CN102706352A - Vector map matching navigation method for linear target in aviation - Google Patents

Abstract

The invention discloses a vector map matching navigation method for a linear target in aviation, which comprises the following steps: preparing a base vector diagram and a template vector diagram for map matching, unifying the base vector diagram and the template vector diagram under a same vector precision level, and extracting included angle characteristics of the template vector diagram and the base vector diagram; sequentially utilizing a distance constraint condition, a sequence constraint condition and an error constraint condition to gradually limit size of a feasible solution space; clustering pose parameters of the feasible solution space, taking a class containing most pose parameters as a correct matching relationship; and further computing the pose parameters to be errors for correcting an inertial navigation system by matching positioning results. The method provided by the invention can overcome shortages of space efficiency and time efficiency in the existing grid image matching navigation method for aviation and avoids the problems of large data volume, low efficiency and the like in the grid image matching; in addition, the method provided by the invention overcomes influence of small-scale change on a vector map and can achieve vector map matching under rotation, translation and small-scale change.

Description

A kind of aviation is with the map vector coupling air navigation aid of linear target

Technical field

The present invention relates to a kind of map vector coupling navigation (Vector Map Matching Navigation) method, particularly a kind of aviation is with the map vector coupling air navigation aid of linear target.

Background technology

Scene matching aided navigation assisting navigation technology has been successfully applied in the cruise missile terminal guidance system so that its measuring accuracy is high, independence is strong, antijamming capability is outstanding, system energy consumption is low, the high outstanding advantage of navigation accuracy.Because scene matching aided navigation often adopts grating image as the matched data source, its airborne reference database generally requires memory space bigger, and image matching algorithm is consuming time longer usually, and the real-time of navigational system is had certain influence.

Adopt the grating image Matching Location different with the scene matching aided navigation navigation, the navigation of map vector coupling is based on the location technology of vector image coupling.Its basic process is: utilize airborne imageing sensor to gather ground image, and through mating with the map vector data storehouse that is stored in the navigational computer in advance after the Flame Image Process such as denoising, vector quantization, thereby obtain the navigational parameter of aircraft.With respect to the grating image coupling, the navigate mode that matees based on map vector has following advantage:

(1) non-loss transformation.Because image to be matched and reference picture all are made up of vector, thus can be rotated, harmless mathematic(al) manipulations such as convergent-divergent, perspective, and the grating image convergent-divergent can produce the discontinuous ladder phenomenon of pixel.

(2) space efficiency is high.Vector image adopts few point coordinate to represent complicated X-Y scheme, and than grating image, its expression way data volume is little, and the memory capacity that therefore airborne chart datum database needs is also just less.

(3) time efficiency is high.The grating image coupling often need scan the entire image zone, and calculated amount is big, and therefore the point that vector image often only needs the processing vector key element to comprise can realize the quick computing of images match process.

Simultaneously, the navigation of map vector coupling exists vector image and expresses not shortcoming intuitively, can not directly utilize coordinate figure to mate, and matching algorithm is comparatively complicated.Usually can select for use other characteristic quantities to mate, for linear target, geometric properties commonly used comprises length, concavity, angle, position angle etc., and some scholar also proposes to adopt characteristic quantities such as curvature, described function to carry out the line target coupling.For example, Wang Wencheng etc. have proposed with the curvature between the characteristic segments as matching characteristic through outline line is carried out segmentation; Through splicing, verified that the feasibility of this method (is seen Wang Wencheng, Li Xiaowei to four province's maps such as Tibet, Qinghai, Sichuan, Yunnan; Intelligence is good, etc., " based on the outline line coupling of Hausdorff distance "; " Xian Institute of Posts and Telecoms's journal ", 2007,12 (3): 91-94).Also have, pair Zhong Liang etc. adopt the shape description function of positive tangent space, are dependent variable with normalization apart from the corner that is independent variable, each peripheral broken line; This description form also can be used for the coupling of wire vector key element, has embodied the continuity of vector line segment, and the accuracy rate problem that can solve coupling preferably (is seen and paid Zhong Liang; Shao Shiwei, " the quick shape matching method of complicated planar vector key element ", " mapping circular "; 2011, (3): 26-28).

At present; What aviation was adopted with the map match navigational system basically is scene matching aided navigation assisting navigation mode; And the vector matching technology is mainly used in the GIS field; The maintenance and the aspects such as renewal, location-based navigation Service that comprise the integrated or fusion of spatial data, multiscale space data are not well used in the navigation field of aircraft.In addition; In the vector graphics coupling in GIS field; Mostly under the situation geometric element of two Matching Source be complete and shape identical; And aviation with map vector coupling navigational system in, the geometric element of imageing sensor images acquired behind vector quantization be the part of ground geometric element often, there is bigger difference in the vector matching under two kinds of situations.Map vector coupling navigate mode is that the navigation of aircraft provides a kind of new thinking, has bright development prospect, and along with the development of vector matching technology, its advantage will be more and more obvious also, and this case promptly is based on aforementioned thinking and produces.

