CN116662765B - Multi-track association method based on target topology - Google Patents
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- 239000006185 dispersion Substances 0.000 claims abstract description 23
- 238000009792 diffusion process Methods 0.000 claims abstract description 7
- 238000004364 calculation method Methods 0.000 claims abstract description 4
- 230000011218 segmentation Effects 0.000 claims description 5
- 239000013598 vector Substances 0.000 claims description 5
- 238000010187 selection method Methods 0.000 claims description 4
- 108700041286 delta Proteins 0.000 claims 2
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
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- G06N7/02—Computing arrangements based on specific mathematical models using fuzzy logic
Abstract
The invention relates to a multi-track association method based on target topology, and belongs to the technical field of passive positioning and tracking. The shortest distance point reaching n representative points is selected as a Fermat reference point, the characteristic difference between aircraft tracks is increased by selecting the Fermat reference point, whether two aircraft tracks are related or not is judged more easily, the three-dimensional matrix constructed by grid numbers is subjected to fuzzy diffusion treatment, the diffusion coefficient is increased, the possibility that the grid numbers are changed in adjacent areas due to large positioning errors of a satellite-borne satellite platform is reduced, and the accuracy of multi-track association is improved; and (3) carrying out fuzzy proximity calculation on the points of the aircraft tracks represented by the three-dimensional matrix after the fuzzy dispersion treatment to obtain the overlapping degree of the aircraft tracks, and effectively judging whether the aircraft tracks are related or not.
Description
Technical Field
The invention relates to a multi-track association method based on target topology, belongs to the technical field of passive positioning and tracking, and particularly relates to a heterogeneous track association method.
Background
In a satellite-borne passive positioning system, the association between two platforms and multiple tracks is challenging due to the large positioning errors. The relative position between tracks, namely the topological structure information is basically unchanged, and the correlation judgment can be carried out according to the relative position. Typical algorithms (Dan, wang Yue, wang Shugang, etc.. Fuzzy track correlation method based on target reference topology [ J ]. University of national defense science and technology journal, 2006 (04): 105-109.): and establishing relative position topology information by taking the target to be associated as a center and simultaneously taking the positions of other targets, and extracting the topological vector characteristics of the target. And finally, defining the fuzzy closeness and selecting a maximum value for correlation. However, this method has the following problems: 1. the association features are only applicable to two-dimensional association; 2. the association between multiple tracks needs to adopt multiple reference points, and the topology matrix information of the corresponding reference points needs to be required, so that the data processing is complex. Aiming at the problems, the method selects the proper Fisher-Tropsch reference point, and carries out multi-track association of non-common view observation by utilizing the topological structure according to the position of the multi-track relative to the Fisher-Tropsch reference point.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and solve the problem of non-common-view track association under the influence of positioning errors, and provides a multi-track association method based on target topology.
The method is realized by the following technical scheme:
a multi-track association method based on a target topology, the method comprising the steps of:
step one, acquiring point track position information of n aircraft tracks by using a satellite platform 1, taking an average value of the point tracks of each aircraft track to obtain representative points of each aircraft track, obtaining n representative points altogether, selecting a point reaching the shortest distance of the n representative points as a Fermat reference point 1, acquiring the point track position information of the n aircraft tracks by using a satellite platform 2, taking an average value of the point tracks of each aircraft track to obtain the representative points of each aircraft track, obtaining n representative points altogether, and selecting a point reaching the shortest distance of the n representative points as a Fermat reference point 2;
establishing a reference topological coordinate system 1 by taking the Fisher reference point 1 obtained in the step one as an origin, taking the X-axis direction of the aircraft track as the X-direction, taking the Y-axis direction of the aircraft track as the Y-direction and taking the Z-axis direction of the aircraft track as the Z-direction, wherein under the reference topological coordinate system 1, the point track of each aircraft track is represented by three characteristics; establishing a reference topological coordinate system 2 by taking the Fermat reference point 2 obtained in the step one as an origin, taking the X-axis direction of the aircraft track as the X-direction, taking the Y-axis direction of the aircraft track as the Y-direction and taking the Z-axis direction of the aircraft track as the Z-direction, wherein under the reference topological coordinate system 2, the point track of each aircraft track is represented by three characteristics;
