An online calibration method for micro-array polarization camera parameters based on star sensor

Abstract

The present invention relates to an online calibration method for parameters of a micro-array polarization camera based on a star sensor. The method comprises the following steps: using the light intensity gain coefficient, polarization coefficient, and polarizer installation angle of each polarization unit of the micro-array polarization camera as state variables to establish a state equation; based on the principle that the dot product of vectors remains unchanged in different coordinate systems, the moon vector in the geographic coordinate system is combined with the star vector observed by the star sensor to solve for the moon vector in the carrier coordinate system. Furthermore, the polarization azimuth is characterized based on the perpendicular relationship between the moon vector and the polarization vector. Furthermore, the polarization azimuth is combined with the model of each polarization unit of the micro-array polarization camera to establish a measurement equation for the polarization intensity of each optical path channel, the light intensity gain coefficient, polarization coefficient, and polarizer installation angle; and finally, an unscented Kalman filter is used to achieve online calibration of the micro-array polarization camera model parameters.

Description

Technical Field

[0001] The present invention relates to an online calibration method for micro-array polarization camera parameters based on star sensors. By combining the star vector information of the star sensor, an online calibration model for the micro-array polarization camera parameters based on light intensity is established. This method implements online calibration of the micro-array polarization camera model parameters and improves the environmental adaptability of the micro-array polarization camera under different moon phases and weather conditions at night. Background Art

[0002] Natural organisms, such as dung beetles and sweat bees, can perceive polarized light fields at night, enabling navigational activities such as foraging and catching prey. Inspired by this biological navigation method, nighttime biomimetic polarized light navigation has garnered widespread attention. Its advantages, such as immunity to electromagnetic interference and lack of error accumulation, provide a technical means for autonomous navigation of unmanned systems at night. Polarization sensors, as instruments for sensing polarized light fields at night, are capable of detecting polarized light and are a core component of nighttime polarized light navigation. Their accuracy is crucial for nighttime polarized light navigation. Theoretical analysis and research have shown that the accuracy of polarization sensors depends not only on the design of the sensor's optical path structure, but also on the calibration of the polarization sensor model parameters. The accuracy and speed of model parameter calibration are crucial for improving the performance and environmental adaptability of polarization sensors.

[0003] In recent years, many research institutions have conducted extensive research on polarization sensor calibration. The paper "Design and Calibration of a Novel Bio-Inspired Pixelated Polarized Light Compass" uses an integrating sphere and a high-precision turntable to provide polarization angle information. It introduces an iterative least squares algorithm to calibrate model parameters in an array of polarization cameras, improving the accuracy of the polarization camera's heading angle solution. The patent "A Multi-Source Error Calibration Method for a Bio-Inspired Polarization Sensor Based on Adaptive EKF" (Application Number: CN201811421555.8) establishes a polarization sensor model based on multiple interference sources such as installation error and measurement noise. An adaptive extended Kalman filter method is designed. While using a turntable and integrating sphere for filtering calculations, a noise statistical estimator is employed to estimate and correct for unknown time-varying noise characteristics, enhancing the sensor calibration's anti-interference capability. The patent "A Calibration Method for a Multi-Camera Polarization Sensor" (Application Number: CN201610030919.4) establishes the measurement error equations for a multi-camera polarization sensor and the linear regression equations for each camera. Next, based on the polarization angle information provided by the turntable and integrating sphere, a target optimization function for the polarizer installation error angle was established. Finally, the installation error angle was calibrated using Gauss-Newton iteration, effectively improving the measurement accuracy of the polarization sensor.

[0004] The polarization sensor calibration methods proposed in the aforementioned papers and patents all rely on a turntable, are offline calibration methods, and the calibration parameters are fixed. In actual application scenarios, the atmospheric environment and meteorological parameters will change, making the fixed parameters of offline calibration difficult to apply to such environments. To address this issue, the patent "A method for online calibration of polarization sensor errors based on the assistance of a solar sensor" (application number: CN202311648246.5) utilizes the high-precision solar vector information provided by a solar sensor. Based on the relationship between the polarization vector perpendicular to the solar vector and the observation vector under the carrier system, combined with the polarization sensor model, it achieves online calibration of the polarization sensor error parameters. However, this method is only applicable to daytime environments and is difficult to apply in nighttime environments. Therefore, in order to meet the demand for nighttime polarization sensor parameter calibration, further research is needed to combine the star vector information obtained by the star sensor, break through the online calibration technology of the polarization sensor model parameters, achieve dynamic optimization of the polarization sensor model parameters, and thereby improve the angular measurement performance and environmental adaptability of the polarization sensor in nighttime environments. Summary of the Invention

[0005] To address the aforementioned issues and overcome the shortcomings of the prior art, the present invention proposes an online calibration method for micro-array polarization camera parameters based on a star sensor. The method uses the model parameters of the micro-array polarization camera, namely the light intensity gain coefficient, polarization degree coefficient, and analyzer direction angle, as the state quantities to be estimated, and establishes a state equation. The moon vector information is calculated using the star vector measured by the star sensor, and a functional relationship between the polarization azimuth angle and the moon vector is then established. Based on this, and in combination with the micro-array polarization camera model, a measurement equation based on the output light intensity of the micro-array polarization camera's optical path channels is established. Finally, an unscented Kalman filter is used to achieve online calibration of the micro-array polarization camera model parameters.

