CN104331882A - Method for measuring speed of aircraft - Google Patents

Abstract

The invention provides a method for measuring the speed of an aircraft. The speed of the aircraft is estimated by the aid of a sequential image shot by a camera. The method includes the steps: firstly, respectively correcting images in front time and rear time from current positions to positions with zero-degree attitude angles according to attitude angle information; secondly, automatically registering the two images based on an SIFT (scale invariant feature transform) algorithm and determining an overlap area of the images in the front time and the rear time to obtain a group of optimal matching points; thirdly, calculating the speed of the aircraft according to remote sensor height information and shooting time. The method for measuring the speed of the aircraft has the advantages of independent working performance, high interference resistance, simplicity and convenience in use and the like, and is suitable for future aerial development trend.

Description

A kind of method measuring aircraft speed

Technical field

The present invention relates to airborne remote sensing field, in particular to a kind of method measuring aircraft speed.

Background technology

Camera imaging model: because video camera is fixing on aircraft, therefore, the pose of video camera can be directly used in the pose characterizing aircraft.Camera imaging model can be described below:

$\mathrm{\λ}\left[\begin{array}{c}{x}^{\′}\\ y^{\′}\\ 1\end{array}\right]=\left[\begin{array}{cccc}{f}_x& 0& c_x& 0\\ 0& f_y& c_y& 0\\ 0& 0& 1& 0\end{array}\right]\left[\begin{array}{cccc}{r}_{11}& r_{12}& r_{13}& t_x\\ r_{21}& r_{22}& r_{23}& t_y\\ r_{31}& r_{32}& r_{33}& t_z\\ 0& 0& 0& 1\end{array}\right]\left[\begin{array}{c}x\\ y\\ z\\ 1\end{array}\right]$

Wherein, on the right of equation, Section 1 is camera internal reference matrix, f _x=f/dx, f _y=f/dy, be called the normalization focal length in x-axis and y-axis, f is camera focus, dx and dy represents the size of unit picture element in sensor x-axis and y-axis respectively.C _xand c _ywhat then represent is optical centre, i.e. the intersection point of camera optical axis and the plane of delineation, is usually located at picture centre place, therefore its value often gets the half of resolution.

The pose of video camera is represented by attitude angle, and namely Eulerian angle are used for describing the orientation of rigid body at three-dimensional Euclidean space.For the reference frame of in three dimensions, the orientation of any coordinate system, can show by three Eulerian angle.As shown in Figure 1, comprising xyz-axle and XYZ-coordinate axis, claim xy-plane to be the line of nodes (N) with the crossing of XY-plane, three Eulerian angle (α, beta, gamma) are defined as respectively: α is the angle of x-axle and the line of nodes; β is the angle of z-axle and Z-axle; γ is the angle of the line of nodes and X-axle.If α=0 °, β=30 °, γ=0 °, namely x-axle overlaps with X-axle, and overlaps with the line of nodes, and the angle of z-axle and Z-axle is 30 °.

For any reference frame, the orientation of a rigid body is that the rotation doing three Eulerian angle from this reference frame sets according to order.So the orientation of rigid body can decide with three basic rotation matrixs, namely any rotation matrix R rotated about rigid body is composited by three basic rotation matrixs:

$R=\left[\begin{array}{ccc}\cos \mathrm{\γ}& \sin \mathrm{\γ}& 0\\ -\sin \mathrm{\γ}& \cos \mathrm{\γ}& 0\\ 0& 0& 1\end{array}\right]\left[\begin{array}{ccc}1& 0& 0\\ 0& \cos \mathrm{\β}& \sin \mathrm{\β}\\ 0& -\sin \mathrm{\β}& \cos \mathrm{\β}\end{array}\right]\left[\begin{array}{ccc}\cos \mathrm{\α}& \sin \mathrm{\α}& 0\\ -\sin \mathrm{\α}& \cos \mathrm{\α}& 0\\ 0& 0& 1\end{array}\right]$

Summary of the invention

The object of the invention is to provide a kind of method measuring aircraft speed, the sequence image utilizing video camera to take estimation aircraft speed.

