A modeling method based on atmospheric polarization pattern under the joint influence of the sun and the moon

Abstract

The application discloses a modeling method of atmospheric polarization mode based on the joint influence of the sun and the moon, and is aimed at the special weather situation that the sun and the moon as light sources are both in the sky. The distribution rule of the atmospheric polarization mode is acquired by using a polarization imaging device. On the basis of establishing an atmospheric polarization mode three-dimensional space coordinate system and an imaging coordinate system, the polarization information of each observation point in the sky is obtained. The application is a more accurate atmospheric polarization mode modeling method, so that the model is closer to the actual atmospheric polarization mode, and can be applied to polarization light navigation and positioning.

Description

Technical Field

[0001] This invention belongs to the field of intelligent information acquisition and processing and polarized light navigation technology. It continuously improves and optimizes the model based on natural polarization information, and in particular, it involves the establishment of an atmospheric polarization mode based on the combined influence of the sun and moon, thereby simplifying the application of polarized light navigation. Background Technology

[0002] Navigation technology has extremely wide applications in both civilian and military fields, and navigation methods based on the Earth's natural properties have attracted widespread attention due to their strong anti-interference capabilities and resistance to interference. Atmospheric polarization models possess rich spatiotemporal information. By studying the modeling and characterization methods of atmospheric polarization models and analyzing their distribution characteristics, we can obtain information such as time and spatial orientation, which is of great value and significance for autonomous navigation using polarized light.

[0003] Sunlight emitted from the sun is inherently unbiased. However, as it passes through the atmosphere, various atmospheric particles, such as oxygen, water droplets, and dust, absorb and scatter the light, resulting in polarization characteristics. This leads to a stable and regularly distributed atmospheric polarization pattern on a macroscopic scale. This pattern is closely related to factors such as the sun's position, atmospheric environment, and weather conditions. Key parameters include the degree of polarization, polarization direction, and neutral point position, containing crucial navigation information. Therefore, establishing an analytical model that describes its true distribution characteristics is a prerequisite for understanding and realizing the navigation behavior of polarized light.

[0004] Currently, two main categories of models have been developed to describe atmospheric polarization, both achieving certain results. The first category primarily involves analyzing the composition of the Earth's atmosphere to understand its structure and dynamics, and then solving the vector radiation transfer equation to construct an atmospheric polarization model. This modeling method mainly includes the doubling-accumulation method and the discrete coordinate method, but these methods are computationally complex and easily affected by initial conditions, limiting their application in many situations. The second category of models analyzes the distribution patterns of atmospheric polarization modes, focusing on the overall patterns and characteristics of sky polarized light distribution from a feature description perspective. This leads to the establishment of simple and practical analytical models of atmospheric polarization modes, such as the Rayleigh single scattering model and singular value theory models. The second category of models strikes a trade-off between large-scale computational speed and accuracy.

[0005] In existing models, there is no complete analytical model of sky polarization patterns. Furthermore, the models only consider the position of one light source, that is, they study the polarization patterns of the sun and moon separately and describe them theoretically. However, these two patterns have not been analyzed together. When the sun and moon are both in the sky, ignoring the interaction between the polarization patterns of the sun and moon will also cause errors between the measured data and the simulation results. Summary of the Invention

[0006] To address the shortcomings of the aforementioned technologies, this invention provides an atmospheric polarization pattern modeling method based on the combined influence of the sun and moon. This method aims to reduce the computational complexity of atmospheric polarization models and improve their accuracy, thereby providing a more reliable basis for obtaining heading information for polarized light navigation.

[0007] The present invention solves the technical problem by adopting the following technical solution:

[0008] The present invention provides a method for modeling atmospheric polarization patterns based on the combined influence of the sun and moon, characterized by the following steps:

[0009] Step 1: Based on the imaging characteristics of the fisheye lens, construct a two-dimensional planar representation in the isometric imaging mode;

[0010] Step 1.1: Establish a three-dimensional spatial coordinate system OXYZ to describe the theoretical atmospheric polarization model, with the ground observation location as the origin, geographic north as the Y-axis, geographic east as the X-axis, and the direction towards the zenith as the Z-axis.