step three, carrying out grid numbering treatment on the point trace of the aircraft track represented by three characteristics under the reference topological coordinate system 1 obtained in the step two, constructing a three-dimensional matrix 1 by using the numbering treatment, carrying out fuzzy dispersion treatment on the three-dimensional matrix 1, and representing the position 1 of the point trace of the aircraft track by using the three-dimensional matrix 1 after the fuzzy dispersion treatment;
grid numbering is carried out on the points of the aircraft track represented by three features under the reference topological coordinate system 2 obtained in the second step, a three-dimensional matrix 2 is constructed by using the numbers, fuzzy dispersion treatment is carried out on the three-dimensional matrix 2, and the positions 2 of the points of the aircraft track are represented by the three-dimensional matrix 2 after the fuzzy dispersion treatment;
and step four, carrying out fuzzy closeness calculation on the position 1 and the position 2 obtained in the step three to obtain a fuzzy closeness matrix, and carrying out global optimal distribution on the fuzzy closeness matrix by using a Hungary algorithm to obtain a trace matching pair of the aircraft track.
In the first step, the selection method of the Fermat reference point 1 comprises the following steps: expanding the method for selecting the Fermat points to n points to obtain Fermat reference points;
the selection method of the Fermat reference point 2 comprises the following steps: expanding the method for selecting the Fermat points to n points to obtain Fermat reference points;
in the second step, three features are as follows in reference to the topological coordinate system 1: the polar diameter r1, the included angle formed by clockwise rotation of the projection point of the point trace of the aircraft track on the XOY plane and the positive direction of the Y axis1. An included angle formed by clockwise rotation of a projected point of a track of the airplane on a YOZ plane and the positive direction of the Z axis is +.>1；
Referring to topological coordinate system 2, three features are: the projected point of the polar diameter r2 and the point trace of the aircraft track on the XOY plane forms an included angle with the clockwise rotation of the Y-axis positive direction2. An included angle formed by clockwise rotation of a projected point of a track of the airplane on a YOZ plane and the positive direction of the Z axis is +.>2；
In the third step, referring to the topological coordinate system 1, the grid number is expressed as:
wherein ,representing rounding down, < >>Is a set of polar paths r1 of the points of n aircraft tracks on the satellite platform 1,for the number of the track points of the aircraft track in the radius r1 division, +.>Is at->1 number of the track points of the aircraft track in the angle division,/-for the angle division>Is at->1, numbering the points of the aircraft track in the angle segmentation;
referring to topological coordinate system 2, the grid number is expressed as:
wherein ,representing rounding down, < >>Is a set of polar paths r2 of the points of n aircraft tracks on the satellite platform 2,for the number of the track points of the aircraft track in the radius r2 segmentation +.>Is at->2 number of the track points of the aircraft track in the angle division,/-for the angle division>Is at->2 numbering the points of the aircraft track in the angle segmentation;
in the third step, the three-dimensional matrix 1 is represented by: the value of the matrix at the grid number position of the point trace of the aircraft track is 1, and the other positions are 0;
the three-dimensional matrix 2 is represented by: the value of the matrix at the grid number position of the point trace of the aircraft track is 1, and the other positions are 0;
in the third step, the fuzzy dispersion treatment method comprises the following steps: in the three-dimensional matrix 1, the number positions of the upper layer, the lower layer, the row and the column with the value of 1 are added with the diffusion coefficient1（0</>1<1) Obtaining a reference topological grid dispersion matrix of the point trace of the aircraft track, namely a three-dimensional matrix 1 after fuzzy dispersion treatment;
the fuzzy dispersion treatment method comprises the following steps: in the three-dimensional matrix 2, the number positions of the upper layer, the lower layer, the row and the column with the value of 1 are added with the diffusion coefficient2（0</>2<1) Obtaining a reference topological grid dispersion matrix of the point trace of the aircraft track, namely a three-dimensional matrix 2 after fuzzy dispersion treatment;
in the fourth step, the fuzzy proximity degree calculating method comprises the following steps: and tiling the position 1 and the position 2 between the points of any two aircraft tracks into one-dimensional vectors, and then dot-accumulating the two one-dimensional vectors to obtain the fuzzy closeness between the points of the two aircraft tracks.
