CN117053797A - Atmospheric polarization navigation method based on multi-view vision - Google Patents
Atmospheric polarization navigation method based on multi-view vision Download PDFInfo
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Abstract
The invention relates to an atmospheric polarization navigation method based on multi-view vision, and belongs to the field of polarized light navigation. The method comprises the following steps: s1: three gray images with polarization angles of 0 degree, 45 degrees and 90 degrees are obtained by using a polarization acquisition device, and DOP and AOP of the sky in the current state are obtained; s2: respectively extracting and processing the features of the DOP and the AOP to obtain pole position information of the DOP and an AOP feature point set; s3: inputting the three gray images into a convolutional neural network, judging the current weather, and selecting an optimal solution according to a judgment result; the solar meridian position is obtained by an optimal solution, and then the solar azimuth angle under a carrier coordinate system is obtained; s4: calculating to obtain the solar azimuth angle under the navigation coordinate system at the current moment by using the current year and date and the real-time; s5: and using the solar azimuth angle as an intermediate bridge to obtain the relative relation between the carrier coordinate system and the navigation coordinate system, and finally obtaining the carrier travelling direction.
Description
Technical Field
The invention belongs to the technical field of polarized light navigation, and relates to an atmospheric polarized light navigation method based on multi-view vision.
Background
Navigation is widely applied in a plurality of fields such as emergency rescue, weapon guidance, aircraft ship positioning and the like. The navigation method based on natural characteristics is particularly suitable for navigation in unfamiliar environments with weak/no satellite navigation signals because the navigation method is difficult to be interfered and destroyed by human factors in a large range, has been widely focused in recent years, and has important research significance and military application value.
The method realizes the judgment of carrier course information through the detection and calculation of the atmospheric polarization mode, and is an autonomous navigation method suitable for the unfamiliar environment of weak/no satellite navigation signals. The bionic polarized light navigation is also important content of a navigation method based on natural characteristics, and has strong guiding significance and important application value for autonomous navigation under special conditions.
In 2000, wehner et al first applied the navigation strategy of desert ants to the autonomous navigation system of Sahabor mobile robots, providing a meaningful reference for the research of novel navigation sensors. Thereafter, many students at home and abroad have conducted related researches. In China, the university of company, 2005, university of company, jinkui teaches that the subject group firstly carries out the study of sky polarized light distribution mode and the multichannel point source type bionic polarized navigation angle measurement sensor, and completes the robot experiment of the polarized navigation angle measurement sensor and tests the performance of the polarized navigation angle measurement sensor. In 2014, an integrated point source type micro-nano polarization navigation angle measurement sensor is manufactured based on a nano imprinting process, and indoor precision reaches +/-0.1 degrees for the first time. In 2015, an imaging polarization navigation angle measurement sensor based on a nanoimprint process and using a CMOS image sensor as a substrate is proposed. In 2018, a novel real-time full-polarization imaging detection device is designed and built, and real-time display of target polarization information is achieved.
The bionic polarized light navigation method is still in the research stage. It is a research hotspot in the field of autonomous navigation and positioning, and a plurality of key problems need to be solved. Currently, studies on polarization navigation measurement apparatuses and data processing methods are mainly classified into three types.
The first is the currently mainstream polarized navigation structure. The navigation principle is to solve the course angle by using single-point polarization information. This method requires less information to collect and analyze, but a smaller field of view. Because of the smaller field of view, the amount of information required for collection and analysis is less, and is susceptible to obstructions and intense ambient light, thereby reducing navigation accuracy or causing navigation failure.
The second type is a focal plane polarization sensor array. Compared with the first type of single-point polarization information measurement, the structure of the sensor is closer to a biological compound eye, more accurate azimuth information and anti-interference capability are provided through polarization information in a large field of view, but the measurement structure is accurate and complex at the same time, and measurement errors caused by environmental changes are difficult to solve.
The third type is a polarized imaging camera with a large field of view. The imaging type polarization information detection device is mainly used for carrying out polarization information calculation based on Stokes vectors. Three polarized images with different angles are obtained by using imaging equipment, then the information of the polarization degree and the polarization azimuth angle of a detection target is calculated by using Stokes vectors, and then the information of the carrier heading is obtained by using corresponding polarization information, but the real-time calculation result is easily influenced by climate mutation. Furthermore, in some extreme weather, accuracy can be greatly compromised.
The image type polarization navigation sensor has the advantages of high stability, high robustness and the like. Imaging polarization navigation algorithms are also correspondingly proposed, and most of the algorithms are to acquire the position of the solar meridian by utilizing the symmetry of the atmospheric polarization mode, and then determine the heading information of the carrier. The acquisition of solar meridian is a crucial step in the acquisition of course angle information. Therefore, the solar meridian position information has important significance for researching imaging polarized light navigation. The solar meridian position information acquisition algorithm is high in calculation accuracy and good in robustness, and has important application value.