Summary of the invention

The object of the invention; Be to provide the map vector coupling air navigation aid of a kind of aviation with linear target; It can overcome existing aviation with the deficiency of grating image coupling air navigation aid on space efficiency and time efficiency; Avoid grating image coupling problems, the problem includes: problem such as data volume is big, efficient is low, and overcome small scale and change influence, can accomplish at the map vector that has under rotation, translation and the small scale conversion and mate map vector.

In order to reach above-mentioned purpose, solution of the present invention is:

A kind of aviation comprises the steps: with the map vector coupling air navigation aid of linear target

(1) judges whether to start the navigation by map-matching system,, then prepare the base vector figure and the template vector figure of map match if start;

(2) template vector figure and base vector figure is unified under same vector accuracy rank, and the angle characteristic of extraction template vector figure and base vector figure;

(3) based on the template vector figure of step (2) acquisition and the angle characteristic of base vector figure; Utilize distance restraint condition, order constrained condition and three constraintss of error constraints progressively to limit the size in feasible solution space successively, finally obtain the 3rd layer of feasible solution space;

(4) the pose parametric solution to the 3rd layer of feasible solution space carries out cluster; To comprise the maximum class of pose parametric solution as correct matching relationship; And then utilize the pose algorithm for estimating to calculate the pose parameter, proofread and correct the error of inertial navigation system as the Matching Location result.

The particular content of above-mentioned steps (1) is:

Step 101, judge whether to get into the navigation by map-matching zone, if not, then do not start the navigation by map-matching system based on the inertial navigation system outgoing position; If, then start the navigation by map-matching system, promptly allow aircraft keep horizontal attitude, and utilize airborne imageing sensor to gather ground image, get into step 102;

Step 102, be written near the map vector data storehouse the inertial navigation system outgoing position, as the base vector figure of map match based on the wire key element;

Step 103, to the linear target of gathering in real time on the ground image, obtain real-time polar plot through vector technology based on the wire key element, it is the image coordinate system of unit in the image upper left corner, with the pixel that the coordinate system of this real-time polar plot adopts initial point;

Step 104, with the coordinate transform of real-time polar plot under the geographic coordinate yardstick, as the template vector figure of map match.

The particular content of above-mentioned steps (2) is:

Step 201, employing Douglas-Peucker method are compressed template vector figure and base vector figure, in compression process, use identical distance threshold value D ₁Thereby, template vector figure and base vector figure is unified under same vector accuracy rank;

Step 202, compression obtains to step 201 respectively real-time polar plot and base vector figure, all broken lines among the sweep vector figure, and calculate corresponding broken line angle sequence.

The particular content of above-mentioned steps (3) is:

Step 301, to the angle sequence of each bar broken line among the template vector figure, calculate its with base vector figure on unidirectional Hausdorff distance between all broken line angle sequences, keep on the base vector figure unidirectional Hausdorff apart from less than predetermined threshold value D ₂All broken lines, as ground floor feasible solution space;

Step 302, in the ground floor feasible solution space that step 301 obtains; Reject the broken line that does not satisfy condition in proper order according to the broken line angle; To the broken line that satisfies condition, find out possible point correspondence between template vector figure and the base vector figure, and then set up second layer feasible solution space;

Step 303, for all possible point correspondence in the second layer feasible solution space; Utilize the position and orientation estimation method of anti-change of scale to find the solution rotation angle, side-play amount and scale factor; And after utilizing the rotation angle obtain and side-play amount that template vector figure is carried out the pose conversion; Compare and find the solution the square mean error amount of being had a few with base vector figure, with square mean error amount greater than predetermined threshold value D ₅Point correspondence from second layer feasible solution space, reject away, thereby set up the 3rd layer of feasible solution space.

The particular content of above-mentioned steps 301 is: the angle sequence of certain broken line is A=[α on the note template vector figure ₁, α ₂..., α _n], certain broken line angle sequence does on the base vector figure

K representes the numbering of this broken line on the base vector figure, then unidirectional Hausdorff distance h (A, B ^k) computing formula following:

$h(A,B^k)=\underset{{\mathrm{\α}}_i\∈A}{\max }\underset{{{\mathrm{\β}}_j}^k\∈B^k}{\min }|{\mathrm{\α}}_i-{{\mathrm{\β}}_j}^k|$

All angles in the following formula reflection sequence A are to sequence B ^kMinimal difference, as A and B ^kUnidirectional Hausdorff distance h (A, B ^k) greater than preset predetermined threshold value D ₂The time, judge B ^kThe broken line that corresponding broken line is corresponding with A does not also match.

