Polarization vector non-orthogonal error identification method

Abstract

The invention discloses a polarization vector non-orthogonal error identification method. The method comprises the following steps: acquiring an atmospheric polarization image; constructing a polarization vector non-orthogonal error angle model; and substituting the prior information and the observation information of each observation point in the atmospheric polarization image into the polarization vector non-orthogonal error angle model, and estimating to obtain a non-orthogonal error angle of each observation point in the atmospheric polarization image. The method is applied to the field of polarized light navigation, polarization vector non-orthogonal errors caused by multiple scattering in cloudy weather are quantitatively introduced into a model construction process, and the polarization vector non-orthogonal errors are estimated based on prior information and observation information of observation points according to the characteristic that a non-orthogonal error angle changes slowly in a short time. Therefore, the influence of the non-orthogonal error angle on the orientation result can be better compensated, and the method can be effectively applied to a polarized light orientation method in cloudy weather.

Description

Technical Field

[0001] The invention relates to the technical field of polarized light navigation, and in particular to a method for identifying non-orthogonal errors of polarization vectors. Background Art

[0002] Accurate positioning information is the basis for autonomous navigation of long-flight unmanned platforms. However, in the case of satellite stoppage or complex electromagnetic interference environment, the existing inertial navigation has error accumulation and geomagnetic navigation is easily interfered, which cannot meet the requirements of high-precision navigation of unmanned platforms.

[0003] During the propagation process, sunlight is absorbed and scattered by atmospheric particles to produce polarized light. A large amount of polarized light converges in the sky to form an atmospheric polarization pattern with a certain distribution pattern. The atmospheric polarization pattern contains directional information. Based on the geometric property that the E vector of polarized light is perpendicular to the scattering surface in the Rayleigh scattering model, the carrier azimuth can be estimated by measuring the atmospheric polarization information, which is the conventional orientation method based on the orthogonality of the polarization vector. Although the orientation method based on the orthogonality of the polarization vector can effectively improve the orientation accuracy in sunny days with obstructions, few clouds and cloudy weather, it is not effective for cloudy weather. The reason is that the polarization degree is not clearly distinguished in cloudy weather. Even if there are a few Rayleigh points, it is difficult to screen them. The E vector of the non-Rayleigh point is no longer perpendicular to the scattering surface, but there is an angle between it and the E vector of the Rayleigh point, which is called the non-orthogonal error angle of the polarization vector. In addition, the non-orthogonal error angle of the non-Rayleigh point is large in cloudy weather. If the orientation method based on the orthogonality of the polarization vector continues to be used, a large orientation error will be introduced. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides a method for identifying non-orthogonal errors of polarization vectors, which can realize the estimation of non-orthogonal error angles of polarization vectors and can be effectively applied to polarized light orientation methods under cloudy weather.

[0005] To achieve the above object, the present invention provides a method for identifying polarization vector non-orthogonality errors, comprising the following steps:

[0006] Step 1, obtaining an atmospheric polarization image;

[0007] Step 2, constructing a polarization vector non-orthogonal error angle model, including:

[0008] Decompose the E vector e of the observation point into the coordinate system composed of the sun direction vector s axis, the observation direction vector v axis and the orthogonal axes composed of v×s:

[0009] e=r1·s+r2·v+r3·v×s

[0010] Among them, r1=sinη / / sinτ, r2=-sinη / / tanτ, r3=-cosη / / sinτ are the modulus lengths of the E vector e of the observation point on the three axes respectively, η is the non-orthogonal error angle of the observation point, and τ is the scattering angle;

[0011] Project the E vector e of the observation point to the optical compass coordinate system:

[0012] e c =r1·s c +r2·v c +r3·v c ×s c

[0013] Among them, e c is the projection of the E vector e of the observation point on the optical compass coordinate system, s c is the projection of the sun direction vector on the optical compass coordinate system, v c is the projection of the observation direction vector on the optical compass coordinate system;

[0014] Let f(η) = r1·s c +r2·v c +r3·v c ×s c -e c As the objective function, the polarization vector non-orthogonal error angle model is

[0015] Step 3: Substitute the prior information and the observation information of each observation point in the atmospheric polarization image into the polarization vector non-orthogonal error angle model to estimate the non-orthogonal error angle of each observation point in the atmospheric polarization image.

[0016] In one embodiment, in step 1, the scattering angle is specifically:

[0017]

[0018] Where T is the transpose of the matrix.