Disclosure of Invention
In view of the above, the present invention aims to provide an atmospheric polarization navigation method (including an image type polarization navigation acquisition structure and its corresponding imaging type polarization navigation algorithm) based on multi-view, so as to improve the precision of bionic polarized light navigation, reduce the failure rate of navigation, and simplify the structure of the polarization acquisition device.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the atmospheric polarization navigation method based on the multi-view vision specifically comprises the following steps:
s1: three gray images with polarization angles of 0 degree, 45 degrees and 90 degrees are obtained by using a polarization acquisition device, and light intensities in different polarization directions are obtained through gray images, so that a Stokes vector is obtained to obtain a DOP image and an AOP image of the sky in the current state; wherein DOP is polarization degree, and AOP is polarization direction angle;
s2: respectively carrying out Gaussian filtering and feature extraction on the DOP, and clustering the extracted feature points to obtain pole position information of the DOP; extracting the features of the AOP to obtain an AOP feature point set;
s3: inputting three gray images of 0 degree, 45 degrees and 90 degrees into a convolutional neural network, judging the current weather, and selecting an optimal solution according to a judgment result; then, the optimal solution selected by the judgment result is used for solving the solar meridian position, and then the solar azimuth angle under the carrier coordinate system is solved by the solar meridian position;
judging the current weather, and selecting an optimal solution according to a judging result specifically comprises the following steps:
when the weather is judged to be sunny, the AOP feature point set is combined with the pole position information of DOP, and an optimal interval method is used for resolving the optimal interval of the solar meridian, so that the solar azimuth angle under the carrier coordinate system is obtained; when the weather is judged to be cloudy, a clustering center method is used for resolving, namely an AOP characteristic point set is abandoned, and the slope of a straight line formed by two DOP poles is used for resolving;
s4: calculating to obtain the solar azimuth angle under the navigation coordinate system at the current moment by using the current year and date and the real-time;
s5: and using the solar azimuth angle as an intermediate bridge to obtain the relative relation between the carrier coordinate system and the navigation coordinate system, and finally obtaining the carrier travelling direction.
In step S1, the polarization acquisition device includes a USB camera, a polarization analyzer, a linear polarizer, and an electric rotating cradle head; the analyzer comprises a positive 8-sided columnar mounting seat and a polaroid clamping groove;
the USB camera is placed on a base inside the right 8-sided columnar mounting seat and is fixed through four struts; the analyzer is fixed on the electric rotating cradle head; the polarization clamping groove is in clearance fit with the positive 8-sided shape hole on the mounting seat, so that each rotation of the polarization clamping groove is 45 degrees; the linear polaroid is stuck on the polarization clamping groove, and the transmission axis of the polarization analyzer can be changed every time of rotation, so that polarized images of 0 degree, 45 degrees and 90 degrees can be collected simultaneously.
Further, in step S2, the method for extracting the AOP feature points includes: the AOP feature points are defined to satisfy 45-I AOP < +_oc th Point of ≡c th Is any value greater than 0.
Further, in step S2, the method for obtaining pole position information of the DOP includes the steps of:
1) Solar position removal
Knowing that the DOP value of the position of the sun is minimum according to the Rayleigh scattering principle, and removing the minimum area in the DOP by using threshold segmentation:
where(DOP＝min(DOP))：DOP＝nan
wherein nan represents a non-number, not involved in subsequent calculations; and performing Gaussian filtering treatment on the image with the region removed;
2) DOP image feature extraction
Extracting features of the obtained DOP image by using threshold segmentation to extract polarization valleys; defining the feature points as pixel points satisfying the above formula:
wherein θ th For the segmentation threshold, given by dynamic calculation, τ is the correction value; when the number of 1 obtained by segmentation is smaller than 3600, τ=τx1.2, and iterating; jumping out of iteration when the number of the segmented 1 is greater than 3600;
performing kmeans clustering by taking the DOP feature point set as a sample point, wherein the number of clustering centers is set to be 2; definition of clustering center μ 1 、μ 2 Loss function J:
wherein x is i Represents the ith sample, c i Is x i The cluster to which the cluster belongs is selected,representing the center point corresponding to the cluster; after multiple iteration convergence, cluster center mu is obtained 1 、μ 2 ；
The two clustering centers respectively correspond to two poles, and the 2-degree of the two poles is calculated to obtain the distance d between the two poles:
when the distance between the two cluster centers is smaller than the limit value d th Then consider that there is only one pole in the image, take midpoint mu of two clustering centers 0 Is a new pole;
further, in step S3, the optimal interval method specifically includes: solar azimuth angle using angle interval statisticsPerforming final calculation;
calculating the connection between all AOP feature points and the poles by taking the calculated poles as the center in the AOP feature point setThe angle formed by the lines, namely each characteristic point has a corresponding angle value; taking 1 degree as a section, dividing 1-180 degrees into 180 sections to obtain a section set { S } i I=1, 2, …,180}, counting the number of angle values in different intervals to obtain a maximum statistical interval S i Then, calculating the average value of the angles in the interval to obtain the solar azimuth angle of the solar meridian under the carrier coordinate system
Wherein n is the maximum statistical interval S i The number of elements in the matrix.