[0011] Let v′ represent the projection point of the observation point v onto the two-dimensional plane XOY in the isometric imaging mode of the fisheye lens;

[0012] Let the elevation angle of the observation point v be α. v =90°-θ v , where θ v Let θ represent the zenith angle at observation point v, let ω represent the half field of view of the lens at observation point v, and let θ represent the zenith angle at observation point v. v =ω;

[0013] Using equation (1), the relationship between the imaging height y0 and the half field of view ω of the lens in the isometric mode is obtained:

[0014] y0=fω (1)

[0015] In equation (1), f represents the focal length of the fisheye lens;

[0016] Step 1.2: Based on the equidistant imaging pattern, the azimuth angle of the projection point v′ is obtained using equation (2).

[0017]

[0018] In equation (2), x v′ y v′ Let v′ be the projection position of the projection point on the X and Y axes;

[0019] The zenith angle θ of the projection point v′ is obtained using equation (3). v′ :

[0020]

[0021] Step 2: Based on Berry scattering theory, establish an atmospheric polarization model in the equidistant imaging mode;

[0022] Step 2.1: In the three-dimensional spatial coordinate system OXYZ, represent the position information of the observation point v on the hemispherical surface as follows: Where R is the radius of the hemisphere, θ v It is the zenith angle of observation point v. It is the azimuth angle of the observation point v;

[0023] Let the spatial position of the sun point s on the hemisphere be . Where, θ s This represents the zenith angle of the sun point 's'. Let α represent the azimuth angle of the sun point s, and let α be the sun's altitude angle. s =90°-θ s ;

[0024] When the altitude angle of the sun point s is α s Then, using equation (4), the radius of the projection circle of the plane where the sun point s is located on the XOY plane is obtained as r. s :

[0025]

[0026] Step 2.2: Let the point with a polarization degree of 0 in the observation points be the neutral point. After splitting the solar point s and the anti-solar point as, four neutral points are obtained. The positions of the four neutral points are then obtained using equation (5) and denoted as v in sequence. s+ ,v s- ,v as+ ,v as- :

[0027]

[0028] In equation (5), L is a parameter representing the degree of distortion at the center point, and y s v is the projection position of the sun point s on the Y-axis; s+ and v s- Let v be the position of the two neutral points where the sun point s splits. as+ and v as- Let i represent the positions of the two neutral points where the anti-solar point as splits, and let i represent the imaginary unit of the complex number.

[0029] The degree of polarization |w(v)| at the observation point v is obtained using equation (6):

[0030]

[0031] Step 3: Improve the atmospheric polarization model in the isometric imaging mode;

[0032] Step 3.1: Use equation (7) to establish the correlation factor I(θ) between the light intensity information and polarization degree information at observation point v. v ,γ v ):

[0033]

[0034] In equation (7), γ v Let F(θ) be the scattering angle corresponding to the observation point v. v ,γ v Let F be the equation for the light intensity distribution at the observation point v. ls The equation representing the light intensity distribution at position ls of the light source is F. 90 The equation representing the light intensity distribution at a position 90° angular distance from the light source;

[0035] Step 3.2: Use equation (8) to establish the depolarization factor E(θ) of the horizon region at the observation point v. v ):

[0036]

[0037] In equation (8), N is the control parameter for the effect of depolarization;

[0038] Step 3.3: Use equation (9) to obtain the control factor Q(T,α) for the maximum polarization degree under atmospheric polarization mode. ls ):

[0039]

[0040] In equation (9), α ls Let be the elevation angle of the light source ls, T be the atmospheric turbidity, and k1, k2, and k3 be three empirical coefficients.

