A sun tracking and integrated navigation method and device based on a polarized light helicity field

Abstract

The application discloses a sun tracking and combined navigation method and device based on a polarized light curl field, and belongs to the field of autonomous navigation. Firstly, a polarized degree image and a polarized angle image are collected; a variable step gradient fusion method is used to extract gradient change information; a polarized E vector, a polarized degree gradient and a polarized E vector curl are further calculated, and a regional point set density fusion method based on statistical distribution characteristics is used to estimate a maximum polarized degree; a polarized light curl field is established according to the above information, and a sun tracking model and a combined navigation measurement model based on the polarized light curl field are constructed, which are used to realize sun tracking or correct a sky direction misalignment angle of combined navigation. The application mines spatial neighborhood constraint information contained in the polarized light field, overcomes a vertical under-constraint problem of a traditional polarized navigation method based on a polarized E vector or a polarized degree gradient vector, and provides a new solution for improving the robustness of polarized navigation.

Description

Technical Field

[0001] This invention belongs to the field of autonomous navigation, specifically relating to a solar tracking and integrated navigation method and device based on polarization curl field. Background Technology

[0002] Navigation, as a sensing method for measuring and estimating physical motion information such as attitude, velocity, and position of a moving body, is a key technology for the autonomy and intelligence of unmanned systems. Among existing main navigation methods, inertial navigation systems suffer from long-term error accumulation and accuracy degradation; visual navigation systems are limited to structured environments and confined spaces, making it difficult to meet the urgent need for long-term autonomous navigation across domains; and satellite / inertial integrated navigation systems are susceptible to satellite denial and communication interference. Therefore, there is an urgent need to explore highly reliable, robust, and fully autonomous spatial motion information sensing methods to ensure the mission execution of unmanned systems in denied environments.

[0003] The compound eyes of insects, migratory birds, and mantis shrimp can sense the polarized light field formed by the scattering of sunlight through the atmosphere, which is used to determine their course. The resulting biomimetic polarization navigation, with its advantages of full autonomy and zero error accumulation, has become an emerging and interdisciplinary technology. Biomimetic polarization navigation primarily calculates the solar vector using polarization characteristic information such as the degree of polarization and the polarization E-vector, thereby constructing a measurement constraint relationship between the solar vector and navigation information. However, existing polarization navigation methods still have shortcomings in robustness, specifically in terms of information deficiency and underdetermined constraints.

[0004] From the perspective of information deficiency, CN113819907A (An Inertial / Polarization Navigation Method Based on Polarization and Solar Dual Vector Switching) discloses a method for integrated navigation by performing measurement fusion decisions based on independent observations of polarization information in different directions by multiple sensors. CN117308926A (A Solar Vector Optimization Method Based on Solar Sensor and Polarization Sensor) discloses a method for integrated navigation based on measurement fusion decisions using a polarization compound eye sensor and a solar sensor. These methods only utilize the characteristic distribution information of a single polarization E-vector, and the polarization degree information is only used as a weighting factor to characterize measurement quality, ignoring the polarization navigation features inherent in the polarization degree distribution. CN118464020A (A Combined Navigation Method Based on Underwater Polarization Gradient Measurement) discloses a method for correcting the celestial misalignment angle in underwater combined navigation by relying solely on polarization degree information. However, due to the instability of the single polarization degree distribution characteristics, and the lack of more stable polarization E-vector characteristic distribution information, this method is not robust to environmental noise interference. In terms of information correlation, the above methods treat measurement information from different observation directions as independent, only considering the vertical constraints formed by each measurement and the solar vector, without analyzing the correlation constraints between measurement information implied in local regional changes. This results in the solar vector being constrained only within a vertical plane in local regions, leading to under-constraint problems, increasing the uncertainty of the solar vector solution, and thus affecting the accuracy of polarization navigation.