Further, in step S3, the clustering center method specifically includes: obtaining a clustering center mu of DOP feature points after multiple iteration convergence 1 、μ 2 Obtaining the slope k of the solar meridian under the carrier coordinate system 0 ：
The azimuth angle of the solar meridian under the carrier coordinate system is:
further, in step S3, the solar azimuth angle calculated by the angle interval statistical methodThe value range is [0,180 ]]And actually +.>The value range is [0,360 ]]Therefore, the combination of "the average value of the degree of polarization near the solar meridian is smaller than the average value of the degree of polarization near the inverse solar meridian" isA rule solves the ambiguity problem of the sun azimuth angle; the specific treatment process is as follows:
cutting a square area in the DOP by taking a pole as a center, and translating a carrier coordinate system to enable the center of the carrier coordinate system to coincide with the pole; calculating the average value dop of the polarization degree of 4 quadrants of the square area 1 、dop 2 、dop 3 、dop 4 ；
When (when)When comparing the polarization degree average value of the first quadrant and the third quadrant: if dop 1 ＞dop 3 Then->Otherwise->Remain unchanged; when->And comparing the polarization degree average values of the two quadrants and the four quadrants: if dop 2 ＞dop 4 Then-> Otherwise->Remain unchanged; the disambiguation expression is:
further, in step S4, the calculation is performed to obtain the solar azimuth angle under the navigation coordinate system at the current moment, which specifically includes: establishing a spatial straight line with the geographic north direction as an X axis, the geographic east direction as a Y axis and the vertical line passing over the zenith as a Z axisThe angular coordinate system is used for projecting the three-dimensional space coordinate system onto a two-dimensional plane to obtain a navigation reference coordinate system; azimuth angle of sunThe north is taken as the starting direction, the clockwise direction is taken as the positive angle, and the value range is 0-360 degrees; under the celestial coordinate system, introducing solar angle alpha, solar declination angle delta and true solar time S t And the solar time angle T, and obtaining theoretical positions of the zenith angle and the solar azimuth angle by astronomical related formulas;
the specific calculation process of the sun position is as follows:
1) Calculating a solar angle alpha:
α＝2π(D-D o )/365.24
D o ＝79.6764+0.2422*(year-1985)-floor((year-1985)/4)
wherein D is the product day of the current year, and the observation date is the day of the current year from 1 month and 1 day, year is the current year, and floor is a downward rounding function; d (D) o To correct errors since 1985 due to the flat year;
2) Calculating the solar declination angle delta of the current day:
δ＝0.3723+23.2567sinα+0.1149sin 2α-0.1712sin 3α-0.758cosα+0.3656cos2α+0.0201cos 3α
3) Calculate true solar time S t ：
First calculate the local sun S d ：
S d ＝S o +F o -[120°-(J D +J F /60)]*4/60
Wherein S is o 、F o Beijing time and minute, J, of the observation point D 、J F Longitude and meridian point of observation point; from the angle of day alpha, the time difference E can be calculated t ：
E t ＝0.0028-1.9857sinα+9.9059sin 2α-7.0924cosα-0.6882cos2α
By time difference E t Correcting true solar time S at this time t ：
S t ＝S d +E t /60
4) According to true solar time S t To calculate the solar time angle T:
T＝(S t -12)*15°
5) According to the astronomical related formula, the following relation can be obtained:
wherein delta is the declination angle of the sun, T is the sun hour angle of the observation site, and L is the latitude of the observation site; the solar altitude angle theta can be calculated according to the astronomical formula s Azimuth with the sun
Further, the step S5 specifically includes: the navigation coordinate system takes a ground observation point as an origin O, the geographic north direction as a Y axis and the geographic east direction as an X axis; the carrier coordinate system takes a carrier as an origin O, the opposite direction of the heading is an X axis, and the direction vertical to the heading is a Y axis; coinciding the navigation coordinate system with the origin of the carrier coordinate system, and drawing the carrier coordinate system in the navigation coordinate system by taking the position of the solar meridian in the navigation coordinate system as a reference; is known to beAzimuth angle of solar meridian under carrier coordinate system, < ->For the solar meridian azimuth angle under the navigation coordinate system, the heading angle +.>Consider->Greater than, less than, equal to 180 degrees:
when (when)Above 180 DEG, 360 DEG minus +.>Converting the value range to [0,180 ]]Use +.>Minus->The converted value is the direction of the X axis of the carrier coordinate system, and the running direction of the carrier is opposite to the direction of the X axis, so that the result is converted into [0,360 ] after 180 DEG]Interval, course angle under navigation coordinate system +.>When->When the angle is smaller than 180 DEG, use +.>Add->Adding 180 deg. to obtain->When->Equal to 180 °%>The final heading angle expression after the value range conversion is as follows:
in step S1, an error at a rotation angle of 10 ° is used as a system error of the polarization acquisition device during rotation acquisition, and an 8-order fourier series approximation is performed on an error curve by using a MATLAB curve fitting tool box, so as to obtain an error compensation function f (x) as follows:
f(x)＝27.84-13.05×cos(x×w)-25.4×sin(x×w)-13.96×cos(2×x×w)-8.67×sin(2×x×w)-1.287×Cos(3×x×w)+3.088×sin(3×x×w)-2.463×Cos(4×x×w)+4.925×sin(4×x×w)+3.977×Cos(5×x×w)+1.215×sin(5×x×w)+0.3619×cos(6×x×w)+1.958×sin(6×x×w)
w＝0.01398
wherein x is the rotation angle of the acquisition device, and w is the coefficient of f (x).
The invention has the beneficial effects that: compared with the mainstream technologies such as GPS navigation, geomagnetic navigation and inertial navigation, the method has the advantages that the vehicle only needs to quickly acquire the course angle from the collected polarized images, and does not need to interact with the outside. The method has high concealment and is not affected by accumulated errors.
Compared with the existing method, the method disclosed by the invention uses image type polarization navigation, has a larger visual field, can collect and analyze larger information quantity, and is not easy to be influenced by obstacles and strong ambient light; in the face of different weather conditions, the algorithm provided by the invention can select different resolving methods aiming at sunny and cloudy according to the decision device, so that the navigation precision is improved, and the navigation failure rate is reduced; structurally, the invention has a simple measurement structure and can restrain measurement errors caused by environmental changes. Compared with the prior method, the method has the advantages of high stability, high robustness and the like.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objects and other advantages of the invention may be realized and obtained by means of the instrumentalities and combinations particularly pointed out in the specification.
Drawings
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in the following preferred detail with reference to the accompanying drawings, in which:
FIG. 1 is a schematic diagram of an image type polarized navigation acquisition device;
FIG. 2 is a flowchart of a polarization navigation algorithm;
FIG. 3 is a carrier coordinate system;
FIG. 4 is a DOP image feature point extraction flow chart;
FIG. 5 is a navigation coordinate system;
FIG. 6 is a schematic diagram of a heading angle acquisition method;
FIG. 7 is a schematic diagram of a method of determining heading angle under different conditions;
FIG. 8 is a comparison of algorithm output results with expected results;
fig. 9 is a schematic diagram of an error curve.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the illustrations provided in the following embodiments merely illustrate the basic idea of the present invention by way of illustration, and the following embodiments and features in the embodiments may be combined with each other without conflict.
