used for classifying the non-refraction stars and the refraction stars according to the star point projection characteristics.
6. The multi-frame combined non-refracted star and refracted star classifying device according to claim 5, wherein the matching module includes:
an acquisition unit for acquiringThe star vectors of the camera coordinate system of all the star points in the frame image form a setIn the formulaThe vector of the star vector is used as the vector of the star,the number of the star marks is the same as the star number,is as followsThe total number of stars in the frame image; get the firstThe star vectors of the camera coordinate system of all the star points in the frame image form a setIn the formulaThe vector of the star vector is used as the vector of the star,the number of the star marks is the same as the star number,is as followsThe total number of stars in the frame image;
a matching unit for searching all matching star points according to the star vectors of the two frames,
and the computing unit is used for computing the interframe attitude matrix according to the matched star points.
7. The multi-frame combined non-refracted star and refracted star classifying device according to claim 6, wherein the feature module includes:
the projection unit is used for calculating the coordinates of the projection star vector under the image coordinate system according to the pinhole camera model;
8. The multi-frame combined non-refracted star and refracted star classifying device according to claim 7, wherein the classifying module includes:
a regression unit for projecting the characteristics according to the star pointsCalculating a linear regression matrixIn the formulaAndare respectively asAndaverage value of (d); and also for use in accordance with the linear regression matrixCalculating the eigenvector corresponding to the minimum eigenvalue, and recording asAnd calculating its vertical vector from the vector;
A decision unit for determining a vector based on the vectorAnd vectorSeparately calculating linear regression residualsAndthe calculation formula isAndand calculating the index of refraction star(ii) a And also for determining the star index of refractionClassifying the star points into two categories and definingThe star point of (A) is a non-refracting star, definedThe star point of (A) is a refraction star, whereinIs a classification threshold.
9. A non-volatile storage medium, comprising a stored program, wherein the program, when executed, controls an apparatus in which the non-volatile storage medium is located to perform the method of any one of claims 1 to 4.
10. An electronic device comprising a processor and a memory; the memory has stored therein computer readable instructions for execution by the processor, wherein the computer readable instructions when executed perform the method of any of claims 1 to 4.
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