CN103822635A - Visual information based real-time calculation method of spatial position of flying unmanned aircraft - Google Patents

Abstract

The invention discloses a visual information based real-time calculation method of spatial position of a flying unmanned aircraft, belonging to the technical field of digital video image processing. The method is mainly based on aerial photography image information, elevation information, combines unmanned aircraft flight parameter information to analyze and identify the spatial position of an unmanned aircraft. According to the method, images are rectified by using aerial photography images of an unmanned aircraft and combining flight parameters such as the elevation information of the unmanned aircraft, comparative analysis with prior information is conducted, so that the present location information of the unmanned aircraft can be obtained via the aerial photography images through inverse computation. The visual information based unmanned aircraft flight spatial location real-time calculation method aims to the characteristics of the unmanned aircraft, fully utilizes the visual information and improves the independence of the unmanned aircraft.

Description

Unmanned plane during flying spatial location real-time computing technique based on visual information

Technical field

The invention belongs to digital video image processing technology field, be specifically related to a kind of unmanned plane during flying spatial location real-time computing technique based on visual information.

Background technology

In recent years, along with the development of unmanned plane technology, unmanned plane is not only militarily widely used, and extends to gradually civilian occasion.Militarily, it can be used for aerial reconnaissance, electronic interferences, communication repeating, target localization, battlefield surveillance and border patrol etc., can be used for aeroplane photography, disaster surveillance, geophysical exploration, aeroplane photography etc. on civilian.

In the past, unmanned plane mainly relies on inertial navigation system (Inertial Navigation System, and GPS (Global Position System INS), GPS) navigate, but in navigation procedure, inertia device has cumulative errors, too responsive to initial value, and GPS is not always retrievable, even and can obtain, its precision often can not meet the needs of Navigation of Pilotless Aircraft.

In addition, radio signal and gps signal transmission are subject to block, and antijamming capability is not strong, advantage not obvious in the hidden scouting of military affairs.It is reported, Iran declares that it has cracked U.S. army's gps signal, has controlled communication link, and has successfully inveigled, caught a RQ-170 who executes the task in Iran " sentry " scounting aeroplane of U.S. army within the border.On September 13rd, 2009, out of hand when a MQ-9 of U.S. army " harvester " unmanned plane is executed the task in Afghan Mountainous Area of North, U.S. army helplessly sends fighter plane to be shot down, to prevent that it from flying into Tajikistan or Chinese territorial sky.The generation of these accidents is all because UAV Communication link is obstructed or is decoded and take over by enemy, receives false navigation position information, has reduced self reliability.

Gps signal is easily disturbed, and controlled by other country, and inertial navigation/GPS integrated navigation precision is limited.Also just because of these reasons, in order to improve unmanned plane autonomous flight and anti-deception ability, people have produced very large research interest to unmanned plane independent navigation, and have formed a focus in recent unmanned plane research field, and vision guided navigation independence is strong, the acquisition of navigational parameter does not rely on external unit, acquired information amount is large, is provided by aircraft self completely, and antijamming capability is strong, position location and identification are more accurate, highly beneficial to realizing the independent navigation of aircraft.

Vision guided navigation is take Relatively orientation as main at present, and for example aircraft, in landing mission,, constantly adjusts aspect if runway sideline is as reference take terrestrial reference, to reach the object of safe landing.The method of navigation Absolutely orientation is fewer, in unmanned plane during flying process, utilize GPS/INS integrated navigation, and assisting navigation based on vision has been realized navigator fix more accurately, but the in the situation that of communication link fails, utilize vision guided navigation to carry out Absolutely orientation and seem more important.

Summary of the invention

The object of the invention is in order to address the above problem, for unmanned plane own characteristic, unmanned plane during flying spatial location real-time computing technique based on visual information has been proposed, combining image treatment technology, utilize characteristics of image, contrast prior imformation, obtains unmanned plane air position information, improves unmanned plane independence.

Unmanned plane during flying spatial location real-time computing technique based on visual information, comprises following step:

Step 1, 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.