Wherein the drawings are for illustrative purposes only and are shown in schematic, non-physical, and not intended to limit the invention; for the purpose of better illustrating embodiments of the invention, certain elements of the drawings may be omitted, enlarged or reduced and do not represent the size of the actual product; it will be appreciated by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The same or similar reference numbers in the drawings of embodiments of the invention correspond to the same or similar components; in the description of the present invention, it should be understood that, if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc., that indicate an azimuth or a positional relationship based on the azimuth or the positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but not for indicating or suggesting that the referred device or element must have a specific azimuth, be constructed and operated in a specific azimuth, so that the terms describing the positional relationship in the drawings are merely for exemplary illustration and should not be construed as limiting the present invention, and that the specific meaning of the above terms may be understood by those of ordinary skill in the art according to the specific circumstances.
Example 1:
referring to fig. 1 to 7, the present embodiment provides an image type polarized navigation acquisition device and an image type polarized navigation algorithm corresponding thereto.
1. Hardware structure of image type polarized navigation acquisition device
The hardware equipment mainly comprises: USB camera, electric rotation cradle head, analyzer, linear polarizer, tripod, etc. The used camera has a visual angle of 180 degrees, a focal length of 2.8mm and output resolution of 1920 multiplied by 1080; the minimum rotation angle of the electric cradle head is 1 degree.
The polarization image can be acquired by adding the polarization analyzer in front of the camera lens, and the polarization acquisition device is formed by using the polarization analyzer fixing piece, the usb camera and the linear polarizer in the embodiment. The analyzer comprises a positive 8-sided columnar mounting seat and a polaroid clamping groove. As shown in fig. 1.
The camera can be placed on the base inside the mounting seat and fixed through four struts. The polarization clamping groove is in clearance fit with the positive 8-sided shaped hole on the mounting seat, so that each rotation of the polarization clamping groove is 45 degrees. The linear polaroid is stuck on the polarization clamping groove, and the transmission axis of the polarization analyzer can be changed every time of rotation, so that polarized images of 0 degree, 45 degrees and 90 degrees can be collected simultaneously.
2. Polarization navigation algorithm
The algorithm flow is as follows: the three gray images with the polarization angles of 0 degree, 45 degrees and 90 degrees are obtained by the polarization acquisition device, and the light intensities in different polarization directions can be obtained through the gray images, so that the Stokes vector is solved to obtain a polarization degree image (DOP) and a polarization direction angle image (AOP) of the sky in the current state.
Firstly, carrying out Gaussian filtering and feature extraction on the DOP image, and clustering the extracted feature points to obtain pole position information of the DOP image. And then carrying out feature extraction on the AOP to obtain an AOP feature point set.
Three gray images of 0 degree, 45 degrees and 90 degrees are input into a convolutional neural network, judgment is carried out on the current weather, and an optimal solution is selected according to the judgment result. When the weather is judged to be sunny, combining the feature point set extracted by the AOP with the pole position obtained by the DOP, and calculating the optimal interval of the solar meridian to obtain the solar azimuth angle under the carrier coordinate system; when the weather is judged to be cloudy, discarding the AOP characteristic point set, and calculating by using the slope of a straight line formed by two DOP poles. And solving the solar meridian position by the optimal solution selected by the judgment, and solving the solar azimuth angle under the carrier coordinate system by the solar meridian position.
And on the other hand, calculating to obtain the solar azimuth angle under the navigation coordinate system at the current moment by using the current year and date and real-time, and obtaining the relative relation between the carrier coordinate system and the navigation coordinate system by using the solar azimuth angle as an intermediate bridge, thereby finally obtaining the carrier travelling direction. The overall flow chart of the algorithm process is shown in fig. 2.
The specific principle and detailed implementation flow of the algorithm are as follows.
2.1 image description of polarization modes
The stokes vector model is one of the most common methods described with respect to polarization, and the stokes vector of incident light is expressed as:
wherein,indicating that the polarization direction is +.>The incident light intensity is that of sky, Q is 0 degree polarized light component and U is 45 degree polarized light component. So long as three or more ++are known>The I, Q, U component in the original sky can be obtained from the above equation. Three polarization directions of 0 degree, 45 degrees and 90 degrees are selected to obtain an equation set:
the intensity of light in different polarization directions can be obtained by using the gray level diagram, and after the Stokes vector is obtained, the calculation of the polarization degree image (DOP) and the polarization direction angle image (AOP) is as follows:
the polarization degree DOP characterizes the sky polarization state, and the polarization angle AOP is an included angle between a polarization direction vector of a sky observation point in a carrier coordinate system and a carrier (camera) body axis. According to the principle of the Rayleigh Li Jinsi scattering, the atmospheric polarization mode is symmetrical about the solar meridian passing through the sun and the zenith, the polarization degree is symmetrically distributed about the solar meridian, the polarization degree is maximum at the position of the symmetry axis, the farther the distance from the symmetry axis is, the smaller the polarization degree is, and two polarization degree poles are formed on the symmetry axis by the DOP graph.
2.2 solar azimuth acquisition in Carrier coordinate System
The carrier coordinate system shown in fig. 3 is established by taking the center of gravity of the carrier as an origin O, taking the direction opposite to the carrier heading as an X axis and taking the direction perpendicular to the carrier heading as a Y axis.