[0019] In one embodiment, the projection of the E vector e of the observation point on the optical compass coordinate system is specifically:

[0020]

[0021] is the transformation matrix from the observation point coordinate system to the optical compass coordinate system, expressed as:

[0022]

[0023] Among them, α vis the azimuth of the observation point in the optical compass coordinate system, γ v is the zenith angle of the observation point in the optical compass coordinate system, α v , γ v That is the observation information of the observation point;

[0024] e v is the projection of the E vector e of the observation point on the observation point coordinate system, expressed as:

[0025]

[0026] Where φ is the polarization angle of the observation point.

[0027] In one embodiment, the polarization angle φ of the observation point is calculated using the Stokes vector method, specifically:

[0028] The Stokes vector S0 contains four parameters S0 = [S1 S2 S3 S4], where S1 represents the total light intensity, S2 is the light intensity difference between 0° and 90°, S3 is the light intensity difference between 45° and 135°, and S4 is the circular polarization component. The intensity of polarized light after passing through the polarizer is:

[0029]

[0030] Where θ1 is the polarization angle, is the angle between the sensor polarization direction and the system optical axis;

[0031] Omitting the S4 component, the simplified Stokes intensity equation is:

[0032]

[0033] When the polarization angle θ1 is 0°, 45°, and 90° respectively, the Stokes parameter of each pixel on the image is:

[0034]

[0035] Without considering circularly polarized light, the polarization angle of each pixel is φ = (1 / 2) arctan (S3 / S2).

[0036] In one embodiment, the projection of the sun direction vector on the optical compass coordinate system is specifically:

[0037]

[0038] is the transformation matrix from the carrier coordinate system to the optical compass coordinate system, expressed as:

[0039]

[0040] is the transformation matrix from the navigation coordinate system to the optical compass coordinate system, expressed as:

[0041]

[0042] Among them, r0, θ0, Ψ0 are respectively provided by other sensors for the carrier roll angle, pitch angle and heading angle, which are the prior information;

[0043] s n is the sun direction vector in the navigation coordinate system, expressed as:

[0044]

[0045] Where T is the transpose of the matrix, is the azimuth of the sun direction vector in the navigation coordinate system, is the altitude angle of the sun direction vector in the navigation coordinate system, That is the prior information.

[0046] In one embodiment, the projection of the observation direction vector on the optical compass coordinate system is specifically:

[0047] v c =[siny v ·cosα v sinγ v ·sinα v -cosγ v ] T

[0048] Among them, T is the transpose of the matrix, α v is the azimuth of the observation point in the optical compass coordinate system, γ v is the zenith angle of the observation point in the optical compass coordinate system, α v , γ v That is the observation information of the observation point.

[0049] In one embodiment, in step 3, the polarization vector non-orthogonal error angle model is solved based on the interior point method.

[0050] Compared with the prior art, the present invention has the following beneficial technical effects:

[0051] The present invention quantitatively introduces the non-orthogonal error of polarization vector caused by multiple scattering under cloudy weather into the model construction process, and estimates the non-orthogonal error of polarization vector based on prior information and observation information of observation points according to the characteristic that the non-orthogonal error angle changes slowly in a short period of time, so as to better compensate for the influence of the non-orthogonal error angle on the orientation result. The present invention can be effectively applied to the polarized light orientation method under cloudy weather. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0053] Figure 1 Flow chart of a method for identifying polarization vector non-orthogonality errors in an embodiment of the present invention;

[0054] Figure 2 Schematic diagram of the scattering process of sunlight in the sky in an embodiment of the present invention;

[0055] Figure 3 Schematic diagram of non-orthogonal error angle of polarization vectors in an embodiment of the present invention;

[0056] Figure 4 Schematic diagram of the first orthogonal relationship of vibration vectors in an embodiment of the present invention;

[0057] Figure 5 Schematic diagram of the second orthogonal relationship of vibration vectors in an embodiment of the present invention.

[0058] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0061] In addition, the technical solutions between the various embodiments of the present invention can be combined with each other, but it must be based on the fact that ordinary technicians in the field can implement it. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0062] This embodiment discloses a method for identifying non-orthogonal errors of polarization vectors. The method quantitatively introduces the non-orthogonal errors of polarization vectors caused by multiple scattering under cloudy weather into the model construction process. According to the characteristic that the non-orthogonal error angle changes slowly in a short period of time, the non-orthogonal errors of polarization vectors are estimated based on prior information and observation information of the observation points. This can better compensate for the influence of the non-orthogonal error angle on the orientation result. The method can be effectively applied to the polarized light orientation method under cloudy weather.