The particular content of above-mentioned steps 302 is: in the ground floor feasible solution space that certain broken line is corresponding in template vector figure, set up and the identical to be selected corresponding broken line of template vector figure broken line number of endpoint as starting point with each end points on the base vector figure bar broken line respectively; Then, this broken line of template vector figure each angle with base vector figure corresponding broken line to be selected is compared, the note difference is at threshold value D ₃With interior angle number is N _S, total angle number is N, if ratio N _S/ N is greater than predetermined threshold value D ₄, think that then the corresponding broken line of this base vector figure satisfies order constrained condition, and write down this group point correspondence in second time feasible solution space.

The particular content of above-mentioned steps 303 is: suppose that in second layer feasible solution space, a certain group of point correspondence is: the coordinate of template vector figure point set P is p _i=[p _Ix, p _Iy] ^T(i=1,2 ..., n), the coordinate of corresponding base vector figure point set Q is q _i=[q _Ix, q _Iy] ^T, the coordinate transform relation between note template vector figure and the base vector figure is q=sRp+t, and wherein, t is a side-play amount, and s is a scale factor, and R is a rotation matrix, the detailed process of the position and orientation estimation method of anti-change of scale is following:

(1) according to following formula, the center point coordinate that calculates point set P and point set Q is:

$\stackrel{\‾}{p}=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{p}_i,\stackrel{\‾}{q}=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{q}_i$

(2), estimate that scale factor is according to following formula:

$\hat{s}=\sqrt{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\left|\right|q_i-\stackrel{\‾}{q}\left|\right|}^2/\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\left|\right|p_i-\stackrel{\‾}{p}\left|\right|}^2}$

(3), estimate that the anglec of rotation

is according to following formula:

$a=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}({\tilde{p}}_{\mathrm{ix}}\hat{s}{\tilde{q}}_{\mathrm{iy}}-{\tilde{p}}_{\mathrm{iy}}\hat{s}{\tilde{q}}_{\mathrm{ix}}),b=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}({\tilde{p}}_{\mathrm{ix}}\hat{s}{\tilde{q}}_{\mathrm{ix}}+{\tilde{p}}_{\mathrm{iy}}\hat{s}{\tilde{q}}_{\mathrm{iy}})$

(4), estimate that side-play amount is according to following formula:

$\hat{t}=\stackrel{\‾}{q}-\hat{s}\hat{R}\stackrel{\‾}{p}$

Wherein the estimated value of rotation matrix can obtain according to following formula:

$\hat{R}=\left[\begin{array}{cc}\cos \left(\widehat{\mathrm{\θ}}\right)& -\sin \left(\widehat{\mathrm{\θ}}\right)\\ \sin \left(\widehat{\mathrm{\θ}}\right)& \cos \left(\widehat{\mathrm{\θ}}\right)\end{array}\right]$

(5) calculate square error e:

$e=\sqrt{\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\left|\right|q_i-(\hat{s}\hat{R}{p}_i+\hat{t})\left|\right|}^2}.$

The particular content of above-mentioned steps (4) is:

Step 401, to each pose parametric solution, set up a class, and calculate with other all pose parametric solutions between difference, if angle difference, position difference and yardstick difference are distinguished all less than predetermined threshold value D ₆, D ₇, D ₈, then with in this pose parametric solution type of depositing in;

Step 402, find out the class of pose parametric solution most number; And find out the point correspondence of such all pose parametric solution representatives; According to all corresponding point; Utilize the pose algorithm for estimating of anti-change of scale to calculate the pose parameter, and as the output of final matching positioning result, in order to proofread and correct the error of inertial navigation system.

After adopting such scheme; The present invention adopts map vector as the matched data source; The angle of broken line is as the matching characteristic amount; And based on the thought of handling by different level, reduce the size in feasible solution space successively according to distance restraint condition, order constrained condition and error constraint condition, thereby fast and reliable ground obtains the navigation by map-matching result.

Description of drawings

Fig. 1 is that map vector coupling navigational system of the present invention constitutes synoptic diagram;

Fig. 2 is the algorithm flow chart of map vector coupling air navigation aid of the present invention;

Fig. 3 is a vector compression Douglas-Peucker ratio juris synoptic diagram of the present invention;

Fig. 4 is a broken line angle sequence synoptic diagram of the present invention;

Fig. 5 is verification of correctness test simulation of the present invention figure as a result;

Fig. 6 is the simulation result figure of certain reliability testing test of the present invention;

Fig. 7 is the anglec of rotation Error Graph of reliability testing test of the present invention;

Fig. 8 is the site error figure of reliability testing test of the present invention.

Embodiment

Below with reference to accompanying drawing, technical scheme of the present invention is elaborated.