Above-mentioned purpose of the present invention is realized by the technical characteristic of independent claims, and dependent claims develops the technical characteristic of independent claims with alternative or favourable mode.

For reaching above-mentioned purpose, technical scheme of the present invention is as follows:

Measure a method for aircraft speed, the sequence image estimation aircraft speed utilizing video camera to take, its realization comprises the following steps:

Step 1, respectively the image in front and back two moment is corrected to from current location the position that attitude angle is 0 according to attitude angle information;

Step 2, based on SIFT algorithm, autoregistration is carried out to aforementioned two width images, determine the picture registration region in front and back two moment, obtain one group of optimal match point; And

Step 3, calculate the speed of aircraft in conjunction with remote sensor elevation information and shooting time.

From the above technical solution of the present invention shows that, beneficial effect of the present invention is:

The present invention proposes the portable aviation speed-measuring method that a kind of serviceability is independent, precision is higher, and speed-measuring method main at present has that GPS (GPS) tests the speed, radar Doppler tests the speed and Pitot-static tube speed-measuring method.Wherein GPS has larger restriction on testing the speed and using, and signal is easily disturbed; Radar Doppler tests the speed volume and weight greatly, and use cost is high; Pitot-static tube tests the speed easily affected by environment.The present invention program is based on sequence image, and the feature such as have that cost is low, independence is strong, interference resistance is strong and easy to use, is applicable to following aviation development trend.

Accompanying drawing explanation

Fig. 1 is the schematic diagram of Eulerian angle.

Fig. 2 is the schematic flow sheet that an embodiment of the present invention measures the method for aircraft speed.

Fig. 3 is the principle schematic calculating aircraft speed in Fig. 2 embodiment according to remote sensor elevation information and shooting time.

Embodiment

In order to more understand technology contents of the present invention, institute's accompanying drawings is coordinated to be described as follows especially exemplified by specific embodiment.

As shown in Figure 2, according to preferred embodiment of the present invention, a kind of method measuring aircraft speed, the sequence image utilizing video camera to take estimation aircraft speed, its realization comprises the following steps:

Step 1, respectively the image in front and back two moment is corrected to from current location the position that attitude angle is 0 according to attitude angle information;

Step 2, based on SIFT algorithm, autoregistration is carried out to aforementioned two width images, determine the picture registration region in front and back two moment, obtain one group of optimal match point; And

Step 3, calculate the speed of aircraft in conjunction with remote sensor elevation information and shooting time.

Shown in accompanying drawing 2-3, describe the concrete enforcement of above steps in detail.

Step 1, respectively the image in front and back two moment is corrected to from current location the position that attitude angle is 0 according to attitude angle information

Updating formula is:

$\mathrm{\λ}\left[\begin{array}{c}{x}^{\′}\\ y^{\′}\\ 1\end{array}\right]={\mathrm{KR}}^{-1}{K}^{-1}\left[\begin{array}{c}x\\ y\\ 1\end{array}\right]$

In formula: λ is scale factor, K is intrinsic parameters of the camera matrix, and R is the orthogonal rotation matrix of unit.

Particularly, in the present embodiment, correct according to following step:

First converted images size is determined; Then by correct after coordinate figure inverse transformation to original image coordinate points; Carry out sub-pixel positioning finally by quadratic interpolattion, obtain the image after correcting.

