CN103822635B - The unmanned plane during flying spatial location real-time computing technique of view-based access control model information - Google Patents
The unmanned plane during flying spatial location real-time computing technique of view-based access control model information Download PDFInfo
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- CN103822635B CN103822635B CN201410078669.2A CN201410078669A CN103822635B CN 103822635 B CN103822635 B CN 103822635B CN 201410078669 A CN201410078669 A CN 201410078669A CN 103822635 B CN103822635 B CN 103822635B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
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Abstract
The invention discloses the unmanned plane during flying spatial location real-time computing technique of a kind of view-based access control model information, belong to digital video image processing technology field.The method Main Basis Aerial Images information, elevation information, merge unmanned plane during flying parameter information, unmanned plane air position is given analysis and identifies.Utilize unmanned plane Aerial Images, in conjunction with flight parameters such as unmanned plane elevation informations, to correct image, with prior information relative analysis, Aerial Images inverse go out unmanned plane current location information.The present invention is directed to unmanned plane feature, make full use of visual information, improve unmanned plane autonomy.
Description
Technical field
The invention belongs to digital video image processing technology field, the unmanned plane being specifically related to a kind of view-based access control model information flies
Row spatial location real-time computing technique.
Background technology
In recent years, along with the development of unmanned air vehicle technique, unmanned plane is the most militarily widely used, and
And gradually extend to civilian occasion.Militarily, it can be used for aerial reconnaissance, electronic interferences, communication relay, target location, war
Monitor and border patrol etc., civilian on can be used for aeroplane photography, disaster surveillance, geophysical exploration, aeroplane photography etc..
In the past, unmanned plane relied primarily on inertial navigation system (Inertial Navigation System, INS) and the whole world
Alignment system (Global Position System, GPS) is navigated, but, in navigation procedure, inertia device has accumulation
Error, the most sensitive to initial value, and GPS is not the most retrievable, even and can obtain, its precision is often full
The foot the most not needs of Navigation of Pilotless Aircraft.
It addition, radio signal and gps signal transmission are the most blocked, capacity of resisting disturbance is not strong, in military hidden scouting
Advantage is the most inconspicuous.It is reported, Iran declares that it has cracked U.S. army's gps signal, controls communication link, and successfully inveigles, catches
One frame of Huo Liao U.S. army performs RQ-170 " sentry " scounting aeroplane of task within the border in Iran.On JIUYUE 13rd, 2009, U.S. army one
Frame MQ-9 " harvester " unmanned plane performs during task out of hand in Afghanistan Mountainous Area of North, and U.S. army helplessly sends fighter plane to be incited somebody to action
It shoots down, to prevent it from flying into Tajikistan or China territorial sky.The generation of these accidents is all due to UAV Communication link
It is obstructed or is decoded by enemy and take over, receiving false navigation position information, reduce own reliability.
Gps signal is easily disturbed, easily by other country's control, and inertial navigation/GPS integrated navigation limited precision.Also just because of
These reasons, in order to improve unmanned plane autonomous flight and anti-fraud ability, unmanned plane independent navigation is created the biggest by people
Research interest, and define a focus in recent unmanned plane research field, and vision guided navigation autonomy is strong, navigational parameter
Acquisition is independent of external equipment, it is thus achieved that contain much information, and is provided by aircraft self completely, and capacity of resisting disturbance is strong, location positioning and knowledge
The most accurate, highly beneficial to the independent navigation realizing aircraft.
Vision guided navigation is based on Relatively orientation at present, and such as aircraft is in landing mission, with terrestrial reference such as runway sideline
For reference, aspect is constantly adjusted, to reach the purpose of safe landing.The method of navigation Absolutely orientation compares
Few, during unmanned plane during flying, utilize GPS/INS integrated navigation, and the assisting navigation of view-based access control model achieve the most accurate
Navigator fix, but in the case of communication link fails, utilize vision guided navigation to carry out Absolutely orientation and seem more important.
Summary of the invention
The invention aims to solve the problems referred to above, for unmanned plane own characteristic, it is proposed that view-based access control model information
Unmanned plane during flying spatial location real-time computing technique, in conjunction with image processing techniques, utilize characteristics of image, contrast priori letter
Breath, it is thus achieved that unmanned plane air position information, improves unmanned plane autonomy.
The unmanned plane during flying spatial location real-time computing technique of view-based access control model information, including following step:
Step one, sets up relief data storehouse, unmanned plane during flying course line；
Step 2, destination detects；
Step 3, data acquisition；
Step 4, Data Matching；
Step 5, obtains positional information.
It is an advantage of the current invention that:
(1) utilize unmanned aerial vehicle onboard resource and equipment, carry out the absolute fix of unmanned plane locus；
(2) visible ray, the natural information such as infrared, good concealment are utilized；
Accompanying drawing explanation
Fig. 1 is the method flow diagram of the present invention；
Fig. 2 is the image information coupling flow chart of the present invention；
Fig. 3 is unmanned plane shooting point and the landforms central point geometrical relationship figure of the present invention.