[0041] Step 3.4: Use equation (10) to obtain the polarization degree DoP of the optimized light source ls. ls :

[0042]

[0043] Step 4: Obtain the lunar influence factor in the atmospheric polarization model;

[0044] Step 4.1: Obtain the angular distance β between the Sun and the Earth with the Moon as the center based on astronomical and geographical location information, and then obtain the lunar phase information P(β) according to equation (11):

[0045]

[0046] Step 4.2: Use equation (12) to obtain the albedo information A of the moon m. m :

[0047]

[0048] In equation (12), g i a represents the i-th power of the phase angle. i φ represents the i-th phase angle coefficient. 2i-1 b represents the 2i-1 power of the sun's longitude. i Represents the i-th solar longitude coefficient; K represents the fitting order;

[0049] Step 4.3: Use equation (13) to obtain the influence factor Inf of the moon m. m :

[0050] Inf m =P(β)·A m (13)

[0051] Step 5: Use equation (14) to obtain the degree of polarization DoP under the combined influence of the sun and moon. sm :

[0052] DoP sm =(1-Inf) m DoP s +Inf m DoP m (14)

[0053] In equation (14), DoP s DoP represents the degree of polarization under the influence of solar point s. m The degree of polarization is influenced by the moon's m.

[0054] The present invention provides an electronic device, including a memory and a processor, wherein the memory is used to store a program that supports the processor in executing the atmospheric polarization mode modeling method, and the processor is configured to execute the program stored in the memory.

[0055] The present invention discloses a computer-readable storage medium on which a computer program is stored, wherein the computer program, when executed by a processor, performs the steps of the atmospheric polarization mode modeling method.

[0056] Compared with existing technologies, the beneficial effects of this invention are reflected in:

[0057] 1. This invention addresses the shortcomings of existing traditional models by proposing corresponding optimization strategies. Furthermore, for cases where existing models only analyze a single light source, it proposes an atmospheric polarization pattern modeling method based on the combined influence of the sun and moon, making the atmospheric polarization model results closer to the actual atmospheric polarization pattern of the sky.

[0058] 2. The atmospheric polarization mode characterization model established in this invention, based on imaging theory, solves the problem that the mapping method of the sky polarization model differs significantly from the actual imaging principle when mapping from three-dimensional space to a two-dimensional plane. In the process of establishing the model, the optical imaging principle of the imaging system was fully considered, ensuring a one-to-one correspondence between sky observation points and pixels.

[0059] 3. This invention addresses the scenario where the sun and moon appear simultaneously in the sky. Based on existing theoretical models, it utilizes polarization information acquisition equipment to obtain the actual atmospheric polarization pattern under this scenario. Then, by analyzing the moon's influence factor, it obtains an atmospheric polarization model under the combined influence of the sun and moon, so as to more accurately extract information that can be used for polarized light navigation from the model. Attached Figure Description

[0060] Figure 1 This is a schematic diagram of the atmospheric polarization mode imaging relationship established in this invention;

[0061] Figure 2 This is a schematic diagram of the three-dimensional rectangular coordinate system of the atmospheric polarization mode established in this invention. Detailed Implementation

[0062] Atmospheric polarization models contain rich navigation information. By utilizing the distribution characteristics of atmospheric polarization models, we can obtain the heading angle information required for navigation. However, the key to realizing the modeling method based on the combined influence of the sun and moon is to use the model to obtain the polarization information of the observation points corresponding to the actual sky polarization model distribution.

[0063] Atmospheric polarization patterns have a time-dependent and stable spatial distribution. Therefore, by adding influencing factors that affect the actual sky polarization distribution based on the actual atmospheric polarization pattern, the accuracy of the polarization degree information at the observation point can be improved, thereby achieving more accurate theoretical results.