[0006] The technical solution adopted by the present invention is: an online calibration method for parameters of a micro-array polarization camera based on a star sensor, which is implemented in the following steps:

[0007] Step (1) is to use the light intensity gain coefficient of each polarization unit of the microarray polarization camera Polarization coefficient Analyzer angle α i,j As the state quantity x, where i represents the serial number of the polarization unit, j = 1, ..., 4 represents the j-th optical path channel of the polarization unit. The state quantity of the i-th polarization unit is expressed as: Establishing the state equation of polarization camera parameters Where f(·) is the state quantity x and its first-order derivative The functional relationship between them.

[0008] Step (2): Use the star sensor to measure and obtain the star vectors under N carrier systems (system b): Where N≥3. According to the astronomical calendar, the corresponding N star vector information in the geographic coordinate system (n system) is obtained And the moon vector information m n Based on the principle that the vector dot product remains unchanged under different coordinate systems, the equation S is established. b ·m b =S n ·m n , get the moon vector m under the carrier system b . Further, according to the b system and each polarization unit coordinate system (l i The coordinate transformation relationship of the system) is obtained i Moon vector

[0009] Step (3), 1 i Polarization vector under the system Perpendicular to the moon vector and the observation vector Based on the above relationship, the polarization vector is established. Medium polarization azimuth With moon vector Functional relationship Where h represents the polarization azimuth With moon vector The functional relationship between them.

[0010] Step (4), based on the model of the i-th polarization unit in the microarray polarization camera Further combined with the polarization azimuth angle established in step (3) With moon vector The functional relationship of the camera model parameter measurement equation based on the polarization output light intensity is established. in, represents the incident light intensity, d i represents the degree of polarization, y i,j represents the output light intensity of the jth optical path, g i (·), L i (·) represent the functional relationship between the input parameters and the polarization output light intensity.

[0011] Step (5) combines the state equations and measurement equations of the microarray polarization camera parameters in steps (1) and (4) to establish an online calibration model for the microarray polarization camera parameters assisted by a star sensor. Based on the characteristics of the model, the unscented Kalman filter method is used to online estimate the model parameters of each polarization unit in the microarray polarization camera, thereby improving the nighttime navigation accuracy and environmental adaptability of the polarization camera.

[0012] Furthermore, in the step (1), the light intensity gain coefficient of each polarization unit of the microarray polarization camera is Polarization coefficient Analyzer angle α i,j As the state quantity x, where i represents the serial number of the polarization unit, j = 1, ..., 4 represents the j-th optical path channel of the polarization unit. The state quantity of the i-th polarization unit is expressed as: Establishing the state equation of polarization camera parameters Where f(·) is the state quantity x and its first-order derivative The functional relationship between them.

[0013] In each polarization unit of the microarray polarization camera, the model parameters can be approximately considered to be constants within a unit time, and are slowly varying state quantities. Therefore, the state equation can be expressed as:

[0014]

[0015] Furthermore, in step (2), the star vectors under N carrier systems (system b) are measured using a star sensor. Where N≥3. According to the astronomical calendar, the corresponding N star vector information in the geographic coordinate system (n system) is obtained And the moon vector information m n Based on the principle that the vector dot product remains unchanged under different coordinate systems, the equation S is established. b ·m b =S n ·m n , get the moon vector m under the carrier system b . Further, according to the b system and each polarization unit coordinate system (l i The coordinate transformation relationship of the system) is obtained i Moon vector

[0016] Define the following formula:

[0017]

[0018] in, The matrix is ​​composed of S n and m n The angle between them.

[0019] Based on the least squares method, the moon vector under the carrier system can be expressed as:

[0020]

[0021] Furthermore, the coordinate system of each polarization unit in the microarray polarization camera is defined as l iAccording to the center point of the micro-array polarization camera (x c ,y c ) and the optical focal length f c , l i The coordinate transformation matrix between the a system and the b system can be expressed as:

[0022]

[0023] in, x p ,y p is the center point coordinate of the i-th polarization unit.

[0024] Therefore, l i Moon vector It can be expressed as:

[0025]

[0026] in, The T in the upper right corner is the transpose symbol.

[0027] Furthermore, in the step (3), i Polarization vector under the system Perpendicular to the moon vector and the observation vector Based on the above relationship, the polarization vector is established. Medium polarization azimuth With moon vector Functional relationship Where h represents the polarization azimuth With moon vector The functional relationship between them.