Shown in Figure 1 is that map vector matees navigational system formation synoptic diagram; The navigation of map vector coupling utilizes airborne imageing sensor to gather ground or target area image; The real-time map vector that Flame Image Process is obtained matees with the map vector data storehouse that is stored in the navigational computer in advance, thereby obtains the navigational parameter of aircraft.Map vector coupling navigational system mainly comprises Flame Image Process, extracted region, map vector matching algorithm and four parts of navigation calculation.

(1) Flame Image Process:, utilize image denoising, yardstick unification, vector quantization etc. to handle the back and obtain the corresponding real-time polar plot, as the input source of matching algorithm according to real-time collection grating image.

(2) extracted region: according to reference position and the site error scope that other navigate modes such as INS provide, extract the vector data in the navigation area in the map vector data storehouse, form base vector figure, as the reference source of matching algorithm.

(3) map vector matching algorithm:, confirm the position of real-time polar plot in base vector figure, anglec of rotation etc. according to the process of search, comparison, optimizing based on real-time polar plot and base vector figure.

(4) navigation calculation: according to coordinate transform relation, confirm the navigational parameters such as geographic position, course angle of carrier, and then the INS navigation error is proofreaied and correct.

The process flow diagram that is a kind of aviation provided by the present invention with the map vector coupling air navigation aid of linear target shown in Figure 2 specifically comprises the steps:

Step 1, algorithm initialization: judge whether to start the navigation by map-matching system,, then prepare the base vector figure and the template vector figure of map match if start.

Step 101, judge whether to get into the navigation by map-matching zone, if not, then do not start the navigation by map-matching system based on the inertial navigation system outgoing position; If, then start the navigation by map-matching system, promptly allow aircraft keep horizontal attitude, and utilize airborne imageing sensor to gather ground image, get into step 102;

Step 102, be written near the map vector data storehouse the inertial navigation system outgoing position, as the base vector figure of map match based on the wire key element.

Linear targets such as step 103, the river on the real-time collection ground image, road, mountain range obtain the real-time polar plot based on the wire key element through vector technology.It is the image coordinate system of unit in the image upper left corner, with the pixel that the coordinate system of this real-time polar plot adopts initial point;

Step 104, with the coordinate transform of real-time polar plot to geographic coordinate system, as the template vector figure of map match.Suppose that aircraft is h at reference altitude ₀And during horizontal flight, the ingestible ground of imageing sensor scope is x ₀* y ₀, the image size of collection is a * b (pixel), the current geography of navigational system indication highly is h, then the coordinate range with x in the real-time polar plot transform to from [0, b] [0, (h/h ₀) * x ₀], the coordinate range of y transform to from [0, a] [0, (h/h ₀) * y ₀].

Step 2, feature extraction: template vector figure and base vector figure is unified under same vector accuracy rank, and the angle characteristic of extraction template vector figure and base vector figure.

Step 201, the compression of vector line segment: adopt the Douglas-Peucker method that template vector figure and base vector figure are compressed, in compression process, use identical distance threshold value D ₁Thereby, template vector figure and base vector figure is unified under same vector accuracy rank.

Suppose certain vector line segment shown in the ABCDEF curve among Fig. 3, then the basic process of vector compression Douglas-Peucker method is following:

(1) junction curve AF end points obtains straight-line segment AF (string of curve), calculates the AF that leaves bowstring on this curve apart from the some C of maximum, calculate its to AF apart from d.

(2) the distance threshold value T of comparison d and appointment.If < T then is regarded as the approximate of curve with this straight-line segment to d; If d>T, then curve is divided into two sections AC and CF with C, respectively two line segments are handled according to above method.

(3) after all curve processing finish, connecting the broken line that each cut-point forms successively, be the compression result of vector line segment, is the vector quantization compression result of curve A F like the broken line ABCDEF among Fig. 1.

Step 202, angle feature extraction: compression obtains to step 201 respectively real-time polar plot and base vector figure, all broken lines among the sweep vector figure, and calculate corresponding broken line angle sequence.

Suppose the P among certain vector line segment such as Fig. 4 ₁P ₂P ₃P ₄P ₅Shown in the broken line, then the computation process of angle sequence is following: choose three some P on the broken line successively ₁P ₂P ₃, angle is defined as vector P ₁P ₂With vector P ₂P ₃Between angle, i.e. P ₁P ₂P ₃P ₄P ₅The angle sequence that broken line is corresponding is α ₁～α ₃

Step 3, multi-level constraint:, utilize distance restraint condition, order constrained condition and three constraint conditions of error constraint condition progressively to limit the size in feasible solution space successively according to the template vector figure of step 2 acquisition and the angle characteristic of base vector figure.

Step 301, distance restraint condition: to the angle sequence of each bar broken line among the template vector figure; Calculate the unidirectional Hausdorff distance between all broken line angle sequences on itself and the base vector figure, keep on the base vector figure unidirectional Hausdorff distance less than predetermined threshold value D ₂All broken lines, as ground floor feasible solution space.