[0063] refer to Figure 1 In this embodiment, the polarization vector non-orthogonal error identification method specifically includes the following steps:

[0064] Step 1, obtaining an atmospheric polarization image;

[0065] Step 2, constructing a polarization vector non-orthogonal error angle model;

[0066] Step 3: Substitute the prior information and the observation information of each observation point in the atmospheric polarization image into the polarization vector non-orthogonal error angle model to estimate the non-orthogonal error angle of each observation point in the atmospheric polarization image.

[0067] refer to Figure 2 Schematic diagram of the scattering process of sunlight in the sky, where O c represents the observer on the ground, V represents the observation point in the sky, S represents the sun, Z represents the zenith, N represents the geographic north, τ represents the scattering angle, γ s , α s Represent the solar zenith angle and azimuth respectively, φ represents the polarization angle of the observation point, α v represents the azimuth of the observation point, γ v , α v Represents the zenith angle and azimuth angle of the observation point V in the polarized light compass coordinate system respectively.

[0068] In this embodiment, the right-front-upper coordinate system is defined as the polarized light compass coordinate system (hereinafter referred to as the "C system"), X c Axis and Y c The axes point to the horizontal and vertical axes of the polarized light compass respectively, Z c The axis is the optical axis direction of the polarized light compass. After leveling, the Z cThe axis points to the zenith. The north-east-earth coordinate system is defined as the navigation coordinate system (hereinafter referred to as the "n system"), and O n -X n Y n Z n Indicates that O n With O c coincide, Figure 2 For the sake of simplicity, Y is omitted. n Axis and Z n Axis, X n The axis direction is the geographic north. Figure 2 The front-right-bottom coordinate system is defined as the carrier coordinate system (hereinafter referred to as the "b system"), and O b -X b Y b Z b To represent, where O b With O c coincide, Figure 2 For the sake of simplicity, Y is omitted. b Axis and Z b Axis, the heading angle Ψ of the carrier is X b The angle between the axis and N. Define O v -X v Y v Z v is the observation point coordinate system (hereinafter referred to as “v system”), Z v The axis points to the direction of the observation point, X v The axis is located in the observation plane ΔO v In VV′, Y v The axis is known from the right-hand rule. Figure 2 For the sake of simplicity, Y is omitted. v Axis. e is the unit vector of the vibration direction of the polarized light E vector at the observation point V, v is the unit vector of the observation direction, and s is the unit vector in the direction of the sun.

[0069] refer to Figure 3 is a schematic diagram of the non-orthogonal error angle of the polarization vector, where the coordinate system is set and Figure 2 In the figure, the polarized light E vector e′ at the Rayleigh point is perpendicular to the scattering plane ΔSO c O v , the polarized light E vector e at the non-Rayleigh point is not perpendicular to the scattering plane ΔSO c O v Since light is a transverse wave, there are always e′ and e perpendicular to the incident light direction vector v, so there is a polarization vector non-orthogonal error angle between e and e′, which is recorded as η in this embodiment.

[0070] refer to Figure 4 , Figure 5Regardless of whether the polarization vectors have an orthogonal relationship, e can be represented by the vector consisting of the incident light direction vector v, the sun direction vector s, and v×s. Therefore, the specific construction process of the polarization vector non-orthogonal error angle model in this embodiment is:

[0071] First, decompose the E vector e of the observation point into a coordinate system consisting of the sun direction vector s axis, the observation direction vector v axis, and the orthogonal axes formed by v×s:

[0072] e=r1·s+r2·v+r3·v×s (1)

[0073] Among them, r1=sinη / / sinτ, r2=-sinη / / tanτ, r3=-cosη / / sinτ are the modulus lengths of the E vector e of the observation point on the three axes respectively;

[0074] The calculation process of the scattering angle τ is:

[0075]

[0076] Among them, s c is the projection of the sun direction vector on the optical compass coordinate system, v c is the projection of the observation direction vector on the optical compass coordinate system, and T is the transpose of the matrix;

[0077] Ideally, the non-orthogonal error angle η of the Rayleigh point is 0. At this time, equation (1) degenerates into a polarization vector orthogonal model, that is, e = r3·v×s;

[0078] Then, project the E vector e of the observation point into the optical compass coordinate system, and we have:

[0079] e c =r1·s c +r2·v c +r3·v c ×s c (3)