Detailed description of the invention
Below in conjunction with accompanying drawing, the detailed description of the invention of the present invention is described in detail.
The unmanned plane during flying spatial location real-time computing technique of the view-based access control model information of the present invention, flow process as it is shown in figure 1,
Including following step:
Step one, sets up the relief data storehouse in unmanned plane during flying course line；
The course line planned in advance according to unmanned plane, the most observable within sweep of the eye at unmanned plane, extract multiple
Image and the positional informationes such as geomorphological environment such as residential block, vegetation, highway, waters, and calculate the color of geomorphologic map picture, texture,
The various features such as straight line, angle point, SIFT, storage warehouse-in；
Particularly as follows: first the course line planned to be gathered destination, the i.e. building such as signal beacon, viaduct or skyscraper
Thing terrestrial reference, then calculates the dotted line feature of destination and stores, and its step is as follows:
(1) destination in unmanned plane course line is obtained；
According to unmanned plane planning set in advance course line, choose the destination on unmanned plane course line, utilize multi-load equipment to adopt
The information of collection destination；
Unmanned plane during flying course line destination type includes the most several: signal beacon, viaduct or skyscraper etc. are built
Thing terrestrial reference, building terrestrial reference has feature and substantially and is difficult to the feature replicated, and chooses building terrestrial reference as destination, is conducive to carrying
The reliability of high the inventive method.
According to planning course line, multi-load equipment is utilized to gather the much information of destination, including landmark image information, corresponding height
Journey information and navigation position information etc.；
(2) feature is calculated；
Obtain the landmark image information of destination according to step (1), calculate the SIFT point feature of destination, Harris angle point spy
Levy, textural characteristics etc.；
(3) relief data storehouse is obtained；
Step (1), (2) are gathered and are calculated SIFT point feature, Harris Corner Feature, textural characteristics, Hough straight line
Feature and the positional information of landmark image, be deposited into relief data storehouse, completes the foundation in relief data storehouse.
The positional information of landmark image includes destination figure title, picture size, centre coordinate.
According to the structure shown in table 1, store information into relief data storehouse, complete the foundation in relief data storehouse.
Table 1 relief data library structure
Step 2, unmanned plane, in airline operation, carries out destination detection.
In unmanned plane during flying, detect the destination in course line in real time, i.e. detect the terrestrial references such as such as signal beacon, building, due to
Harris angular-point detection method has the features such as accuracy is high, real-time is good, utilizes this detection method to examine destination terrestrial reference
Survey, the destination detected is mated with having deposited destination in relief data storehouse, if the match is successful, carries out step 3, otherwise continue
The continuous next one destination that carries out detects, and performs step 2；
Specifically include following step:
(1) destination detection
When unmanned plane during flying a to destination, using Harris angular-point detection method, the Harris obtaining this destination is special
Levying, Harris angular-point detection method has the features such as accuracy is high, real-time is good, has taken into account and has wanted of both efficiency and precision
Asking, false detection rate is low.
(2) destination coupling
In the Harris feature of destination that will obtain, with relief data storehouse, the Harris feature of the destination of storage is carried out
Join, if the match is successful, carry out step 3, otherwise proceed next destination detection, perform step 2；
Step 3, destination data acquisition.
To the destination that the match is successful, utilizing airborne ccd video camera to gather data, data include high definition Aerial Images and unmanned
Machine is taken photo by plane parameter, and unmanned plane parameter of taking photo by plane includes unmanned plane height H, course angle α, pitching angle beta, and roll angle γ and CCD images
Machine platform angle η, azimuth λ；
Step 4, Data Matching.
With relief data storehouse, the data collected are carried out storehouse respectively mate, access landforms data base, extract current location
Landforms view data, utilize characteristics of image to carry out feature point detection and mate, be calculated matching characteristic points N.
As in figure 2 it is shown, Data Matching includes following step:
(1) Aerial Images pretreatment；
Firstly, since by weather, temperature, the impact of the factors such as humidity in unmanned plane during flying, current Aerial Images is with airborne
There is some difference in relief data storehouse, first Aerial Images is carried out pretreatment, including medium filtering denoising, grey level enhancement
Method, and calculate the SIFT point feature of Aerial Images data, Harris Corner Feature, Hough linear feature；
(2) landforms data base is accessed；
Access landforms data base, according to destination matching result, extract the landforms view data of current waypoint location, including
SIFT point feature, Harris Corner Feature and Hough linear feature；
(3) image information coupling；
By above-mentioned two step, obtain Aerial Images and (the prior image letter of landmark image in relief data storehouse of destination
Breath) feature, choose the most prominent feature and mate, obtain matching characteristic points N, if N is more than predetermined threshold value, then
Being made into merit, enter step 5, otherwise it fails to match, returns step 3；
It is illustrated for prominent feature, such as, if the more comparatively dense of Harris Corner Feature, then it represents that could
Can occur in that residential block, or the longest parallel lines occurs, then may there be a highway lower section, in this case,
Harris Corner Feature or Hough linear feature just seem the most prominent.In the case of general features is not prominent, use
SIFT point feature calculation matching characteristic points N, if N is more than 10, then it is assumed that the match is successful, the most unsuccessful.