The invention has the advantages that:

(1) utilize unmanned aerial vehicle onboard resource and equipment, carry out the absolute fix of unmanned plane locus;

(2) utilize visible ray, the natural information such as infrared, good concealment;

Accompanying drawing explanation

Fig. 1 is method flow diagram of the present invention;

Fig. 2 is image information coupling process flow diagram of the present invention;

Fig. 3 is unmanned plane shooting point of the present invention and landforms central point geometric relationship figure.

Embodiment

Below in conjunction with accompanying drawing, the specific embodiment of the present invention is elaborated.

Unmanned plane during flying spatial location real-time computing technique based on visual information of the present invention, flow process as shown in Figure 1, comprises following step:

Step 1, sets up the relief data storehouse in unmanned plane during flying course line;

The course line of planning in advance according to unmanned plane, within sweep of the eye observable continuously at unmanned plane, extract image and the positional informations such as multiple geomorphological environment such as residential block, vegetation, highway, waters, and calculate the various features such as color, texture, straight line, angle point, SIFT of geomorphologic map picture, storage warehouse-in;

Be specially: first the course line of planning is gathered to destination, i.e. the buildings terrestrial reference such as signal beacon, viaduct or skyscraper, dotted line feature the storage of then calculating destination, its step is as follows:

(1) obtain the destination in unmanned plane course line;

According to the predefined planning of unmanned plane course line, choose the destination on unmanned plane course line, utilize multi-load equipment to gather the information of destination;

Unmanned plane during flying course line destination type comprises several as follows: the buildings terrestrial references such as signal beacon, viaduct or skyscraper, buildings terrestrial reference has feature obviously and the feature that is difficult to copy, choose buildings terrestrial reference as destination, be conducive to improve the reliability of the inventive method.

According to planning course line, utilize multi-load equipment to gather the much information of destination, comprise landmark image information, corresponding elevation information and navigation position information etc.;

(2) calculated characteristics;

Obtain the landmark image information of destination according to step (1), calculate the SIFT point feature, Harris Corner Feature, textural characteristics of destination etc.;

(3) obtain relief data storehouse;

Step (1), (2) are gathered to the positional information that calculates SIFT point feature, Harris Corner Feature, textural characteristics, Hough linear feature and landmark image, be deposited into relief data storehouse, complete the foundation in relief data storehouse.

The positional information of landmark image comprises 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 in real time the destination in course line, detect terrestrial references such as signal beacon, buildings, because Harris angular-point detection method has the features such as accuracy is high, real-time is good, utilize this detection method to detect destination terrestrial reference, by the destination detecting with in relief data storehouse, deposited destination and mated, carry out step 3 if the match is successful, detect execution step two otherwise proceed next destination;

Specifically comprise following step:

(1) destination detects

In the time of unmanned plane during flying to destination, adopt Harris angular-point detection method, obtain the Harris feature of this destination, Harris angular-point detection method has the features such as accuracy is high, real-time is good, has taken into account the requirement of efficiency and precision two aspects, and false detection rate is low.

(2) destination coupling

By the Harris feature of the destination obtaining, mate with the Harris feature of the destination of storing in relief data storehouse, carry out step 3 if the match is successful, detect execution step two otherwise proceed next destination;

Step 3, destination data acquisition.

To the destination that the match is successful, utilize airborne ccd video camera image data, data comprise high definition Aerial Images and the unmanned plane parameter of taking photo by plane, the unmanned plane parameter of taking photo by plane comprises unmanned plane height H, course angle α, angle of pitch β, roll angle γ and ccd video camera mesa corners η, position angle λ;

Step 4, Data Matching.

Storehouse is carried out respectively in the data that collect and relief data storehouse and mate, access landforms database, the landforms view data of extraction current location, utilizes characteristics of image to carry out feature point detection and mate, and calculates matching characteristic points N.