The angle sequence of certain broken line is A=[α on the note template vector figure ₁, α ₂..., α _n], certain broken line angle sequence does on the base vector figure

K representes the numbering of this broken line on the base vector figure, then unidirectional Hausdorff distance h (A, B ^k) computing formula following:

$h(A,B^k)=\underset{{\mathrm{\&alpha;}}_i\&Element;A}{\max }\underset{{{\mathrm{\&beta;}}_j}^k\&Element;B^k}{\min }|{\mathrm{\&alpha;}}_i-{{\mathrm{\&beta;}}_j}^k|$

All angles in the following formula reflection sequence A are to sequence B ^kMinimal difference, as A and B ^kUnidirectional Hausdorff distance h (A, B ^k) greater than preset predetermined threshold value D ₂The time, can judge B ^kThe broken line that corresponding broken line is corresponding with A does not also match.

Step 302, order constrained condition: in the ground floor feasible solution space that step 301 obtains; Reject the broken line that does not satisfy condition in proper order according to the broken line angle; To the broken line that satisfies condition; Find out possible point correspondence between template vector figure and the base vector figure, and then set up second layer feasible solution space.

Utilize the detailed process of broken line angle order constrained condition following: in the ground floor feasible solution space that certain broken line is corresponding in template vector figure, to set up and the identical to be selected corresponding broken line of template vector figure broken line number of endpoint as starting point with each end points on the base vector figure bar broken line respectively; Then, this broken line of template vector figure each angle with base vector figure corresponding broken line to be selected is compared, the note difference is at threshold value D ₃With interior angle number is N _S, total angle number is N, if ratio N _S/ N is greater than predetermined threshold value D ₄, think that then the corresponding broken line of this base vector figure satisfies order constrained condition, and write down this group point correspondence in second time feasible solution space.

Step 303, error constraint condition: for all possible point correspondence in the second layer feasible solution space; Utilize the position and orientation estimation method of anti-change of scale to find the solution rotation angle, side-play amount and scale factor; And after utilizing the rotation angle obtain and side-play amount that template vector figure is carried out the pose conversion; Compare and find the solution the square mean error amount of being had a few with base vector figure, with square mean error amount greater than predetermined threshold value D ₅Point correspondence from second layer feasible solution space, reject away, and be designated as the 3rd layer of feasible solution space.

Suppose that in second layer feasible solution space, a certain group of point correspondence is: the coordinate of template vector figure point set P is p _i=[p _Ix, p _Iy] ^T(i=1,2 ..., n), the coordinate of corresponding base vector figure point set Q is q _i=[q _Ix, q _Iy] ^T, the coordinate transform relation between note template vector figure and the base vector figure is q=sRp+t, and wherein, t is a side-play amount, and s is a scale factor, and R is a rotation matrix, the detailed process of the position and orientation estimation method of anti-change of scale is following:

(1) according to following formula, the center point coordinate that calculates point set P and point set Q is:

$\stackrel{\&OverBar;}{p}=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{p}_i,\stackrel{\&OverBar;}{q}=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{q}_i$

(2), estimate that scale factor

is according to following formula:

$\hat{s}=\sqrt{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{\left|\right|q_i-\stackrel{\&OverBar;}{q}\left|\right|}^2/\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{\left|\right|p_i-\stackrel{\&OverBar;}{p}\left|\right|}^2}$

(3), estimate that the anglec of rotation

is according to following formula:

$a=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}({\tilde{p}}_{\mathrm{ix}}\hat{s}{\tilde{q}}_{\mathrm{iy}}-{\tilde{p}}_{\mathrm{iy}}\hat{s}{\tilde{q}}_{\mathrm{ix}}),b=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}({\tilde{p}}_{\mathrm{ix}}\hat{s}{\tilde{q}}_{\mathrm{ix}}+{\tilde{p}}_{\mathrm{iy}}\hat{s}{\tilde{q}}_{\mathrm{iy}})$

(4), estimate that side-play amount

is according to following formula:

$\hat{t}=\stackrel{\&OverBar;}{q}-\hat{s}\hat{R}\stackrel{\&OverBar;}{p}$

Wherein the estimated value of rotation matrix

can obtain according to following formula:

$\hat{R}=\left[\begin{array}{cc}\cos \left(\widehat{\mathrm{\&theta;}}\right)& -\sin \left(\widehat{\mathrm{\&theta;}}\right)\\ \sin \left(\widehat{\mathrm{\&theta;}}\right)& \cos \left(\widehat{\mathrm{\&theta;}}\right)\end{array}\right]$

(5) calculate square error e:

$e=\sqrt{\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{\left|\right|q_i-(\hat{s}\hat{R}{p}_i+\hat{t})\left|\right|}^2}$

Step 4, the overall situation are handled and decision-making: the pose parametric solution to the 3rd layer of feasible solution space carries out cluster; To comprise the maximum class of pose parametric solution as correct matching relationship; And then utilize the pose algorithm for estimating in the step 303 to calculate the pose parameter, proofread and correct the error of inertial navigation system as the Matching Location result.