[0005] In summary, the lack of information and underdetermined constraints in existing polarization navigation systems lead to reduced robustness. Regarding the lack of information, it is necessary to integrate the constraint characteristics inherent in multi-dimensional polarization features such as the polarization E-vector and degree of polarization to enhance information utilization capabilities. Regarding the underdetermined constraints, it is necessary to analyze the correlation constraints of measurement information from the characteristics of local regional variations to overcome the underdetermined problems caused by the vertical constraint between traditional measurements and the solar vector. Summary of the Invention

[0006] To address the aforementioned technical issues, this invention proposes a solar tracking and integrated navigation method based on the polarization curl field. This method considers both the curl distribution characteristics of the spatial polarization field, including polarization degree and polarization E-vector distribution, and navigation constraints. By introducing the variation characteristics of the local observation area of ​​the polarization field, a collinearity constraint between polarization information and the solar vector can be established, overcoming the vertical under-constraint defect of traditional polarization navigation methods. Furthermore, the introduction of polarization E-vector information enhances the stability of constraints based solely on polarization degree information, providing a new solution for improving the robustness of biomimetic polarization navigation.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] A solar tracking and integrated navigation method based on polarization curl field includes the following steps:

[0009] Step 1: Based on the light intensity images acquired by the polarization image sensor at polarization detection directions of 0°, 45°, 90°, and 135°... Calculate the polarization degree image Image with polarization angle ;

[0010] Step 2: Use the variable step size gradient fusion method to extract the polarization degree images respectively. and polarization angle image Gradient change information in the X and Y directions ;

[0011] Step 3: Based on the polarization degree image Polarization angle image and its gradient change information , , , The polarization vector E is calculated. Polarization gradient and the curl of the polarization E vector The maximum polarization degree is estimated using a region point set density fusion method based on statistical distribution characteristics. ;

[0012] Step 4: Calculate the polarization curl field based on the results of Step 3. And construct a solar tracking model and integrated navigation measurement model .

[0013] A solar tracking and integrated navigation device based on polarization curl field includes the following modules:

[0014] The polarization degree image and polarization angle image calculation module calculates light intensity images acquired by the polarization image sensor at polarization analysis directions of 0°, 45°, 90°, and 135°. Calculate the polarization degree image Image with polarization angle ;

[0015] The gradient change information extraction module uses a variable step size gradient fusion method to extract polarization degree images separately. and polarization angle image Gradient change information in the X and Y directions ;

[0016] The maximum polarization degree estimation module estimates the polarization degree based on the polarization degree image. Polarization angle image and its gradient change information , , , The polarization vector E is calculated. Polarization gradient and the curl of the polarization E vector The maximum polarization degree is estimated using a region point set density fusion method based on statistical distribution characteristics. ;

[0017] The model construction module calculates the polarization curl field based on the results of step 3. And construct a solar tracking model and integrated navigation measurement model .

[0018] An electronic device includes: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the above-described solar tracking and integrated navigation method based on polarization rotation field.

[0019] A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to implement the aforementioned solar tracking and integrated navigation method based on polarization curl field.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] This invention constructs a spatial polarization curl field by extracting gradient change information from polarization images. It comprehensively utilizes spatial neighborhood variation constraints, including multi-dimensional polarization feature information such as polarization degree and polarization E vector, to overcome the information deficiency problem of traditional polarization navigation methods based on single polarization features. Considering the influence of polarization imaging noise, a variable step size gradient fusion method and a region point set density fusion method based on statistical distribution characteristics are designed to enhance the robustness of gradient information extraction and maximum polarization degree estimation. A solar tracking model based on the polarization curl field and integrated navigation measurement constraints are designed. The collinearity constraint between the polarization curl field and the solar vector overcomes the vertical under-constraint problem of traditional polarization navigation methods, improves solar tracking accuracy and robustness, and enhances the error correction capability of integrated navigation. Attached Figure Description

[0022] Figure 1 This is a flowchart of a solar tracking and integrated navigation method based on polarization curl field according to the present invention;

[0023] Figure 2 This is a schematic diagram of the polarization curl field calculation results of the present invention;

[0024] Figure 3 This is a comparison chart of the solar tracking performance of embodiments of the present invention and traditional methods based on polarization degree gradients;

[0025] Figure 4 This is a comparison chart of the heading angle and azimuth misalignment angle results of the embodiment of the present invention and the traditional integrated navigation based on the polarization degree gradient method. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other. To achieve the above objectives, this invention adopts the following technical solution.