[0064] In this embodiment, an atmospheric polarization modeling method based on the combined influence of the sun and moon optimizes existing traditional polarization models according to actual atmospheric polarization models and supplements the special case of the sun and moon appearing in the sky together. The process is carried out in the following steps:

[0065] Step 1: Based on the imaging characteristics of the fisheye lens, construct a two-dimensional planar representation in the isometric imaging mode;

[0066] Step 1.1: Establish a three-dimensional spatial coordinate system OXYZ to describe the theoretical atmospheric polarization model, with the ground observation location as the origin, geographic north as the Y-axis, geographic east as the X-axis, and the direction towards the zenith as the Z-axis.

[0067] See Figure 1 , where (a) is the meridian section of the hemisphere, and (b) is the imaging relationship of the atmospheric polarization mode;

[0068] Let v′ represent the projection point of the observation point v onto the two-dimensional plane XOY in the isometric imaging mode of the fisheye lens;

[0069] Let the elevation angle of the observation point v be α. v =90°-θ v , where θ v Let θ represent the zenith angle at observation point v, ω represent the half-field angle of the lens at observation point v, and θ represent the zenith angle at observation point v. v =ω;

[0070] Using equation (1), the relationship between the imaging height y0 and the half field of view ω of the lens in the isometric mode is obtained:

[0071] y0=fω (1)

[0072] In equation (1), f represents the focal length of the fisheye lens;

[0073] Step 1.2: Based on the equidistant imaging pattern, the azimuth angle of the projection point v′ is obtained using equation (2).

[0074]

[0075] In equation (2), x v′ y v′ Let v′ be the projection position of the projection point on the X and Y axes;

[0076] The zenith angle θ of the projection point v′ is obtained using equation (3). v′ :

[0077]

[0078] Step 2: Based on Berry scattering theory, establish an atmospheric polarization model in the equidistant imaging mode;

[0079] Step 2.1: See Figure 2 In the three-dimensional spatial coordinate system OXYZ, the position information of the observation point v on the hemispherical surface is represented as follows: Where R is the radius of the hemisphere, θ v It is the zenith angle of observation point v. It is the azimuth angle of the observation point v;

[0080] Let the spatial position of the sun on the hemisphere be Where, θ s Indicates the zenith angle of the sun. Let α represent the azimuth of the sun, and let α be the altitude of the sun. s =90°-θ s ;

[0081] When the solar altitude angle is α s Then, using equation (4), the radius of the projection circle of the plane where the sun is located on the XOY plane is obtained as r. s :

[0082]

[0083] Step 2.2: Let the point with a polarization degree of 0 in the observation points be the neutral point. The solar point and the anti-solar point will split into four neutral points.

[0084] The positions of the four neutral points are obtained using equation (5) and denoted as v. s+ ,v s- ,v as+ ,v 4as- :

[0085]

[0086] In equation (5), the parameter L representing the degree of distortion at the center point is set to 0.18 in this embodiment. s v is the projection position of the sun s onto the Y-axis; s+ and v s- Let v be the two neutral points that split from the solar point s. as+ and v as- Let i be the two neutral points split from the anti-solar point as, and let i represent the imaginary unit of the complex number.

[0087] The degree of polarization |w(v)| at the observation point v is obtained using equation (6):

[0088]

[0089] Step 3: Improve the atmospheric polarization model in the isometric imaging mode;

[0090] Step 3.1: Use equation (7) to establish the correlation factor I(θ) between the light intensity information and polarization degree information at observation point v. v ,γ v ):

[0091]

[0092] In equation (7), γ v Let F(θ) be the scattering angle corresponding to the observation point v. v,γ v Let F be the equation for the light intensity distribution at the observation point v. ls The equation representing the light intensity distribution at position ls of the light source is F. 90 The equation representing the light intensity distribution at a position 90° angular distance from the light source;

[0093] Step 3.2: Use equation (8) to establish the depolarization factor E(θ) of the horizon region at the observation point v. v ):

[0094]

[0095] In equation (8), the control parameter for the effect of polarization N is set to 10 in this embodiment;

[0096] Step 3.3: Use equation (9) to obtain the control factor Q(T,α) for the maximum polarization degree under atmospheric polarization mode. ls ):

[0097]

[0098] In equation (9), α ls Let be the elevation angle of the light source ls, T be the atmospheric turbidity. In this embodiment, T is set to 3 under clear atmospheric conditions. k1, k2, and k3 are three empirical coefficients, which are set to 0.78, 5, and 0.76 respectively in the model.