Step 401, to each pose parametric solution, set up a class, and calculate with other all pose parametric solutions between difference, if angle difference, position difference and yardstick difference are distinguished all less than predetermined threshold value D ₆, D ₇, D ₈, then with in this pose parametric solution type of depositing in.

Suppose that the pose parametric solution that obtains according to i group point correspondence is v _i=(θ _i, t _i, s _i) (i=1,2 ... M), note is a j group pose parametric solution when pre-treatment, and sets up j group pose parameter class; Other all pose parametric solutions and j group pose parametric solution are compared; With the i group is example, if following formula is set up, then i group pose parametric solution is deposited in the j group pose parameter class:

|θ _i-θ _j|<D ₆,||t _i-t _j||<D ₇,|s _i-s _j|<D ₈

Step 402, find out the class of pose parametric solution most number; And find out the point correspondence of such all pose parametric solution representatives; According to all corresponding point; Utilize the pose algorithm for estimating of the anti-change of scale in the step 303 to calculate the pose parameter once more, and as the output of final matching positioning result, in order to proofread and correct the error of inertial navigation system.

The present invention compared with prior art has following characteristics:

(1) there are problems such as data volume is big, efficient is low to existing aviation with grating image coupling air navigation aid; The present invention adopts map vector as the matched data source; Avoid the storage of mass data, improved the extraction efficiency of data and the time efficiency of matching algorithm.

(2) be directed against local feature and the inconsistent problem of global characteristics that has the wire key element when adopting normalization distance or described function as the matching characteristic amount in the existing vector graphics matching algorithm; The present invention adopts the angle of broken line as the matching characteristic amount; The local angle of wire key element is identical with overall angle; And broken line angle characteristic has unchangeability for translation, rotation, yardstick, and characteristic is obvious, and matching effect is better.

(3) the present invention is based on the thought of handling by different level, reduce the size in feasible solution space successively according to distance restraint condition, order constrained condition and error constraint condition, guaranteed the rapidity and the reliability of matching algorithm.

For the performance of the map vector coupling air navigation aid of estimating the linear target that the present invention proposes, carried out l-G simulation test.In the verification of correctness test, concrete test condition is following:

(1) do not consider picture noise and image vector error;

(2) database parameter: 116.05 °～116.60 ° of longitude scopes, 40.25 °～40.80 ° of latitude scope (being the scope of base vector figure);

(3) imageing sensor parameter: highly be that the ground scope that imageing sensor can collect is: 0.04 ° of longitudinal, 0.04 ° in latitude direction (being the size of template vector figure) under 0 ° the situation for 4000m, course angle.

Under the situation of diverse geographic location, different course angle, differing heights, design three groups of tests respectively, corresponding pose parameter is as shown in table 1.

The preset pose parameter of table 1 verification of correctness test

Test findings is as shown in Figure 5, and the big figure in left side representes vector reference map to be searched, and the little figure A on right side, B, C difference analog image sensor acquisition image are through the result behind the vector quantization.According to final matching results template vector figure is transformed among the base vector figure, like the part that comprises in the square frame among the big figure in left side.As can beappreciated from fig. 5, under the situation of not considering error, three width of cloth template vector figure are the ability correct match all, has verified algorithm validity.

On the computing machine of Pentium (R) 4 CPU 3.00GHz processors, 1GB internal memory, based on the MATLABR2007b programmed environment, the reference diagram to 4 groups of different sizes carries out emulation respectively under the situation of diverse location, the anglec of rotation and zoom factor.Guaranteeing under the correct situation of coupling, the elapsed time of record and statistics map vector matching algorithm, as shown in table 2.

The real-time performance testing result of table 2 algorithm

Can find out that from table 2 this algorithm has good real-time performance.Along with reference diagram diminishes gradually, the feasible solution space that search for and compare also diminishes with regard to corresponding, and matching speed is further accelerated.That is to say that if the reference position error that other navigational system such as INS provide is more little, the real-time performance of map vector coupling navigational system is also just good more.

Consider picture noise and vector quantization error, further the reliability of analytical algorithm has designed reliability compliance test.The grating image size of supposing collection is 2000 * 2000pixels; With height 4000m as benchmark; When imageing sensor is horizontal; Ingestible ground scene scope is 0.04 ° * 0.04 °, and promptly the corresponding ground bin of camera pixel unit is 0.00002 ° (0.072 rad, about 2.2m).And hypothesis image vector error is in the unit picture element length range, therefore in real time among the figure error of coordinate (longitudinal is identical with the latitude direction) of each end points of vector line segment can to select standard deviation for use be 0.00002 ° white noise.The employing size is 0.45 ° * 0.45 ° a reference diagram in the l-G simulation test, selects the pose parameter in the table 1 for use, carries out test of many times and can find out, exists under the situation of error at real-time polar plot, and this algorithm can correctly be located.