Step 2, based on SIFT algorithm, autoregistration is carried out to aforementioned two width images, determine the picture registration region in front and back two moment, obtain one group of optimal match point

In the present embodiment, specifically comprise the following steps:

(1) detection of key point: by input picture by the gaussian kernel function continuous filtering of different scale and down-sampling, forms gaussian pyramid image, and then subtracts each other two Gaussian image of adjacent yardstick and obtain DoG pyramid multiscale space and represent;

Compare one by one the point of each point of DoG metric space and adjacent yardstick and adjacent position, the local extremum position obtained is position residing for key point and corresponding yardstick;

(2) SIFT descriptor is constructed: the gradient direction distribution characteristic utilizing key point neighborhood territory pixel is each key point assigned direction parameter: by X-axis rotate to unique point direction, to ensure rotational invariance; To any one key point, at the metric space at its place, get the neighborhood of 16 × 16 pixel sizes centered by key point, then this neighborhood is divided into 4 × 4 sub regions equably, to every sub regions compute gradient direction histogram, this histogram is evenly divided into 8 directions; Then, sort successively according to position to 8 histograms of oriented gradients of 4 × 4 sub regions, form the vector of 4 × 4 × 8=128 dimension, this vector is SIFT descriptor;

(3) characteristic matching: adopt Euclidean distance to measure as the similarity determination of key point in two width images, when this distance is less than setting threshold value, then judges that these two key points are as possible match point;

(4) error hiding is removed: to the institute's likely matching double points determined, set less tolerance, application RANSAC robust method carries out Geometrical consistency inspection, obtains one group of optimal match point;

(5) affined transformation: two width image mapped are determined overlapping region under same coordinate system.

Step 3, calculate the speed of aircraft in conjunction with remote sensor elevation information and shooting time

Through the match point of the front and back two moment sequence image of overcorrect, be positioned at and differing heights be parallel to each other and be parallel in the plane of lunar surface, therefore the displacement in the x, y, z-directions of video camera photocentre can be obtained respectively in conjunction with elevation information.

To a change in coordinate axis direction and two moment t ₁and t ₂, as shown in Figure 3, p ₁and p ₂matching double points, be on lunar surface same point P in not picture point in the same time, O _i(i=1,2) are the positions of camera, therefore can obtain according to similar triangle theory:

$\frac{C_i{P}_i}{T_{i}P}=\frac{O_i{C}_i}{O_i{T}_i}$

In formula: i=1,2, O _ic _ifor focal length of camera f, O _it _ifor camera height H _i, some C _ifor t _ithe central point of time chart picture, C _ip _ifor pixel P in image _ito the distance of central pixel point.Therefore, at focal length of camera f, camera height O _it _iwhen known, by the distance C of match point in measurement image to picture centre pixel _ip _i, we can obtain:

$T_{i}P=\frac{f}{H_i}{C}_i{P}_i$

Thus, between two moment, video camera photocentre relative to the displacement on ground is

$T_1{T}_2=T_{1}P+P{T}_2=\frac{f}{H_1}{C}_1{P}_1+\frac{f}{H_2}{C}_2{P}_2$

In conjunction with shooting time, the instantaneous velocity that difference can obtain all directions is carried out to the displacement of all directions.

v＝T ₁T ₂/(|t ₂-t ₁|)

Although the present invention with preferred embodiment disclose as above, so itself and be not used to limit the present invention.Persond having ordinary knowledge in the technical field of the present invention, without departing from the spirit and scope of the present invention, when being used for a variety of modifications and variations.Therefore, protection scope of the present invention is when being as the criterion depending on those as defined in claim.

Claims (4)

1. measure a method for aircraft speed, the sequence image estimation aircraft speed utilizing video camera to take, is characterized in that, comprise the following steps:

Step 1, respectively the image in front and back two moment is corrected to from current location the position that attitude angle is 0 according to attitude angle information;

Step 2, based on SIFT algorithm, autoregistration is carried out to aforementioned two width images, determine the picture registration region in front and back two moment, obtain one group of optimal match point; And

Step 3, calculate the speed of aircraft in conjunction with remote sensor elevation information and shooting time.