The solar azimuth angle under the carrier coordinate system is the deflection angle of the solar meridian under the body coordinate system
The invention can acquire the solar meridian position according to the characteristic that the E vector along the solar meridian direction is perpendicular to the solar meridian.
2.3 specific method for acquiring solar azimuth under carrier coordinate system
2.3.1 AOP feature point extraction
Because the number of the points in which the azimuth angle is precisely coincident with the meridian is very small in the measured data, and the polarization angle information of the meridian area is fully utilized, the AOP characteristic points are defined as meeting 45-I AOP I < th Point of ≡c th Any value greater than 0, in the experiment ≡ th And 43.
2.3.2 clustering-based DOP Pole positioning
1) Solar position removal
The position of the sun can interfere with polarized imaging as shown in fig. 3. The location of the sun can be seen to create a significant error region in the AOP image. Knowing that the DOP value of the position of the sun is minimum according to the Rayleigh scattering principle, and removing the minimum area in the DOP by using threshold segmentation:
where(DOP＝min(DOP))：DOP＝nan (4)
for facilitating the calculation, the actual algorithm is as follows:
where(DOP＝min(DOP))：DOP＝1 (5)
and performing Gaussian filtering processing on the image with the region removed.
2) DOP image feature extraction
And extracting features of the obtained DOP image by using threshold segmentation to extract polarization valleys. Defining the feature point as a pixel point satisfying the formula (4):
wherein θ th Given by dynamic calculation, when the number of 1 obtained by segmentation is smaller than 3600, τ=τx1.2, iterate; and jumping out of iteration when the number of the segmented 1 is greater than 3600. The DOP image feature extraction flowchart is shown in FIG. 4.
And carrying out kmeans clustering by taking the DOP feature point set as a sample point, wherein the number of clustering centers is set to be 2. Definition of clustering center μ 1 、μ 2 Loss function J:
wherein x is i Represents the ith sample, c i Is x i The cluster to which the cluster belongs is selected,representing the center point corresponding to the cluster. After multiple iteration convergence, cluster center mu is obtained 1 、μ 2 。
The two clustering centers respectively correspond to two poles, and the 2-degree of the two poles is calculated to obtain the distance d between the two poles:
when the distance between the two cluster centers is smaller than the limit value d th Then consider that there is only one pole in the image, take midpoint mu of two clustering centers 0 Is a new pole.
2.3.3 optimal decision maker
And training a convolutional neural network to classify weather, and dividing an output result into two conditions of 'clear' and 'cloudy'. Three gray images of 0 degree, 45 degrees and 90 degrees are input into a convolutional neural network, judgment is carried out on the current weather, and an optimal solution is selected according to the judgment result. When the judgment is 'clear', the optimal interval method is used for resolving; when the judgment is 'cloudiness', a clustering center method is used for resolving.
2.3.4 optimal interval method solution
The invention uses angle interval statistics methodAnd performing final calculation. And extracting features of the DOP, clustering to obtain a polarization pole, and thus obtaining the pole position in the AOP image.
And calculating angles formed by connecting all the AOP characteristic points with the poles in the AOP characteristic point set by taking the calculated poles as centers, namely, each characteristic point has a corresponding angle value. Dividing 1-180 DEG into 180 intervals by taking 1 DEG as interval to obtain interval set { S } i I=1, 2, …,180}, counting the number of angle values in different intervals to obtain a maximum statistical interval S i Then, calculating the average value of angles in the interval to obtain the deflection angle of the solar meridian under the body coordinate system
Wherein n is the maximum statistical interval S i The number of elements in the matrix.
2.3.5 Cluster center method solution
Obtaining a clustering center mu of DOP feature points after multiple iteration convergence 1 、μ 2 Obtaining the slope k of the solar meridian under the carrier coordinate system 0 ：
The azimuth angle of the solar meridian under the carrier coordinate system is
2.3.6Processing of ambiguity
Calculated by angular interval statistical methodThe value range is [0,180 ]]And actually +.>The value range is [0,360 ]]It is therefore necessary to solve the ambiguity of the deflection angle. The problem of azimuth angle ambiguity is solved by combining the rule that the average value of the polarization degree near the solar meridian is smaller than that near the inverse solar meridian. The specific treatment process is as follows:
and cutting a square region in the DOP by taking the pole as the center, and translating the carrier coordinate system to enable the center of the carrier coordinate system to coincide with the pole. Calculating the average value dop of the polarization degree of 4 quadrants of the square area 1 、dop 2 、dop 3 、dop 4 。
When (when)When comparing the polarization degree average value of the first quadrant and the third quadrant: if dop 1 ＞dop 3 Then->Otherwise->Is kept unchangedA change; when->And comparing the polarization degree average values of the two quadrants and the four quadrants: if dop 2 ＞dop 4 Then-> Otherwise->Remain unchanged. The disambiguation expression is shown in formula (13).
2.4 solar azimuth acquisition in navigation coordinate System
And establishing a space rectangular coordinate system with the geographic north direction as an X axis, the geographic east direction as a Y axis and the vertical line passing over the zenith as a Z axis, and projecting the three-dimensional space coordinate system onto a two-dimensional plane to obtain a navigation reference coordinate system. As shown in fig. 5.
Azimuth angle of sunThe north is taken as the starting direction, the clockwise direction is taken as the positive angle, and the value range is 0-360 degrees. Under the celestial coordinate system, introducing solar angle alpha, solar declination angle delta and true solar time S t And the solar time angle T, and obtaining the theoretical positions of the zenith angle and the solar azimuth angle by astronomical correlation formulas. The specific calculation process of the sun position is as follows:
1) Calculating a solar angle alpha:
α＝2π(D-D o )/365.24 (14)
D o ＝79.6764+0.2422*(year-1985)-floor((year-1985)/4) (15)
where D is the product day of the year, and the observation date is the day of the year from 1 month and 1 day, year is the current year, floor is a downward rounding function.