Through 100 l-G simulation tests, the position and attitude error after the coupling such as Fig. 7 and shown in Figure 8 can find out, 100 times anglec of rotation error is all less than 0.2 °, and longitudinal and latitudinal site error are all less than 0.18 rad (about 5.4m).Statistics is as shown in table 3, can find out, the standard deviation of site error is slightly less than ground bin size, and the standard deviation of angular error is all less than 0.06 °, and map vector coupling navigational system can obtain higher course precision and bearing accuracy.

The error statistics result of table 3 test of many times

Above embodiment is merely explanation technological thought of the present invention, can not limit protection scope of the present invention with this, every technological thought that proposes according to the present invention, and any change of on the technical scheme basis, being done all falls within the protection domain of the present invention.

Claims (8)

1. an aviation is characterized in that comprising the steps: with the map vector coupling air navigation aid of linear target

(1) judges whether to start the navigation by map-matching system,, then prepare the base vector figure and the template vector figure of map match if start;

(2) template vector figure and base vector figure is unified to same vector accuracy rank, and the angle characteristic of extraction template vector figure and base vector figure;

(3) based on the template vector figure of step (2) acquisition and the angle characteristic of base vector figure; Utilize distance restraint condition, order constrained condition and three constraintss of error constraints progressively to limit the size in feasible solution space successively, finally obtain the 3rd layer of feasible solution space;

(4) the pose parametric solution to the 3rd layer of feasible solution space carries out cluster; To comprise the maximum class of pose parametric solution as correct matching relationship; And then utilize the pose algorithm for estimating to calculate the pose parameter, proofread and correct the error of inertial navigation system as the Matching Location result.

2. a kind of aviation as claimed in claim 1 is with the map vector coupling air navigation aid of linear target, and it is characterized in that: the particular content of said step (1) is:

Step 101, judge whether to get into the navigation by map-matching zone, if not, then do not start the navigation by map-matching system based on the inertial navigation system outgoing position; If, then start the navigation by map-matching system, promptly allow aircraft keep horizontal attitude, and utilize airborne imageing sensor to gather ground image, get into step 102;

Step 102, be written near the map vector data storehouse the inertial navigation system outgoing position, as the base vector figure of map match based on the wire key element;

Step 103, to the linear target of gathering in real time on the ground image, obtain real-time polar plot through vector technology based on the wire key element, it is the image coordinate system of unit in the image upper left corner, with the pixel that the coordinate system of this real-time polar plot adopts initial point;

Step 104, with the coordinate transform of real-time polar plot under the geographic coordinate yardstick, as the template vector figure of map match.

3. a kind of aviation as claimed in claim 1 is with the map vector coupling air navigation aid of linear target, and it is characterized in that: the particular content of said step (2) is:

Step 201, employing Douglas-Peucker method are compressed template vector figure and base vector figure, in compression process, use identical distance threshold value D ₁Thereby, template vector figure and base vector figure is unified under same vector accuracy rank;

Step 202, compression obtains to step 201 respectively real-time polar plot and base vector figure, all broken lines among the sweep vector figure, and calculate corresponding broken line angle sequence.

4. a kind of aviation as claimed in claim 1 is with the map vector coupling air navigation aid of linear target, and it is characterized in that: the particular content of said step (3) is:

Step 301, to the angle sequence of each bar broken line among the template vector figure, calculate its with base vector figure on unidirectional Hausdorff distance between all broken line angle sequences, keep on the base vector figure unidirectional Hausdorff apart from less than predetermined threshold value D ₂All broken lines, as ground floor feasible solution space;

Step 302, in the ground floor feasible solution space that step 301 obtains; Reject the broken line that does not satisfy condition in proper order according to the broken line angle; To the broken line that satisfies condition, find out possible point correspondence between template vector figure and the base vector figure, and then set up second layer feasible solution space;

Step 303, for all possible point correspondence in the second layer feasible solution space; Utilize the position and orientation estimation method of anti-change of scale to find the solution rotation angle, side-play amount and scale factor; And after utilizing the rotation angle obtain and side-play amount that template vector figure is carried out the pose conversion; Compare and find the solution the square mean error amount of being had a few with base vector figure, with square mean error amount greater than predetermined threshold value D ₅Point correspondence from second layer feasible solution space, reject away, thereby set up the 3rd layer of feasible solution space.