Advantageous effects
(1) According to the method, the shortest distance points reaching n representative points are selected as the Fermat reference points, and the characteristic distinction between the aircraft tracks is increased by selecting the Fermat reference points, so that whether the two aircraft tracks are related or not is easier to judge;
(2) The method provided by the invention has the advantages that the method for processing the grid number of the reference topology is provided, and the method uses an area body to represent the representative point of the aircraft track, so that the influence caused by large positioning error of satellite-borne electronic investigation is reduced;
(3) According to the method, the three-dimensional matrix of the grid number structure is subjected to fuzzy dispersion treatment, the dispersion coefficient is increased, the possibility that the grid number is changed in an adjacent area due to large positioning error of a satellite-borne satellite platform is reduced, and the accuracy of multi-track association is improved;
(4) According to the method, fuzzy closeness calculation is carried out between the points of the aircraft tracks represented by the three-dimensional matrix after fuzzy dispersion treatment, so that the overlapping degree between the aircraft tracks is obtained, and whether the aircraft tracks are related or not can be effectively judged.
Detailed Description
Examples
Embodiments of the method of the present invention will be described in detail with reference to examples.
A multi-track association method based on target topology comprises the following specific steps:
step one, the satellite platform 1 obtains the track position information of 10 aircraft tracks as follows:
the track position information of 10 aircraft tracks acquired by the satellite platform 2 is as follows:
the method comprises the steps of selecting the Fermat reference points of two satellite platforms as follows: the feima reference point 1 on the satellite platform 1 is (25269.09913, 10438.84611, 6585.770604), and the feima reference point 2 on the satellite platform 2 is (29409.76126, 11679.36223, 6708.660881);
step two, under the reference topological coordinate system 1, the characteristics of the points of 10 aircraft tracks in the satellite platform 1 are expressed as follows:
in reference to the topological coordinate system 2, the characteristics of the points of the 10 aircraft tracks in the satellite platform 2 are expressed as:
step three, grid numbering processing is carried out on the point trace of the aircraft track obtained in the step two, and a three-dimensional matrix 1 after the point trace fuzzy dispersion processing of the aircraft track of the satellite platform 1 is expressed as:
grid numbering processing is carried out on the point trace of the aircraft track obtained in the step two, and a three-dimensional matrix 2 after the point trace fuzzy dispersion processing of the aircraft track of the satellite platform 2 is expressed as follows:
step four, calculating fuzzy closeness between the points of the 10 aircraft tracks of the two satellite platforms obtained in the step three, wherein the fuzzy closeness matrix is as follows:
global optimal allocation is carried out by using a Hungary algorithm, and the obtained point trace matching pair of the aircraft track is as follows:
the matching pair of the points of the aircraft track can be obtained, and the accuracy rate of the correlation of the aircraft track in the example is 100%.
While embodiments of this invention have been described in connection with examples thereof, it will be apparent to those skilled in the art that numerous modifications can be made without departing from the principles of this invention, and these should also be considered to be within the scope of this invention.