As shown in Figure 2, Data Matching comprises following step:

(1) Aerial Images pre-service;

First, owing to being subject to weather in unmanned plane during flying, temperature, the impact of the factors such as humidity, there is some difference for current Aerial Images and airborne relief data storehouse, therefore first Aerial Images is carried out to pre-service, comprise medium filtering denoising, grayscale enhancing method, and calculate SIFT point feature, Harris Corner Feature, the Hough linear feature of Aerial Images data;

(2) access landforms database;

Access landforms database, according to destination matching result, extracts the landforms view data of current destination position, comprises SIFT point feature, Harris Corner Feature and Hough linear feature;

(3) image information coupling;

By above-mentioned two steps, obtain the feature of landmark image (prior image information) in the Aerial Images of destination and relief data storehouse, choosing more outstanding feature mates, obtain matching characteristic points N, if N is greater than predetermined threshold value, the match is successful, enters step 5, otherwise it fails to match, return to step 3;

Be illustrated for outstanding feature, for example, if the more comparatively dense of Harris Corner Feature, express possibility and occurred residential block, or longer parallel lines occurs again, may there be highway below, and under these circumstances, Harris Corner Feature or Hough linear feature just seem more outstanding.In the situation that general features is not given prominence to, adopt SIFT point feature calculation matching characteristic points N, if N exceedes 10, think that the match is successful, otherwise unsuccessful.

Step 5, obtains unmanned plane positional information.

Complete after images match, according to Aerial Images prior imformation, inverse unmanned plane latitude and longitude information, finishes the work.

After images match success, illustrate that unmanned plane has reached position shown in this landmark image (in prior imformation) in relief data storehouse, geomorphologic map looks like to be in Aerial Images center, reads current unmanned plane central point A latitude and longitude coordinates (X, Y).Unmanned plane shooting point P and Aerial Images central point geometric relationship, as shown in Figure 3, P' be P point in ground projection, inverse unmanned plane longitude and latitude formula is as follows:

$\mathrm{\θ}=\frac{\mathrm{\π}}{2}-\mathrm{\η}+\mathrm{\γ}---\left(1\right)$

As shown in formula 1 and formula 2, θ angle is that ccd video camera and unmanned plane center of gravity are pointed to angle,

angle is the crab angle of ccd video camera with respect to body axis system (north day eastern coordinate system).Put the x of A to some P', y distance is:

Unmanned plane latitude and longitude coordinates is expressed as:

$P(x,y)=\left\{\begin{array}{c}[X-x\cos X/111000,Y-y/111000]\\ [X+x\cos X/111000,Y+y/111000]\\ [X+x\cos X/111000,Y-y/111000]\\ [X-x\cos X/111000,Y+y/111000]\end{array}\right.---\left(4\right)$

In formula 4, P (x, y) represents unmanned plane latitude and longitude coordinates, and landforms center A point is true origin, unmanned aerial vehicle projection P ' point may be arranged in any one of four quadrants of coordinate system centered by A point, so formula 4 is computing method of four quadrants of correspondence.Represent four different quadrant internal coordinate computing formula.

The present invention is directed to the practical application request of unmanned plane, propose one and do not relied on data link, the real-time computing technique scheme of unmanned plane during flying spatial location based on visual information, according to airborne equipment measurement data and self-contained priori data, carry out autonomous location recognition, improve unmanned plane independence.

Claims (5)

1. the unmanned plane during flying spatial location real-time computing technique based on visual information, comprises following step:

Step 1, sets up the relief data storehouse in unmanned plane during flying course line;

According to the predefined planning of unmanned plane course line, choose the destination on unmanned plane course line, obtain the landmark image information of destination, calculate SIFT point feature, Harris Corner Feature, textural characteristics, the Hough linear feature of destination, by the positional information of above-mentioned feature and landmark image, be 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, by the destination detecting with in relief data storehouse, deposited destination and mated, carry out step 3 if the match is successful, detect execution step two otherwise proceed next destination;

Step 3, destination data acquisition;

To the destination that the match is successful, utilize airborne ccd video camera image data, data comprise high definition Aerial Images and the unmanned plane parameter of taking photo by plane, the unmanned plane parameter of taking photo by plane comprises unmanned plane height H, course angle α, angle of pitch β, roll angle γ and ccd video camera mesa corners η, position angle λ;

Step 4, Data Matching;

Storehouse is carried out respectively in the data that collect and relief data storehouse and mate, access landforms database, the landforms view data of extraction current location, utilizes characteristics of image to carry out feature point detection and mate, and calculates matching characteristic points N;

Step 5, obtains unmanned plane positional information;

Complete after images match, according to Aerial Images prior imformation, inverse unmanned plane latitude and longitude information, finishes the work.