2. the method for measurement aircraft speed according to claim 1, it is characterized in that, the realization of abovementioned steps 1 comprises the following steps:

First determine converted images size, then by correct after coordinate figure inverse transformation to original image coordinate points, carry out sub-pixel positioning finally by quadratic interpolattion, obtain correct after image, wherein updating formula is:

$\mathrm{\λ}\left[\begin{array}{c}{x}^{\′}\\ y^{\′}\\ 1\end{array}\right]={\mathrm{KR}}^{-1}{K}^{-1}\left[\begin{array}{c}x\\ y\\ 1\end{array}\right]$

In formula: λ is scale factor, K is intrinsic parameters of the camera matrix, and R is the orthogonal rotation matrix of unit.

3. the method for measurement aircraft speed according to claim 1, it is characterized in that, the specific implementation of abovementioned steps 2 comprises the following steps:

(1) detection of key point: by input picture by the gaussian kernel function continuous filtering of different scale and down-sampling, forms gaussian pyramid image, and then subtracts each other two Gaussian image of adjacent yardstick and obtain DoG pyramid multiscale space and represent;

Compare one by one the point of each point of DoG metric space and adjacent yardstick and adjacent position, the local extremum position obtained is position residing for key point and corresponding yardstick;

(2) SIFT descriptor is constructed: the gradient direction distribution characteristic utilizing key point neighborhood territory pixel is each key point assigned direction parameter: by X-axis rotate to unique point direction, to ensure rotational invariance; To any one key point, at the metric space at its place, get the neighborhood of 16 × 16 pixel sizes centered by key point, then this neighborhood is divided into 4 × 4 sub regions equably, to every sub regions compute gradient direction histogram, this histogram is evenly divided into 8 directions; Then, sort successively according to position to 8 histograms of oriented gradients of 4 × 4 sub regions, form the vector of 4 × 4 × 8=128 dimension, this vector is SIFT descriptor;

(3) characteristic matching: adopt Euclidean distance to measure as the similarity determination of key point in two width images, when this distance is less than setting threshold value, then judges that these two key points are as possible match point;

(4) error hiding is removed: to the institute's likely matching double points determined, set less tolerance, application RANSAC robust method carries out Geometrical consistency inspection, obtains one group of optimal match point;

(5) affined transformation: two width image mapped are determined overlapping region under same coordinate system.

4. the method for measurement aircraft speed according to claim 1, it is characterized in that, in abovementioned steps 3, to the match point of the front and back two moment sequence image through overcorrect, be positioned at and differing heights be parallel to each other and be parallel in the plane of lunar surface, therefore the displacement in the x, y, z-directions of video camera photocentre can be obtained respectively in conjunction with elevation information, then the instantaneous velocity that difference can obtain all directions is carried out to the displacement of all directions, specifically comprises:

To a change in coordinate axis direction and two moment t ₁and t ₂, p ₁and p ₂being matching double points, is that on lunar surface, same point P, in not picture point in the same time, therefore can to obtain according to similar triangle theory:

$\frac{C_i{P}_i}{T_{i}P}=\frac{O_i{C}_i}{O_i{T}_i}$

In formula: i=1,2, O _ithe position of camera, O _ic _ifor focal length of camera f, O _it _ifor camera height H _i, some C _ifor t _ithe central point of time chart picture, C _ip _ifor pixel P in image _ito the distance of central pixel point;

Due to focal length of camera f, camera height O _it _iknown, by match point p in measurement image ₁and p ₂to the distance C of picture centre pixel _ip _i, obtain:

$T_{i}P=\frac{f}{H_i}{C}_i{P}_i$

Thus, video camera photocentre is tried to achieve between two moment relative to the displacement T on ground ₁t ₂:

$T_1{T}_2=T_{1}P+{\mathrm{PT}}_2=\frac{f}{H_1}{C}_1{P}_1+\frac{f}{H_2}{C}_2{P}_2$

In conjunction with shooting time, the instantaneous velocity that difference can obtain all directions is carried out to the displacement of all directions:

v＝T ₁T ₂/(|t ₂-t ₁|)。