[0027] According to one embodiment of the present invention, such as Figure 1 As shown, the present invention provides a solar tracking and integrated navigation method based on polarization curl field, comprising the following steps:

[0028] Step 1: Based on the light intensity images acquired by the polarization image sensor at polarization detection directions of 0°, 45°, 90°, and 135°... Calculate the polarization degree image Image with polarization angle ;

[0029] ;

[0030] Step 2: Use the variable step size gradient fusion method to extract the polarization degree images respectively. and polarization angle image Gradient change information in the X and Y directions ;

[0031] The polarization image calculated in step 1 Image with polarization angle A variable step size gradient fusion method is used to extract gradient change information in the X and Y directions. ;

[0032] ;

[0033] in, For element-wise product operators, For convolution operators, , Here are the convolution kernels and their weights in the X direction. , Let Y be the convolution kernel and its weights.

[0034] Step size At that time, the convolution kernel in the X direction and their weights and Y-direction convolution kernel and their weights They are respectively:

[0035] ;

[0036] Step 3: Based on the polarization degree image Polarization angle image and its gradient change information , , , The polarization vector E is calculated. Polarization gradient and the curl of the polarization E vector The maximum polarization degree is estimated using a region point set density fusion method based on statistical distribution characteristics. ;

[0037] First, based on the polarization degree image calculated in steps 1 and 2. Polarization angle image and its gradient change information , , , The polarization vector E is calculated. Polarization gradient and the curl of the polarization E vector :

[0038] ;

[0039] ;

[0040] in, , For camera focal length, These are the X and Y coordinates of the polarization degree or polarization angle image, respectively. Image of polarization angle The value, , They are respectively and The value, , They are respectively and The value, For Nabla operators;

[0041] Furthermore, based on the polarization degree image With polarization gradient The maximum polarization degree is estimated using a candidate region density-weighted fusion method based on statistical distribution characteristics. :

[0042] ;

[0043] in, For the summation operator, For conditions and operators, For vector modulo operator, For the corresponding Quantiles. For point set density weights, It is a matrix of all ones. This is the characteristic matrix of the maximum polarization degree zone.

[0044] Step 4: Calculate the polarization curl field based on the results of Step 3. And construct a solar tracking model and integrated navigation measurement model ;

[0045] The polarization E vector calculated in step 3 Polarization gradient Polarization E-vector curl and maximum polarization degree Calculate the polarization curl field Construct a solar tracking model To achieve tracking of solar vectors Solar tracking model The expression is as follows:

[0046] ;

[0047] in, For antisymmetric matrix operators, For the first Measurement of polarization rotation, The number of polarization rotator measurements. Polarization degree image The value of the radial gradient and take ;

[0048] According to the polarization rotation field It can construct integrated navigation measurement models. :

[0049] ;

[0050] in, For navigation system The solar vector below, To calculate the attitude matrix for strapdown, To solve the attitude matrix for strapdown induction with errors, For the carrier system Measurement of polarization rotation under the following conditions For the attitude misalignment angle, For measuring noise.

[0051] Example:

[0052] This embodiment uses a polarization image sensor based on a pinhole camera model as an example for simulation. The simulation algorithm parameters are shown in Table 1.

[0053] Table 1

[0054]

[0055] The variables in the subsequent formulas of this embodiment are defined and calculated using the same methods as those in the specification, and will not be repeated here. The specific steps are as follows:

[0056] Step 1: Define the polarization image sensor parameters according to the image size, image center, and camera focal length in Table 1, and obtain the polarization degree image based on the ideal Rayleigh scattering model simulation. Image with polarization angle ;

[0057] Step 2: Employ the variable step-size gradient fusion method, based on the step size defined in Table 1. Calculate the convolution kernel in the X direction of the image. and their weights and Y-direction convolution kernel and their weights Based on the calculated convolution kernel and weights, the polarization degree images are extracted respectively. and polarization angle image Gradient change information in the X and Y directions ;

[0058] Step 3: Based on the polarization degree image calculated in Step 1 and Step 2 Polarization angle image and its gradient change information , , , The polarization vector E is calculated. Polarization gradient and the curl of the polarization E vector .