Step 5, obtains unmanned plane positional information.
After completing images match, according to Aerial Images prior information, inverse unmanned plane latitude and longitude information, complete work.
After images match success, illustrate that unmanned plane has reached this landmark image (in prior information) in relief data storehouse shown
Position, geomorphologic map picture is in Aerial Images center, reads currently without man-machine central point A latitude and longitude coordinates (X, Y).Unmanned plane
Shooting point P and Aerial Images central point geometrical relationship, as it is shown on figure 3, P' is that P point is at floor projection, inverse unmanned plane longitude and latitude
Formula is as follows:
As shown in formula 1 and formula 2, θ angle is that ccd video camera points to angle with unmanned plane center of gravity,Angle is ccd video camera
Yaw angle relative to body axis system (east, sky, north coordinate system).Then some A to x, the y distance of some P' is:
Unmanned plane latitude and longitude coordinates is expressed as:
In formula 4, (x, y) represents unmanned plane latitude and longitude coordinates to P, and landforms center A point is zero, and unmanned aerial vehicle is thrown
Shadow P' point is likely located at any one in four quadrants of coordinate system centered by A point, so formula 4 is corresponding four quadrants
Computational methods.Illustrate four different quadrant internal coordinate computing formula.
The present invention is directed to the practical application request of unmanned plane, it is proposed that one is independent of data link, view-based access control model
The unmanned plane during flying spatial location real-time computing technique scheme of information, according to airborne equipment measurement data and self-contained elder generation
Test data, carry out autonomous station identification, improve unmanned plane autonomy.
Claims (4)
1. the unmanned plane during flying spatial location real-time computing technique of view-based access control model information, including following step:
Step one, sets up the relief data storehouse in unmanned plane during flying course line；
According to unmanned plane planning set in advance course line, choose the destination on unmanned plane course line, obtain the landmark image letter of destination
Breath, calculates the SIFT point feature of destination, Harris Corner Feature, textural characteristics, Hough linear feature, by features described above and
The positional information of landmark image, is deposited into relief data storehouse；
Step 2, unmanned plane, in airline operation, carries out destination detection；
In unmanned plane during flying, detect in real time the destination in course line, carry out destination has been deposited in the destination detected and relief data storehouse
Coupling, if the match is successful, carries out step 3, otherwise proceeds next destination detection, performs step 2；
Step 3, destination data acquisition；
To the destination that the match is successful, utilizing airborne ccd video camera to gather data, data include high definition Aerial Images and unmanned plane boat
Clapping parameter, unmanned plane parameter of taking photo by plane includes that unmanned plane height H, course angle α, pitching angle beta, roll angle γ and ccd video camera are flat
Corner of table η, azimuth λ；
Step 4, Data Matching；
With relief data storehouse, the data collected are carried out storehouse respectively mate, access landforms data base, extract the ground of current location
Looks view data, utilizes characteristics of image to carry out feature point detection and mate, is calculated matching characteristic points N；
Step 5, obtains unmanned plane positional information；
After completing images match, according to Aerial Images prior information, inverse unmanned plane latitude and longitude information, complete work；
Described step 5 particularly as follows:
After images match success, read currently without man-machine central point A latitude and longitude coordinates (X, Y), if P is unmanned plane shooting point, P'
For P point at floor projection, inverse unmanned plane longitude and latitude formula is as follows:
θ angle is that ccd video camera points to angle with unmanned plane center of gravity,Angle is the ccd video camera driftage relative to body axis system
Angle；Then some A to x, the y distance of some P' is:
Unmanned plane latitude and longitude coordinates is expressed as:
(x, y) represents unmanned plane latitude and longitude coordinates to P, and formula (4) is four different quadrant internal coordinate computing formula.
The unmanned plane during flying spatial location real-time computing technique of view-based access control model information the most according to claim 1, described
Step one specifically include following step:
(1) destination in unmanned plane course line is obtained；
According to unmanned plane planning set in advance course line, choosing the destination on unmanned plane course line, destination chooses building terrestrial reference, profit
Gather the information of destination with multi-load equipment, obtain the landmark image information of destination；
(2) feature is calculated；
Obtain the landmark image information of destination according to step (1), calculate the SIFT point feature of destination, Harris Corner Feature, stricture of vagina
Reason feature, Hough linear feature；
(3) relief data storehouse is obtained；
Step (1), (2) are gathered and are calculated SIFT point feature, Harris Corner Feature, textural characteristics, Hough linear feature
And the positional information of landmark image, it is deposited into relief data storehouse, completes the foundation in relief data storehouse；
The positional information of landmark image includes destination figure title, picture size, centre coordinate.