[0080] Among them, e c is the projection of the E vector e of the observation point on the optical compass coordinate system;

[0081] Finally, let f(η) = r1·s c +r2·v c +r3·v c ×s c -e c is the objective function. Theoretically, f(η)=0. However, due to the existence of the non-orthogonal error angle of the polarization vector, usually f(η)≠0. Therefore, the final non-orthogonal error angle model of the polarization vector is:

[0082]

[0083] In this embodiment, since the non-orthogonal error angle changes slowly in a short time, in the process of constructing the polarization vector non-orthogonal error angle model, the projection s of the sun direction vector on the optical compass coordinate system can be calculated by prior information. c , the projection v of the observation direction vector on the optical compass coordinate system c And the projection e of the E vector of the observation point on the optical compass coordinate system c .

[0084] In this embodiment, the specific calculation process of the projection of the E vector e of the observation point on the optical compass coordinate system is:

[0085]

[0086] is the conversion matrix from v system to c system, expressed as:

[0087]

[0088] Zenith angle γ of the observation point in the c system v and azimuth α v Specifically:

[0089]

[0090] Among them, (x v ,y v ) is the coordinate of the observation point in the atmospheric polarization image, (x c ,y c ) is the coordinate of the center point of the atmospheric polarization image, f c is the focal length of the polarized light compass obtained through calibration, (x v ,y v ) and (x c ,y c ) is the observation information of the observation point;

[0091] e v is the projection of the E vector e of the observation point on the v system, expressed as:

[0092]

[0093] Among them, φ is the polarization angle of the observation point, and φ is the prior information.

[0094] In this embodiment, in the process of constructing the polarization vector non-orthogonal error angle model, the polarization angle of the observation point can be calculated using the Stokes vector method. The Stokes vector contains four parameters S0 = [S1 S2 S3 S4], where S1 represents the total light intensity, S2 is the light intensity difference in the 0° and 90° directions, S3 is the light intensity difference in the 45° and 135° directions, and S4 is the circular polarization component. The light intensity of the polarized light after passing through the polarizer is:

[0095]

[0096] Where θ1 is the polarization angle, is the angle between the sensor polarization direction and the system optical axis;

[0097] Since there are very few circular polarization components in nature, the S4 component is generally omitted in actual calculations, and the simplified Stokes intensity equation is obtained as follows:

[0098]

[0099] When the polarization angle θ1 is 0°, 45°, and 90° respectively, the Stokes parameter of each pixel on the image is:

[0100]

[0101] Without considering circularly polarized light, the polarization angle of each pixel is:

[0102]

[0103] In this embodiment, the specific calculation process of the projection of the sun direction vector on the optical compass coordinate system is:

[0104]

[0105] is the transformation matrix from b system to c system, expressed as:

[0106]

[0107] is the conversion matrix from n system to c system, expressed as:

[0108]

[0109] Among them, r0, θ0, Ψ0 are respectively provided by other sensors (such as satellite dual antennas) to provide the carrier roll angle, pitch angle and heading angle, and r0, θ0, Ψ0 are prior information;

[0110] s n is the sun direction vector in the navigation coordinate system, expressed as:

[0111]

[0112] in, is the azimuth of the sun direction vector in the navigation coordinate system, is the altitude angle of the sun direction vector in the navigation coordinate system. When the time and geographical location are known, It can be obtained through the solar ephemeris, that is, This is also prior information.

[0113] In this embodiment, the specific calculation process of the projection of the observation direction vector on the optical compass coordinate system is:

[0114] v c =[sinγ v ·cosα v sinγ v ·sinα v -cosγ v ] T (18)

[0115] After completing the construction of the polarization vector non-orthogonal error angle model, the observation information of each observation point in the atmospheric polarization image is substituted into the polarization vector non-orthogonal error angle model, and the polarization vector non-orthogonal error angle model is solved in combination with a series of prior information to estimate the non-orthogonal error angle of each observation point.

[0116] According to formula (4), the problem of solving the non-orthogonal error angle can be transformed into a nonlinear programming problem with boundary constraints. Therefore, in the specific implementation process of solving the non-orthogonal error angle model of the polarization vector in step 2, the interior point method is used to solve the nonlinear optimization problem, which has the advantages of low computational complexity and strong robustness.

[0117] In the specific application process, after calculating the non-orthogonal error angle of each observation point, the non-orthogonal error angle of each observation point can be substituted into r1, r2 and r3 in formula (3), so as to calculate the current solar direction vector by combining the observation information of the observation point and a series of prior information, and the current actual heading angle of the carrier can be derived according to the solar direction vector.