[0099] Step 3.4: Use equation (10) to obtain the polarization degree DoP of the optimized light source ls. ls :

[0100]

[0101] Step 4: Obtain the lunar influence factor in the atmospheric polarization model;

[0102] Step 4.1: Obtain the angular distance β between the Sun and the Earth with the Moon as the center based on astronomical and geographical location information, and then obtain the lunar phase information P(β) according to equation (11):

[0103]

[0104] Step 4.2: Use equation (12) to obtain the albedo information A of the moon m. m :

[0105]

[0106] In equation (12), g i a represents the i-th power of the phase angle. i φ represents the i-th phase angle coefficient. 2i-1 b represents the 2i-1 power of the sun's longitude.i Let represent the i-th solar longitude coefficient, and K represent the fitting order; in this embodiment, K is set to 3.

[0107] Step 4.3: Use equation (13) to obtain the influence factor Inf of the moon m. m :

[0108] Inf m =P(β)·A m (13)

[0109] Step 5: Use equation (14) to obtain the degree of polarization DoP under the combined influence of the sun and moon. sm :

[0110] DoP sm =(1-Inf) m DoP s +Inf m DoP m (14)

[0111] In equation (14), DoP s The degree of polarization under solar influence, DoP m The degree of polarization under the influence of the moon;

[0112] In summary, this invention presents a novel modeling method. Based on the establishment of a three-dimensional spatial coordinate system for atmospheric polarization patterns and an atmospheric polarization pattern characterization model based on imaging theory, it optimizes existing traditional polarization models according to actual atmospheric polarization patterns, improving the accuracy of polarization information at various observation points. Furthermore, it incorporates the special case of the sun and moon appearing together in the sky, establishing a new model under the combined influence of the sun and moon. Compared to the first type of model, the computational complexity is reduced, and the model's accuracy is improved, providing a more reliable basis for obtaining heading information for polarized light navigation.

[0113] In this embodiment, an electronic device includes a memory and a processor. The memory stores a program that supports the processor in executing the above-described method, and the processor is configured to execute the program stored in the memory.

[0114] In this embodiment, a computer-readable storage medium stores a computer program, which is executed by a processor to perform the steps of the above method.