2. the unmanned plane during flying spatial location real-time computing technique based on visual information according to claim 1, described step 1 specifically comprises following step:

(1) obtain the destination in unmanned plane course line;

According to the predefined planning of unmanned plane course line, choose the destination on unmanned plane course line, destination is chosen buildings terrestrial reference, utilizes the information of multi-load equipment collection destination, obtains the landmark image information of destination;

(2) calculated characteristics;

Obtain the landmark image information of destination according to step (1), calculate SIFT point feature, Harris Corner Feature, textural characteristics, the Hough linear feature of destination;

(3) obtain relief data storehouse;

Step (1), (2) are gathered to the positional information that calculates SIFT point feature, Harris Corner Feature, textural characteristics, Hough linear feature and landmark image, be deposited into relief data storehouse, complete the foundation in relief data storehouse;

The positional information of landmark image comprises destination figure title, picture size, centre coordinate.

3. the unmanned plane during flying spatial location real-time computing technique based on visual information according to claim 1, described step 2 specifically comprises following step:

(1) destination detects

In the time of unmanned plane during flying to destination, adopt Harris angular-point detection method, obtain the Harris Corner Feature of this destination;

(2) destination coupling

By the Harris Corner Feature of the destination obtaining, mate with the Harris Corner Feature of the destination of storing in relief data storehouse, carry out step 3 if the match is successful, detect execution step two otherwise proceed next destination.

4. the unmanned plane during flying spatial location real-time computing technique based on visual information according to claim 1, described step 4 specifically comprises following step:

(1) Aerial Images pre-service;

First, Aerial Images is carried out to pre-service, comprise that medium filtering denoising, gray scale strengthen, and calculate SIFT point feature, Harris Corner Feature, the Hough linear feature of Aerial Images data;

(2) access landforms database;

Access landforms database, according to destination matching result, extracts the landforms view data of current destination position, comprises SIFT point feature, Harris Corner Feature and Hough linear feature;

(3) image information coupling;

By above-mentioned two steps, obtain the feature of landmark image in the Aerial Images of destination and relief data storehouse, selected characteristic is mated, obtain matching characteristic points N, if N is greater than predetermined threshold value, the match is successful, enter step 5, otherwise it fails to match, return to step 3.

5. the unmanned plane during flying spatial location real-time computing technique based on visual information according to claim 1, described step 5 is specially:

After images match success, read current unmanned plane central point A latitude and longitude coordinates (X, Y), establishing P is unmanned plane shooting point, P' be P point in ground projection, inverse unmanned plane longitude and latitude formula is as follows:

$\mathrm{\θ}=\frac{\mathrm{\π}}{2}-\mathrm{\η}+\mathrm{\γ}---\left(1\right)$

θ angle is that ccd video camera and unmanned plane center of gravity are pointed to angle,

angle is the crab angle of ccd video camera with respect to body axis system; Put the x of A to some P', y distance is:

Unmanned plane latitude and longitude coordinates is expressed as:

$P(x,y)=\left\{\begin{array}{c}[X-x\cos X/111000,Y-y/111000]\\ [X+x\cos X/111000,Y+y/111000]\\ [X+x\cos X/111000,Y-y/111000]\\ [X-x\cos X/111000,Y+y/111000]\end{array}\right.---\left(4\right)$

P (x, y) represents unmanned plane latitude and longitude coordinates, and formula (4) is four different quadrant internal coordinate computing formula.

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