2) Calculating the solar declination angle delta of the current day:
δ＝0.3723+23.2567sinα+0.1149sin 2α-0.1712sin 3α-0.758cosα+0.3656cos 2α+0.0201cos 3α (16)
3) Calculate true solar time S t ：
First calculate the local sun S d ：
S d ＝S o +F o -[120°-(J D +J F /60)]*4/60 (17)
Wherein S is o 、F o Beijing time and minute, J, of the observation point D 、J F Is the longitude and the meridian point of the observation point. From the angle of day alpha, the time difference E can be calculated t ：
E t ＝0.0028-1.9857sinα+9.9059sin2α-7.0924cosα-0.6882cos 2α (18)
By time difference E t Correcting true solar time S at this time t ：
S t ＝S d +E t /60 (19)
4) According to true solar time S t To calculate the solar time angle T:
T＝(S t -12)*15° (20)
5) According to the astronomical related formula, the following relation can be obtained:
wherein delta is the declination angle of the sun, T is the sun hour angle of the observation site, and L is the latitude of the observation site. The solar altitude angle theta can be calculated according to the astronomical formula s Azimuth with the sun
2.5 course angle acquisition
The carrier coordinate system and the navigation coordinate system are established in the front, the positions of the solar meridians below the carrier coordinate system and the navigation coordinate system are respectively calculated, and the position change of the solar meridians can be used for realizing the two-dimensional plane heading angle solving by using the solar meridians as an intermediate bridge. The course angle acquisition method is shown in fig. 6.
In fig. 6, the navigation coordinate system uses the ground observation point as an origin O, the geographic north direction as a Y axis, and the geographic east direction as an X axis; the carrier coordinate system takes the carrier as an origin O, the opposite direction of the heading is an X axis, and the direction perpendicular to the heading is a Y axis. And coinciding the navigation coordinate system with the origin of the carrier coordinate system, and drawing the carrier coordinate system in the navigation coordinate system by taking the position of the solar meridian in the navigation coordinate system as a reference. Is known to beIs the azimuth angle of the solar meridian under the carrier coordinate system, < +.>For the solar meridian azimuth angle under the navigation coordinate system, the heading angle +.>Consider->Greater than, less than, and equal to 180, as shown in fig. 7.
When (when)Above 180 DEG, 360 DEG minus +.>Converting the value range to [0,180 ]]Use +.>Minus->The converted value is the direction of the X axis of the carrier coordinate system, and the running direction of the carrier is opposite to the direction of the X axis, so that the result is converted into [0,360 ] after 180 DEG]Interval, course angle under navigation coordinate system +.>When->When the angle is smaller than 180 DEG, use +.>Add->Adding 180 deg. to obtain->When->Equal to 180 °%>The final heading angle expression after the value range conversion is as follows:
2.6 error Compensation function
In order to reduce the effects of systematic errors and structural errors, the present invention uses a fourier series to curve fit the error function of the sensor. The error at the angle of 10 degrees is used as the systematic error of the experimental platform constructed by the invention during rotation acquisition, and the error curve is subjected to 8-order Fourier series approximation by utilizing a curve fitting tool box of MATLAB, so that an error compensation function is obtained as follows:
f(x)＝27.84-13.05×cos(x×w)-25.4×sin(x×w)-13.96×cos(2×x×w)-8.67×sin(2×x×w)-1.287×cos(3×x×w)+3.088×sin(3×x×w)-2.463×cos(4×x×w)+4.925×sin(4×x×w)+3.977×cos(5×x×w)+1.215×sin(5×x×w)+0.3619×cos(6×x×w)+1.958×sin(6×x×w)
w＝0.01398
after error compensation, the maximum absolute error is 8.19 degrees, the minimum absolute error is 0.02 degrees, and the error average value is 0.0164 degrees. The error curve after compensation has smaller fluctuation and up-and-down fluctuation around 0 degrees, and no error is accumulated along with the increase of the rotation angle of the camera. The error compensation function is described as well as better suppressing the systematic errors.
Example 2:
the image type polarized navigation acquisition device (namely, the polarized acquisition device) in the embodiment 1 is fixed on a carrier, data of the polarized acquisition device are transmitted to an upper computer by using wireless communication, a polarized navigation algorithm is operated on the upper computer, and navigation information is fed back in real time. The result of the algorithm output and the expected result are shown in fig. 8.
The processing unit of the polarized image mainly comprises an image processing algorithm module (namely the polarized navigation algorithm of the embodiment 1), signal transmission and display. And for the collected atmospheric polarization image, the navigation angle is calculated through a designed algorithm, the built-in clock can correct the result, and the result is displayed on the display screen.
The navigation information is directly obtained from the atmospheric polarization image, so that the situation that the carrier is automatically navigated due to lack of GPS signals or under special environments (such as the existence of electromagnetic interference and the like) can be effectively avoided, and the method is also a main purpose of the invention. Furthermore, since the navigation angle is directly calculated from the polarized image, the measurement result does not have accumulated errors like the inertial navigation device.
As shown in fig. 9, after the 10 ° angular error is compensated, the maximum absolute error is 8.19 °, the minimum absolute error is 0.02 °, and the error average value is 0.0164. As can be seen from the error curve, the error curve after compensation fluctuates slightly and up and down around 0 degrees, and no error is accumulated along with the increase of the rotation angle of the camera. Illustrating the feasibility of using the navigational orientations of the present invention.
Finally, it is noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the present invention, which is intended to be covered by the claims of the present invention.