Claims (6)
1. A multi-track association method based on target topology is characterized in that the method comprises the following steps:
step one, acquiring point track position information of n aircraft tracks by using a satellite platform 1, taking an average value of the point tracks of each aircraft track to obtain a representative point of each aircraft track, obtaining n representative points altogether, and selecting a point reaching the shortest distance of the n representative points as a Fermat reference point 1;
acquiring the point track position information of n aircraft tracks by using a satellite platform 2, taking the average value of the point tracks of each aircraft track to obtain the representative points of each aircraft track, obtaining n representative points in total, and selecting the point of the shortest distance reaching the n representative points as a Fermat reference point 2;
establishing a reference topological coordinate system 1 by taking the Fermat reference point 1 obtained in the first step as an origin, wherein under the reference topological coordinate system 1, the point trace of each aircraft track is represented by three characteristics;
establishing a reference topological coordinate system 2 by taking the Fermat reference point 2 obtained in the first step as an origin, wherein under the reference topological coordinate system 2, the point trace of each aircraft track is represented by three characteristics;
step three, carrying out grid numbering treatment on the point trace of the aircraft track represented by three characteristics under the reference topological coordinate system 1 obtained in the step two, constructing a three-dimensional matrix 1 by using the numbering treatment, carrying out fuzzy dispersion treatment on the three-dimensional matrix 1, and representing the position 1 of the point trace of the aircraft track by using the three-dimensional matrix 1 after the fuzzy dispersion treatment;
grid numbering is carried out on the points of the aircraft track represented by three features under the reference topological coordinate system 2 obtained in the second step, a three-dimensional matrix 2 is constructed by using the numbers, fuzzy dispersion treatment is carried out on the three-dimensional matrix 2, and the positions 2 of the points of the aircraft track are represented by the three-dimensional matrix 2 after the fuzzy dispersion treatment;
step four, carrying out fuzzy proximity calculation on the position 1 and the position 2 obtained in the step three to obtain a fuzzy proximity matrix, and carrying out global optimal allocation on the fuzzy proximity matrix by using a Hungary algorithm to obtain a point trace matching pair of the aircraft track;
referring to topological coordinate system 1, three features are: the method comprises the steps of (1) forming an included angle alpha 1 by clockwise rotation of a projected point of an aircraft track on a satellite platform 1 in an XOY plane and a Y-axis positive direction, and forming an included angle beta 1 by clockwise rotation of a projected point of the aircraft track on the satellite platform 1 in a YOZ plane and a Z-axis positive direction;
referring to topological coordinate system 2, three features are: the polar diameter r2, an included angle alpha 2 formed by clockwise rotation of a projected point of an aircraft track on the satellite platform 2 in the XOY plane and the positive direction of the Y axis, and an included angle beta 2 formed by clockwise rotation of a projected point of the aircraft track on the satellite platform 2 in the YOZ plane and the positive direction of the Z axis;
in the third step, referring to the topological coordinate system 1, the grid number is expressed as:
wherein ,represents rounding down, r1 * Is a set of polar paths r1 of the points of n aircraft tracks on the satellite platform 1,for the number of the track points of the aircraft track in the radius r1 division, +.>For numbering of the points of the aircraft track in the alpha 1 angle division, +.>Numbering the points of the aircraft track in the beta 1 angle segmentation;
referring to topological coordinate system 2, the grid number is expressed as:
wherein ,represents rounding down, r2 * Is a set of polar paths r2 of the points of n aircraft tracks on the satellite platform 2,for the number of the track points of the aircraft track in the radius r2 segmentation +.>For numbering of the points of the aircraft track in the alpha 2 angle division, +.>Is the number of the track points of the aircraft track in the beta 2 angle division.
2. A multi-track association method based on a target topology as claimed in claim 1, wherein:
in the first step, the selection method of the Fermat reference point 1 comprises the following steps: expanding the method for selecting the Fermat points to n points to obtain Fermat reference points;
the selection method of the Fermat reference point 2 comprises the following steps: and expanding the method for selecting the Fermat points to n points to obtain the Fermat reference points.
3. A multi-track association method based on a target topology according to claim 1 or 2, characterized in that:
in the second step, in the established reference topological coordinate system 1, the X-axis direction of the aircraft track on the satellite platform 1 is taken as the X-direction, the Y-axis direction of the aircraft track on the satellite platform 1 is taken as the Y-direction, and the Z-axis direction of the aircraft track on the satellite platform 1 is taken as the Z-direction;
in the established reference topological coordinate system 2, the X-axis direction of the aircraft track on the satellite platform 2 is taken as the X-direction, the Y-axis direction of the aircraft track on the satellite platform 2 is taken as the Y-direction, and the Z-axis direction of the aircraft track on the satellite platform 2 is taken as the Z-direction.