[0059] According to the polarization image and polarization gradient Calculate the characteristic matrix of the maximum polarization degree zone Take the matrix of all ones from Table 1. Using the dimension as a parameter, the point set density weights are further calculated. Combined with polarization degree image Weighted fusion estimation of maximum polarization ;

[0060] Step 4: Based on the polarization E vector calculated in Step 3 Polarization gradient Polarization E-vector curl and maximum polarization degree Constructing the polarization curl field The solar tracking model is solved using a singular value decomposition-based method. The solution to the homogeneous equation is obtained, which is the solar vector. To achieve solar tracking. Based on the polarization curl field. It can construct a combined navigation measurement model. By combining the traditional 15-dimensional inertial navigation error state equation with the Kalman filter algorithm, the azimuth misalignment angle can be corrected, thereby improving the orientation accuracy of the integrated navigation system.

[0061] Based on the parameters in Table 1, the polarization curl field of the light when the solar zenith angle is 45°, obtained through processing in this embodiment, is as follows: Figure 2 As shown, the solid arrows represent the polarization curl field. It can express the collinearity constraint with the solar vector, and the dotted-dash arrow represents the traditional polarization E vector. This only expresses the perpendicular constraint with the solar vector. Therefore, for the underdetermined constraint problem, the collinear constraint of the method of this invention is stronger than that of the traditional polarization E vector. Vertical constraints.

[0062] To verify the performance improvement of this invention compared to the traditional polarization gradient-based solar tracking method, simulation software was used to conduct multiple simulations at 5° intervals within a range of solar azimuth angle from 0° to 360° and solar zenith angle from 0° to 90°. The polarization degree images were used for these simulations. Image with polarization angle Gaussian noise was added to all samples. The standard deviation of the noise is shown in Table 1, and the step size was taken. It is 75. For example... Figure 3 As shown, the root mean square error (RMSE) of estimating the sun's position using the method in this embodiment is 0.56°, while the traditional method based on polarization gradient is easily affected by noise, resulting in an estimated RMS error of 2.75°. Therefore, regarding the problem of insufficient information, the method of this invention is less affected by sampling noise compared to the traditional method based on polarization gradient, and its utilization of spatial neighborhood variation information demonstrates strong robustness in sun tracking.

[0063] To verify the effect of the present invention on the correction of the azimuth misalignment angle of integrated navigation compared with the traditional polarization gradient method, motion trajectory was generated using simulation software, and the error parameters of the inertial navigation device are shown in Table 1. Figure 4 of (a) Figure 4 (b) shows the heading angle curve and the azimuth misalignment angle curve obtained by combined navigation filtering using a classical Kalman filter. The root mean square error of the azimuth misalignment angle corrected using the method in this embodiment is 10.81', while the root mean square error of the azimuth misalignment angle corrected by the traditional method based on polarization degree gradient is 11.03'. Therefore, in terms of azimuth misalignment angle correction in combined navigation, the method of this invention has higher accuracy than the traditional method based on polarization degree gradient.

[0064] Although the illustrative specific embodiments of the present invention have been described above to enable those skilled in the art to understand the invention, it should be understood that the invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes will be obvious as long as they are within the spirit and scope of the invention as defined and determined by the appended claims, and all inventions utilizing the concept of the present invention are protected.

Claims

1. A solar tracking and integrated navigation method based on polarization curl field, characterized in that, Includes the following steps: Step 1: Based on the light intensity images acquired by the polarization image sensor at polarization detection directions of 0°, 45°, 90°, and 135°... Calculate the polarization degree image Image with polarization angle ; Step 2: Use the variable step size gradient fusion method to extract the polarization degree images respectively. and polarization angle image Gradient change information in the X and Y directions ; Step 3: Based on the polarization degree image Polarization angle image and its gradient change information , , , The polarization vector E is calculated. Polarization gradient and the curl of the polarization E vector The maximum polarization degree is estimated using a region point set density fusion method based on statistical distribution characteristics. ; Step 4: Calculate the polarization curl field based on the results of Step 3. And construct a solar tracking model and integrated navigation measurement model .