[0118] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the inventive concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A method for identifying polarization vector non-orthogonality errors, characterized in that: The steps include: Step 1, obtaining an atmospheric polarization image; Step 2, constructing a polarization vector non-orthogonal error angle model, including: Decompose the E vector e of the observation point into the coordinate system composed of the sun direction vector s axis, the observation direction vector v axis and the orthogonal axes composed of v×s: e=r1·s+r2·v+r3·v×s Among them, r1 = sinη / sinτ, r2 = -sinη / tanτ, r3 = -cosη / sinτ are the modulus lengths of the E vector e of the observation point on the three axes, η is the non-orthogonal error angle of the observation point, and τ is the scattering angle; Project the E vector e of the observation point to the optical compass coordinate system: yes c =r1·s c +r2·v c +r3·v c ×s c Among them, e c is the projection of the E vector e of the observation point on the optical compass coordinate system, s c is the projection of the sun direction vector on the optical compass coordinate system, v c is the projection of the observation direction vector on the optical compass coordinate system; Let f(η) = r1·s c +r2·v c +r3·v c ×s c -e c As the objective function, the polarization vector non-orthogonal error angle model is Step 3: Substitute the prior information and the observation information of each observation point in the atmospheric polarization image into the polarization vector non-orthogonal error angle model to estimate the non-orthogonal error angle of each observation point in the atmospheric polarization image.

2. The polarization vector non-orthogonality error identification method according to claim 1, characterized in that: In step 1, the scattering angle is specifically: Where T is the transpose of the matrix.

3. The polarization vector non-orthogonality error identification method according to claim 1, characterized in that: The projection of the E vector e of the observation point on the optical compass coordinate system is specifically: is the transformation matrix from the observation point coordinate system to the optical compass coordinate system, expressed as: Among them, α v is the azimuth of the observation point in the optical compass coordinate system, γ v is the zenith angle of the observation point in the optical compass coordinate system, α v , γ v That is the observation information of the observation point; e v is the projection of the E vector e of the observation point on the observation point coordinate system, expressed as: Where φ is the polarization angle of the observation point.

4. The polarization vector non-orthogonality error identification method according to claim 3, characterized in that: The polarization angle φ of the observation point is calculated using the Stokes vector method, specifically: The Stokes vector S0 contains four parameters S0 = [S1 S2 S3 S4], where S1 represents the total light intensity, S2 is the light intensity difference between 0° and 90°, S3 is the light intensity difference between 45° and 135°, and S4 is the circular polarization component. The intensity of polarized light after passing through the polarizer is: Where θ1 is the polarization angle, is the angle between the sensor polarization direction and the system optical axis; Omitting the S4 component, the simplified Stokes intensity equation is: When the polarization angle θ1 is 0°, 45°, and 90° respectively, the Stokes parameter of each pixel on the image is: Without considering circularly polarized light, the polarization angle of each pixel is φ = (1 / 2) arctan (S3 / S2).

5. The polarization vector non-orthogonality error identification method according to claim 1, characterized in that: The projection of the sun direction vector on the optical compass coordinate system is specifically: is the transformation matrix from the carrier coordinate system to the optical compass coordinate system, expressed as: is the transformation matrix from the navigation coordinate system to the optical compass coordinate system, expressed as: Among them, r0, θ0, Ψ0 are respectively provided by other sensors for the carrier roll angle, pitch angle and heading angle, which are the prior information; s n is the sun direction vector in the navigation coordinate system, expressed as: Where T is the transpose of the matrix, is the azimuth of the sun direction vector in the navigation coordinate system, is the altitude angle of the sun direction vector in the navigation coordinate system, That is the prior information.

6. The polarization vector non-orthogonality error identification method according to claim 1, characterized in that: The projection of the observation direction vector on the optical compass coordinate system is specifically: v c =[sinγ v ·cosα v sinγ v ·sinα v -cosγ v ] T Among them, T is the transpose of the matrix, α v is the azimuth of the observation point in the optical compass coordinate system, γ v is the zenith angle of the observation point in the optical compass coordinate system, α v , γ v That is the observation information of the observation point.

7. The polarization vector non-orthogonality error identification method according to any one of claims 1 to 6, characterized in that: In step 3, the polarization vector non-orthogonal error angle model is solved based on the interior point method.

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