Claims

1. A method for modeling atmospheric polarization patterns based on the combined influence of the sun and moon, characterized in that, The procedure is as follows: Step 1: Based on the imaging characteristics of the fisheye lens, construct a two-dimensional planar representation in the isometric imaging mode; Step 1.1: Establish a three-dimensional spatial coordinate system OXYZ to describe the theoretical atmospheric polarization model, with the ground observation location as the origin, geographic north as the Y-axis, geographic east as the X-axis, and the direction towards the zenith as the Z-axis. Let v′ represent the projection point of the observation point v onto the two-dimensional plane XOY in the isometric imaging mode of the fisheye lens; Let the elevation angle of the observation point v be α. v =90°-θ v , where θ v Let θ represent the zenith angle at observation point v, let ω represent the half field of view of the lens at observation point v, and let θ represent the zenith angle at observation point v. v =ω; Using equation (1), the relationship between the imaging height y0 and the half field of view ω of the lens in the isometric mode is obtained: y0=fω(1) In equation (1), f represents the focal length of the fisheye lens; Step 1.2: Based on the equidistant imaging pattern, the azimuth angle of the projection point v′ is obtained using equation (2). In equation (2), x v′ y v′ Let v′ be the projection position of the projection point on the X and Y axes; The zenith angle θ of the projection point v′ is obtained using equation (3). v′ : Step 2: Based on Berry scattering theory, establish an atmospheric polarization model in the equidistant imaging mode; Step 2.1: In the three-dimensional spatial coordinate system OXYZ, represent the position information of the observation point v on the hemispherical surface as follows: Where R is the radius of the hemisphere, θ v It is the zenith angle of observation point v. It is the azimuth angle of the observation point v; Let the spatial position of the sun point s on the hemisphere be . Where, θ s This represents the zenith angle of the sun point 's'. Let α represent the azimuth angle of the sun point s, and let α be the sun's altitude angle. s =90°-θ s ; When the altitude angle of the sun point s is α s Then, using equation (4), the radius of the projection circle of the plane where the sun point s is located on the XOY plane is obtained as r. s : Step 2.2: Let the point with a polarization degree of 0 in the observation points be the neutral point. After splitting the solar point s and the anti-solar point as, four neutral points are obtained. The positions of the four neutral points are then obtained using equation (5) and denoted as v in sequence. s+ ,v s- ,v as+ ,v as- : In equation (5), L is a parameter representing the degree of distortion at the center point, and y s v is the projection position of the sun point s on the Y-axis; s+ and v s- Let v be the position of the two neutral points where the sun point s splits. as+ and v as- Let i represent the positions of the two neutral points where the anti-solar point as splits, and let i denote the imaginary unit of the complex number. The degree of polarization w(v) of the observation point v is obtained using equation (6): Step 3: Improve the atmospheric polarization model in the isometric imaging mode; Step 3.1: Use equation (7) to establish the correlation factor I(θ) between the light intensity information and polarization degree information at observation point v. v ,γ v ): In equation (7), γ v Let F(θ) be the scattering angle corresponding to the observation point v. v ,γ v Let F be the equation for the light intensity distribution at the observation point v. ls The equation representing the light intensity distribution at position ls of the light source is F. 90 The equation representing the light intensity distribution at a position 90° angular distance from the light source; Step 3.2: Use equation (8) to establish the depolarization factor E(θ) of the horizon region at the observation point v. v ): In equation (8), N is the control parameter for the effect of depolarization; Step 3.3: Use equation (9) to obtain the control factor Q(T,α) for the maximum polarization degree under atmospheric polarization mode. ls ): In equation (9), α ls Let be the elevation angle of the light source ls, T be the atmospheric turbidity, and k1, k2, and k3 be three empirical coefficients. Step 3.4: Use equation (10) to obtain the polarization degree DoP of the optimized light source ls. ls : Step 4: Obtain the lunar influence factor in the atmospheric polarization model; Step 4.1: Obtain the angular distance β between the Sun and the Earth with the Moon as the center based on astronomical and geographical location information, and then obtain the lunar phase information P(β) according to equation (11): Step 4.2: Use equation (12) to obtain the albedo information A of the moon m. m : In equation (12), g i a represents the i-th power of the phase angle. i φ represents the i-th phase angle coefficient. 2i-1 b represents the 2i-1 power of the sun's longitude. i Represents the i-th solar longitude coefficient; K represents the fitting order; Step 4.3: Use equation (13) to obtain the influence factor Inf of the moon m. m : Inf m =P(β)·A m (13) Step 5: Use equation (14) to obtain the degree of polarization DoP under the combined influence of the sun and moon. sm : DoP sm =(1-Inf m )·DoP s +Inf m ·DoP m (14) In equation (14), DoP s DoP represents the degree of polarization under the influence of solar point s. m The degree of polarization is influenced by the moon's m.

2. An electronic device, comprising a memory and a processor, characterized in that, The memory is used to store programs that support the processor in executing the atmospheric polarization mode modeling method of claim 1, and the processor is configured to execute the programs stored in the memory.

3. A computer-readable storage medium storing a computer program, characterized in that, The computer program is executed by the processor to perform the steps of the atmospheric polarization mode modeling method of claim 1.

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