2. The solar tracking and integrated navigation method based on polarization curl field according to claim 1, characterized in that, Step 2 includes: The polarization image calculated in step 1 Image with polarization angle A variable step size gradient fusion method is used to extract gradient change information in the X and Y directions. ; ； in, For element-wise product operators, For convolution operators, , The convolution kernel and its weights are in the X direction. , Let Y be the convolution kernel and its weights.

3. The solar tracking and integrated navigation method based on polarization curl field according to claim 2, characterized in that, Step 2 further includes: determining the step size. At that time, the X-direction convolution kernel of the polarization degree or polarization angle image and their weights and Y-direction convolution kernel and their weights for: 。 4. The solar tracking and integrated navigation method based on polarization curl field according to claim 3, characterized in that, Step 3 includes: The polarization image calculated based on steps 1 and 2 Polarization angle image and its gradient change information , , , The polarization vector E is calculated. Polarization gradient and the curl of the polarization E vector : ； ； in, , For camera focal length, These are the X and Y coordinates of the polarization degree or polarization angle image, respectively. Image of polarization angle The value, , They are respectively and The value, , They are respectively and The value, This is the Nabla operator.

5. The solar tracking and integrated navigation method based on polarization curl field according to claim 4, characterized in that, Step 3 further includes: based on the polarization image With polarization gradient The maximum polarization degree is estimated using a candidate region density-weighted fusion method based on statistical distribution characteristics. : ； in, For the summation operator, For conditions and operators, For vector modulo operator, For the corresponding Quantiles For point set density weights, It is a matrix of all ones. This is the characteristic matrix of the maximum polarization degree zone.

6. The solar tracking and integrated navigation method based on polarization curl field according to claim 5, characterized in that, Step 4 includes: The polarization E vector calculated in step 3 Polarization gradient Curl of polarization E vector and maximum polarization degree Calculate the polarization curl field Construct a solar tracking model To achieve tracking of solar vectors Solar tracking model The expression is as follows: ； in, For antisymmetric matrix operators, For the first Measurement of polarization rotation, The number of polarization rotator measurements. Polarization degree image The value of the radial gradient and take .

7. A solar tracking and integrated navigation method based on polarization curl field according to claim 6, characterized in that, Step 4 further includes: According to the polarization rotation field Constructing an integrated navigation measurement model : ； in, For navigation system The lower solar vector, To calculate the attitude matrix for strapdown, To solve the attitude matrix for strapdown induction with errors, For the carrier system Measurement of polarization rotation under the following conditions For attitude misalignment angle, For measuring noise.

8. A solar tracking and integrated navigation device based on polarization curl field, characterized in that, Includes the following modules: The polarization degree image and polarization angle image calculation module calculates light intensity images acquired by the polarization image sensor at polarization analysis directions of 0°, 45°, 90°, and 135°. Calculate the polarization degree image Image with polarization angle ; The gradient change information extraction module uses a variable step size gradient fusion method to extract polarization degree images separately. and polarization angle image Gradient change information in the X and Y directions ; The maximum polarization degree estimation module estimates the polarization degree based on the polarization degree image. Polarization angle image and its gradient change information , , , The polarization vector E is calculated. Polarization gradient and the curl of the polarization E vector The maximum polarization degree is estimated using a region point set density fusion method based on statistical distribution characteristics. ; The model construction module calculates the polarization curl field based on the results of step 3. And construct a solar tracking model and integrated navigation measurement model .

9. An electronic device, characterized in that, include: One or more processors; A memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the solar tracking and integrated navigation method based on polarization curl field as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores executable instructions that, when executed by a processor, cause the processor to implement the solar tracking and integrated navigation method based on polarization curl field as described in any one of claims 1 to 7.

Images