Claims (10)
1. The atmospheric polarization navigation method based on the multi-view vision is characterized by comprising the following steps of:
s1: three gray images with polarization angles of 0 degree, 45 degrees and 90 degrees are obtained by using a polarization acquisition device, and light intensities in different polarization directions are obtained through gray images, so that a Stokes vector is obtained to obtain a DOP image and an AOP image of the sky in the current state; wherein DOP is polarization degree, and AOP is polarization direction angle;
s2: carrying out Gaussian filtering and feature extraction on the DOP, and clustering the extracted feature points to obtain pole position information of the DOP; extracting the features of the AOP to obtain an AOP feature point set;
s3: inputting three gray images of 0 degree, 45 degrees and 90 degrees into a convolutional neural network, judging the current weather, and selecting an optimal solution according to a judgment result; then, the optimal solution selected by the judgment result is used for solving the solar meridian position, and then the solar azimuth angle under the carrier coordinate system is solved by the solar meridian position;
judging the current weather, and selecting an optimal solution according to a judging result specifically comprises the following steps:
when the weather is judged to be sunny, the AOP feature point set is combined with the pole position information of DOP, and an optimal interval method is used for resolving the optimal interval of the solar meridian, so that the solar azimuth angle under the carrier coordinate system is obtained; when the weather is judged to be cloudy, a clustering center method is used for resolving, namely an AOP characteristic point set is abandoned, and the slope of a straight line formed by two DOP poles is used for resolving;
s4: calculating to obtain the solar azimuth angle under the navigation coordinate system at the current moment by using the current year and date and the real-time;
s5: and using the solar azimuth angle as an intermediate bridge to obtain the relative relation between the carrier coordinate system and the navigation coordinate system, and finally obtaining the carrier travelling direction.
2. The atmospheric polarization navigation method according to claim 1, wherein in step S1, the polarization acquisition device comprises a USB camera, a polarization analyzer, a linear polarizer, and an electric rotating cradle head; the analyzer comprises a positive 8-sided columnar mounting seat and a polaroid clamping groove;
the USB camera is placed on a base inside the right 8-sided columnar mounting seat and is fixed through four struts; the analyzer is fixed on the electric rotating cradle head; the polarization clamping groove is in clearance fit with the positive 8-sided shape hole on the mounting seat, so that each rotation of the polarization clamping groove is 45 degrees; the linear polaroid is stuck on the polarization clamping groove, and the transmission axis of the polarization analyzer can be changed every time of rotation, so that polarized images of 0 degree, 45 degrees and 90 degrees can be collected simultaneously.
3. The atmospheric polarization navigation method according to claim 1, wherein in step S2, the method for extracting the AOP feature point is as follows: defining AOP feature points to satisfy 45- |AOP|<∝ th Point of ≡c th Is any value greater than 0.
4. The atmospheric polarization navigation method according to claim 1, wherein in step S2, the method step of obtaining pole position information of the DOP is:
1) Solar position removal
Knowing that the DOP value of the position of the sun is minimum according to the Rayleigh scattering principle, and removing the minimum area in the DOP by using threshold segmentation:
where(DOP＝min(DOP))：DOP＝nan
wherein nan represents a non-number, not involved in subsequent calculations; and performing Gaussian filtering treatment on the image with the region removed;
2) DOP image feature extraction
Extracting features of the obtained DOP image by using threshold segmentation to extract polarization valleys; defining the feature points as pixel points satisfying the above formula:
wherein θ th For the segmentation threshold, given by dynamic calculation, τ is the correction value; when the number of 1 obtained by segmentation is smaller than 3600, τ=τx1.2, and iterating; jumping out of iteration when the number of the segmented 1 is greater than 3600;
performing kmeans clustering by taking the DOP feature point set as a sample point, wherein the number of clustering centers is set to be 2; definition of clustering center μ 1 、μ 2 Loss function J:
wherein x is i Represents the ith sample, c i Is x i The cluster to which the cluster belongs is selected,representing the center point corresponding to the cluster; after multiple iteration convergence, cluster center mu is obtained 1 、μ 2 ；
The two clustering centers respectively correspond to two poles, and the 2-degree of the two poles is calculated to obtain the distance d between the two poles:
when the distance between the two cluster centers is smaller than the limitValue d th Then consider that there is only one pole in the image, take midpoint mu of two clustering centers 0 Is a new pole;
5. the atmospheric polarization navigation method according to claim 4, wherein in step S3, the optimal interval method specifically comprises: solar azimuth angle using angle interval statisticsPerforming final calculation;
calculating angles formed by connecting all the AOP characteristic points with the poles in the AOP characteristic point set by taking the calculated poles as centers, namely, each characteristic point has a corresponding angle value; taking 1 degree as a section, dividing 1-180 degrees into 180 sections to obtain a section set { S } i I=1, 2, …,180}, counting the number of angle values in different intervals to obtain a maximum statistical interval S i Then, calculating the average value of the angles in the interval to obtain the solar azimuth angle of the solar meridian under the carrier coordinate system
Wherein n is the maximum statistical interval S i The number of elements in the matrix.