4. A multi-track association method based on a target topology as claimed in claim 1, wherein:
in the third step, the three-dimensional matrix 1 is represented by: the value of the matrix at the grid number position of the point trace of the aircraft track on the satellite platform 1 is 1, and the other positions are 0;
the three-dimensional matrix 2 is represented by: the matrix has a value of 1 at the grid number position of the track of the aircraft on the satellite platform 2 and 0 at the other positions.
5. The target topology based multi-track association method of claim 4, wherein:
in the third step, the fuzzy dispersion treatment method comprises the following steps: in the three-dimensional matrix 1, adding a diffusion coefficient delta 1 at the numbering positions of an upper layer, a lower layer, a row and a column with the value of 1 to obtain a reference topological grid diffusion matrix of the point trace of the aircraft track, namely the three-dimensional matrix 1 after fuzzy diffusion treatment; 0< Δ 1<1;
the fuzzy dispersion treatment method comprises the following steps: in the three-dimensional matrix 2, the number positions of the upper layer, the lower layer, the rows and the columns with the value of 1 are added with the dispersion coefficient delta 2, so that the reference topological grid dispersion matrix of the point trace of the aircraft track is obtained, namely the three-dimensional matrix 2 after fuzzy dispersion treatment is obtained, and the delta 2<1 is smaller than 0.
6. A multi-track association method based on a target topology as claimed in claim 1, wherein:
in the fourth step, the fuzzy proximity degree calculating method comprises the following steps: and tiling the position 1 and the position 2 between the points of any two aircraft tracks into one-dimensional vectors, and then dot-accumulating the two one-dimensional vectors to obtain the fuzzy closeness between the points of the two aircraft tracks.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2393430C1 (en) * | 2008-12-29 | 2010-06-27 | Федеральное государственное унитарное предприятие "Лётно-исследовательский институт имени М.М. Громова" | Method for high-precision measurement of aircraft trajectory coordinates in flight investigations on long routes |
| CN104239719A (en) * | 2014-09-19 | 2014-12-24 | 中国人民解放军海军航空工程学院 | Formation target track association algorithm based on duplex fuzzy topology in system errors |
| CN113310491A (en) * | 2021-05-17 | 2021-08-27 | 北京航空航天大学 | Unmanned aerial vehicle navigation network automatic generation method considering specific structure |
| CN116338716A (en) * | 2023-02-24 | 2023-06-27 | 中国人民解放军国防科技大学 | Multi-target association method of air-ground unmanned system based on azimuth topological structure |
| CN116449298A (en) * | 2023-02-20 | 2023-07-18 | 西安电子科技大学 | Track association method based on improved topology |
-
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- 2023-07-31 CN CN202310944191.6A patent/CN116662765B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2393430C1 (en) * | 2008-12-29 | 2010-06-27 | Федеральное государственное унитарное предприятие "Лётно-исследовательский институт имени М.М. Громова" | Method for high-precision measurement of aircraft trajectory coordinates in flight investigations on long routes |
| CN104239719A (en) * | 2014-09-19 | 2014-12-24 | 中国人民解放军海军航空工程学院 | Formation target track association algorithm based on duplex fuzzy topology in system errors |
| CN113310491A (en) * | 2021-05-17 | 2021-08-27 | 北京航空航天大学 | Unmanned aerial vehicle navigation network automatic generation method considering specific structure |
| CN116449298A (en) * | 2023-02-20 | 2023-07-18 | 西安电子科技大学 | Track association method based on improved topology |
| CN116338716A (en) * | 2023-02-24 | 2023-06-27 | 中国人民解放军国防科技大学 | Multi-target association method of air-ground unmanned system based on azimuth topological structure |
Non-Patent Citations (1)
| Title |
|---|
| 基于目标参照拓扑的模糊航迹关联方法;石;王钺;王树刚;山秀明;;国防科技大学学报(04);第105-109页 * |
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