5. a kind of aviation as claimed in claim 4 is with the map vector coupling air navigation aid of linear target, and it is characterized in that: the particular content of said step 301 is: the angle sequence of certain broken line is A=[α on the note template vector figure ₁, α ₂..., α _n], certain broken line angle sequence does on the base vector figure

K representes the numbering of this broken line on the base vector figure, then unidirectional Hausdorff distance h (A, B ^k) computing formula following:

$h(A,B^k)=\underset{{\mathrm{\&alpha;}}_i\&Element;A}{\max }\underset{{{\mathrm{\&beta;}}_j}^k\&Element;B^k}{\min }|{\mathrm{\&alpha;}}_i-{{\mathrm{\&beta;}}_j}^k|$

All angles in the following formula reflection sequence A are to sequence B ^kMinimal difference, as A and B ^kUnidirectional Hausdorff distance h (A, B ^k) greater than preset predetermined threshold value D ₂The time, judge B ^kThe broken line that corresponding broken line is corresponding with A does not also match.

6. a kind of aviation as claimed in claim 4 is with the map vector coupling air navigation aid of linear target; It is characterized in that: the particular content of said step 302 is: in the ground floor feasible solution space that certain broken line is corresponding in template vector figure, set up and the identical to be selected corresponding broken line of template vector figure broken line number of endpoint as starting point with each end points on the base vector figure bar broken line respectively; Then, this broken line of template vector figure each angle with base vector figure corresponding broken line to be selected is compared, the note difference is at threshold value D ₃With interior angle number is N _S, total angle number is N, if ratio N _S/ N is greater than predetermined threshold value D ₄, think that then the corresponding broken line of this base vector figure satisfies order constrained condition, and write down this group point correspondence in second time feasible solution space.

7. a kind of aviation as claimed in claim 4 is with the map vector coupling air navigation aid of linear target; It is characterized in that: the particular content of said step 303 is: suppose that in second layer feasible solution space, a certain group of point correspondence is: the coordinate of template vector figure point set P is p _i=[p _Ix, p _Iy] ^T(i=1,2 ..., n), the coordinate of corresponding base vector figure point set Q is q _i=[q _Ix, q _Iy] ^T, the coordinate transform relation between note template vector figure and the base vector figure is q=sRp+t, and wherein, t is a side-play amount, and s is a scale factor, and R is a rotation matrix, the detailed process of the position and orientation estimation method of anti-change of scale is following:

(1) according to following formula, the center point coordinate that calculates point set P and point set Q is:

$\stackrel{\&OverBar;}{p}=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{p}_i,\stackrel{\&OverBar;}{q}=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{q}_i$

(2), estimate that scale factor

is according to following formula:

$\hat{s}=\sqrt{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{\left|\right|q_i-\stackrel{\&OverBar;}{q}\left|\right|}^2/\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{\left|\right|p_i-\stackrel{\&OverBar;}{p}\left|\right|}^2}$

(3), estimate that the anglec of rotation

is according to following formula:

$a=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}({\tilde{p}}_{\mathrm{ix}}\hat{s}{\tilde{q}}_{\mathrm{iy}}-{\tilde{p}}_{\mathrm{iy}}\hat{s}{\tilde{q}}_{\mathrm{ix}}),b=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}({\tilde{p}}_{\mathrm{ix}}\hat{s}{\tilde{q}}_{\mathrm{ix}}+{\tilde{p}}_{\mathrm{iy}}\hat{s}{\tilde{q}}_{\mathrm{iy}})$

(4), estimate that side-play amount

is according to following formula:

$\hat{t}=\stackrel{\&OverBar;}{q}-\hat{s}\hat{R}\stackrel{\&OverBar;}{p}$

Wherein the estimated value of rotation matrix

can obtain according to following formula:

$\hat{R}=\left[\begin{array}{cc}\cos \left(\widehat{\mathrm{\&theta;}}\right)& -\sin \left(\widehat{\mathrm{\&theta;}}\right)\\ \sin \left(\widehat{\mathrm{\&theta;}}\right)& \cos \left(\widehat{\mathrm{\&theta;}}\right)\end{array}\right]$

(5) calculate square error e:

$e=\sqrt{\frac{1}{n}\stackrel{n}{\underset{i=1}{\mathrm{\&Sigma;}}}{\left|\right|q_i-(\hat{s}\hat{R}{p}_i+\hat{t})\left|\right|}^2}.$

8. a kind of aviation as claimed in claim 1 is with the map vector coupling air navigation aid of linear target, and it is characterized in that: the particular content of said step (4) is:

Step 401, to each pose parametric solution, set up a class, and calculate with other all pose parametric solutions between difference, if angle difference, position difference and yardstick difference are distinguished all less than predetermined threshold value D ₆, D ₇, D ₈, then with in this pose parametric solution type of depositing in;

Step 402, find out the class of pose parametric solution most number; And find out the point correspondence of such all pose parametric solution representatives; According to all corresponding point; Utilize the pose algorithm for estimating of anti-change of scale to calculate the pose parameter, and as the output of final matching positioning result, in order to proofread and correct the error of inertial navigation system.

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