6. The atmospheric polarization navigation method according to claim 4, wherein in step S3, the clustering center method specifically comprises: obtaining a clustering center mu of DOP feature points after multiple iteration convergence 1 、μ 2 Obtaining the slope k of the solar meridian under the carrier coordinate system 0 ：
The azimuth angle of the solar meridian under the carrier coordinate system is:
7. the atmospheric polarization navigation method according to claim 5 or 6, wherein in step S3, the solar azimuth angle is calculated by angle interval statisticsThe value range is [0,180 ]]And actually +.>The value range is [0,360 ]]Therefore, the ambiguity problem of the solar azimuth angle is solved by combining the rule that the average value of the polarization degree near the solar meridian is smaller than that near the inverse solar meridian; the specific treatment process is as follows:
cutting a square area in the DOP by taking a pole as a center, and translating a carrier coordinate system to enable the center of the carrier coordinate system to coincide with the pole; calculating the average value dop of the polarization degree of 4 quadrants of the square area 1 、dop 2 、dop 3 、dop 4 ；
When (when)When comparing the polarization degree average value of the first quadrant and the third quadrant: if dop 1 >dop 3 Then->Otherwise->Remain unchanged; when->And comparing the polarization degree average values of the two quadrants and the four quadrants: if dop 2 >dop 4 Then-> Otherwise->Remain unchanged; the disambiguation expression is:
8. the atmospheric polarization navigation method according to claim 1, wherein in step S4, the solar azimuth angle under the navigation coordinate system at the current moment is calculated, and specifically comprises: establishing a space rectangular coordinate system with the geographic north direction as an X axis, the geographic east direction as a Y axis and a vertical line passing over the zenith as a Z axis, and projecting the three-dimensional space coordinate system onto a two-dimensional plane to obtain a navigation reference coordinate system; azimuth angle of sunThe north is taken as the starting direction, the clockwise direction is taken as the positive angle, and the value range is 0-360 degrees; under the celestial coordinate system, introducing solar angle alpha, solar declination angle delta and true solar time S t And the solar time angle T, and obtaining theoretical positions of the zenith angle and the solar azimuth angle by astronomical related formulas;
the specific calculation process of the sun position is as follows:
1) Calculating a solar angle alpha:
α＝2π(D-D o )/365.24
D o ＝79.6764+0.2422*(year-1985)-floor((year-1985)/4)
wherein D is the product day of the current year, namely the day of observation from 1 month and 1 day of the current year, year is the current year, and floor is a downward rounding function; d (D) o To correct errors since 1985 due to the flat year;
2) Calculating the solar declination angle delta of the current day:
δ＝0.3723+23.2567sinα+0.1149sin2α-0.1712sin3α-0.758cosα+0.3656cos2α+0.0201cos3α
3) Calculate true solar time S t ：
First calculate the local sun S d ：
S d ＝S o +F o -[120°-(J D +J F /60)]*4/60
Wherein S is o 、F o Beijing time and minute, J, of the observation point D 、J F Longitude and meridian point of observation point; calculating the time difference E from the sun angle alpha t ：
E t ＝0.0028-1.9857sinα+9.9059sin2α-7.0924cosα-0.6882cos2α
By time difference E t Correcting true solar time S at this time t ：
S t ＝S d +E t /60
4) According to true solar time S t To calculate the solar time angle T:
T＝(S t -12)*15°
5) According to astronomical related formulas, the following relational expression is obtained:
wherein delta is the declination angle of the sunT is the sun time angle of observation area, L is the latitude of the observation point; the solar altitude angle theta can be calculated according to the astronomical formula s Azimuth with the sun
9. The atmospheric polarization navigation method according to claim 1, wherein step S5 specifically comprises: the navigation coordinate system takes a ground observation point as an origin O, the geographic north direction as a Y axis and the geographic east direction as an X axis; the carrier coordinate system takes a carrier as an origin O, the opposite direction of the heading is an X axis, and the direction vertical to the heading is a Y axis; coinciding the navigation coordinate system with the origin of the carrier coordinate system, and drawing the carrier coordinate system in the navigation coordinate system by taking the position of the solar meridian in the navigation coordinate system as a reference; is known to beAzimuth angle of solar meridian under carrier coordinate system, < ->For the solar meridian azimuth angle in the navigation coordinate system, the heading angle +.>Consider->Greater than, less than, equal to 180 degrees:
when (when)Above 180 DEG, 360 DEG minus +.>Conversion of the value range to [0,180 ]]Use +.>Minus->The converted value is the direction of the X axis of the carrier coordinate system, and the running direction of the carrier is opposite to the direction of the X axis, so that the result is converted into [0,360 ] after 180 DEG]Interval, course angle under navigation coordinate system +.>When->When the angle is smaller than 180 DEG, use +.>Add->180 degrees is added to obtainWhen->Equal to 180 °%>The final heading angle expression after the value range conversion is as follows:
10. the atmospheric polarization navigation method according to claim 1 or 2, wherein in step S1, an error at a 10 ° rotation angle is used as a systematic error of the polarization acquisition device during rotation acquisition, and a MATLAB curve fitting tool box is used to perform 8-order fourier series approximation on the error curve, so as to obtain an error compensation function f (x) as follows:
f(x)＝27.84-13.05×cos(x×w)-25.4×sin(x×w)-13.96×cos(2×x×w)-8.67×sin(2×x×w)-1.287×cos(3×x×w)+3.088×sin(3×x×w)-2.463×cos(4×x×w)+4.925×sin(4×x×w)+3.977×cos(5×x×w)+1.215×sin(5×x×w)+0.3619×cos(6×x×w)+1.958×sin(6×x×w)
w＝0.01398
wherein x is the rotation angle of the acquisition device, and w is the coefficient of f (x).
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| CN117928565B (en) * | 2024-03-19 | 2024-05-31 | 中北大学 | Polarization navigation orientation method under complex shielding environment |
| CN117968669A (en) * | 2024-04-01 | 2024-05-03 | 北京航空航天大学 | Course determination method based on sky significant light intensity region at alternate time of day and month |
| CN117968669B (en) * | 2024-04-01 | 2024-06-11 | 北京航空航天大学 | Course determination method based on sky significant light intensity region at alternate time of day and month |
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