The unmanned plane during flying spatial location real-time computing technique of view-based access control model information the most according to claim 1, described
Step 2 specifically include following step:
(1) destination detection
When unmanned plane during flying a to destination, using Harris angular-point detection method, the Harris angle point obtaining this destination is special
Levy；
(2) destination coupling
The Harris Corner Feature of the destination of storage in the Harris Corner Feature of the destination of acquisition, with relief data storehouse is carried out
Coupling, if the match is successful, carries out step 3, otherwise proceeds next destination detection, performs step 2.
The unmanned plane during flying spatial location real-time computing technique of view-based access control model information the most according to claim 1, described
Step 4 specifically include following step:
(1) Aerial Images pretreatment；
First, Aerial Images is carried out pretreatment, including medium filtering denoising, grey level enhancement, and calculate Aerial Images data
SIFT point feature, Harris Corner Feature, Hough linear feature；
(2) landforms data base is accessed；
Access landforms data base, according to destination matching result, extract the landforms view data of current waypoint location, including SIFT point
Feature, Harris Corner Feature and Hough linear feature；
(3) image information coupling；
Access landforms data base by above-mentioned steps (1) Aerial Images pretreatment and step (2), obtain the Aerial Images of destination with
The feature of landmark image in relief data storehouse, selected characteristic is mated, and obtains matching characteristic points N, if N is more than presetting threshold
Value, then the match is successful, enters step 5, and otherwise it fails to match, returns step 3.
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Families Citing this family (30)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN104808680A (en) * | 2015-03-02 | 2015-07-29 | 杨珊珊 | Multi-rotor flight shooting device |
| CN104713548A (en) * | 2015-03-30 | 2015-06-17 | 成都好飞机器人科技有限公司 | Automatic positioning method for air vehicle |
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| CN109791414A (en) * | 2016-09-26 | 2019-05-21 | 深圳市大疆创新科技有限公司 | The method and system that view-based access control model lands |
| CN106408964B (en) * | 2016-12-05 | 2019-01-29 | 山东大学 | The acquisition methods of the preferential accurate lane grade control area of air-ground coordination bus signals |
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| CN109840285B (en) * | 2019-03-12 | 2023-01-10 | 广东电网有限责任公司 | Automatic image naming method based on latitude and longitude of target |
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| CN110926474B (en) * | 2019-11-28 | 2021-09-03 | 南京航空航天大学 | Satellite/vision/laser combined urban canyon environment UAV positioning and navigation method |
| CN111951178B (en) * | 2020-07-07 | 2024-04-30 | 中国人民解放军93114部队 | Image processing method and device for remarkably improving image quality and electronic equipment |
| CN114202583A (en) * | 2021-12-10 | 2022-03-18 | 中国科学院空间应用工程与技术中心 | Visual positioning method and system for unmanned aerial vehicle |
| TWI835320B (en) * | 2022-09-29 | 2024-03-11 | 國立政治大學 | UAV visual navigation system and method for ground feature image positioning and correction |
| CN116503768B (en) * | 2023-06-29 | 2023-11-07 | 中国科学院心理研究所 | Aerial docking method and device for flight equipment |
| CN117470199B (en) * | 2023-12-27 | 2024-03-15 | 天津云圣智能科技有限责任公司 | Swing photography control method and device, storage medium and electronic equipment |
| CN118050007A (en) * | 2024-04-16 | 2024-05-17 | 南昌航空大学 | Unmanned aerial vehicle navigation system and method based on image recognition |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN100567898C (en) * | 2007-01-16 | 2009-12-09 | 北京航空航天大学 | Pilotless plane landing navigation method and device thereof |
| CN102426019B (en) * | 2011-08-25 | 2014-07-02 | 航天恒星科技有限公司 | Unmanned aerial vehicle scene matching auxiliary navigation method and system |
| CN102853835B (en) * | 2012-08-15 | 2014-12-31 | 西北工业大学 | Scale invariant feature transform-based unmanned aerial vehicle scene matching positioning method |
| CN103175524B (en) * | 2013-02-20 | 2015-11-25 | 清华大学 | A kind of position of aircraft without view-based access control model under marking environment and attitude determination method |
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Effective date of registration: 20170417 Address after: 100191 Beijing, Xueyuan Road, No. 37, inside the Patentee after: Beijing northern sky long hawk UAV Technology Co. Ltd. Address before: 100191 Haidian District, Xueyuan Road, No. 37, Patentee before: Beihang University |
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