[0028] In l i Under the system, the moon vector is Observation vector Based on the perpendicular relationship between the polarization vector, the observation vector and the moon vector, the polarization vector It can be expressed as:

[0029]

[0030] According to formula (6), the polarization azimuth and The relationship can be expressed as:

[0031]

[0032] in, Representative vector The mold length.

[0033] Furthermore, in step (4), based on the model of the i-th polarization unit in the microarray polarization camera Further combined with the polarization azimuth angle established in step (3) With moon vector The functional relationship of the camera model parameter measurement equation based on the polarization output light intensity is established. in, represents the incident light intensity, d i represents the degree of polarization, y i,j represents the output light intensity of the jth optical path, g i (·), L i (·) represent the functional relationship between the input parameters and the polarization output light intensity.

[0034] The j-th optical path channel model of the i-th polarization unit in the microarray polarization camera is expressed as:

[0035]

[0036] Among them, y i,j Indicates the output light intensity, represents the incident light intensity, d i represents the degree of polarization, Indicates the polarization azimuth; light intensity gain coefficient Polarization coefficient Analyzer angle α i,j are the polarization camera model parameters to be estimated;

[0037] The polarization azimuth in formula (7) With moon vector Substitute the relationship into formula (8) to establish the measurement equation based on the output light intensity of the optical path channel:

[0038]

[0039] Among them, ν i,j represents the measurement noise.

[0040] Furthermore, in step (5), the state equations and measurement equations of the microarray polarization camera parameters in steps (1) and (4) are combined to establish an online calibration model for the microarray polarization camera parameters assisted by a star sensor. Based on the characteristics of the model, an unscented Kalman filter method is used to online estimate the model parameters of each polarization unit in the microarray polarization camera, thereby improving the nighttime navigation accuracy and environmental adaptability of the polarization camera.

[0041] Combining formulas (1) and (9), the online calibration model of micro-array polarization camera model parameters based on star-sensor assistance can be expressed as:

[0042]

[0043]

[0044] The advantages of the present invention over the prior art are: it is the first to propose an online calibration method for micro-array polarization camera parameters based on star sensors. In combination with the star vector information of the star sensors, an online calibration model for micro-array polarization camera parameters based on light intensity is established. This allows online calibration of the light intensity gain coefficient, polarization coefficient, and analyzer direction angle, thereby improving the environmental adaptability of the micro-array polarization camera under different moon phases and weather conditions at night. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 The present invention provides a flow chart of an online calibration method for parameters of a micro-array polarization camera based on a star sensor. DETAILED DESCRIPTION

[0046] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all 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.

[0047] Under varying nighttime weather conditions and lunar phases, the fixed parameters of a microarray polarization camera model make it difficult to accurately invert and interpret polarization information. To address this issue, the present invention proposes a star sensor-based online calibration method for microarray polarization camera parameters. By utilizing star vector information measured by the star sensor, this method enables online estimation of microarray polarization camera model parameters, eliminating reliance on a turntable and improving the microarray polarization camera's adaptability to complex nighttime environments.

[0048] The specific implementation steps of the present invention are as follows:

[0049] Step 1: Use the light intensity gain coefficient of each polarization unit of the microarray polarization camera Polarization coefficient Analyzer angle α i,j As the state quantity x, where i represents the serial number of the polarization unit, j = 1, ..., 4 represents the j-th optical path channel of the polarization unit. The state quantity of the i-th polarization unit is expressed as: Establishing the state equation of polarization camera parameters Where f(·) is the state quantity x and its first-order derivative The functional relationship between them.

[0050] In each polarization unit of the microarray polarization camera, the model parameters can be approximately considered to be constants within a unit time, and are slowly varying state quantities. Therefore, the state equation can be expressed as:

[0051]

[0052] Step 2: Use the star sensor to measure and obtain the star vectors under N carrier systems (system b) Where N≥3. According to the astronomical calendar, the corresponding N star vector information in the geographic coordinate system (n system) is obtained And the moon vector information m n Based on the principle that the vector dot product remains unchanged under different coordinate systems, the equation S is established. b ·m b =S n ·m n , get the moon vector m under the carrier system b . Further, according to the b system and each polarization unit coordinate system (l i The coordinate transformation relationship of the system) is obtained i Moon vector

[0053] Define the following formula:

[0054]

[0055] in, The matrix is ​​composed of S n and m n The angle between them.

[0056] Based on the least squares method, the moon vector under the carrier system can be expressed as:

[0057]

[0058] Furthermore, the coordinate system of each polarization unit in the microarray polarization camera is defined as l i According to the center point of the micro-array polarization camera (x c ,y c ) and the optical focal length f c , l i The coordinate transformation matrix between the a system and the b system can be expressed as:

[0059]

[0060] in, x p ,y p is the center point coordinate of the i-th polarization unit.

[0061] Therefore, l i Moon vector It can be expressed as:

[0062]

[0063] in, The T in the upper right corner is the transpose symbol.

[0064] Step 3, l i Polarization vector under the system Perpendicular to the moon vector and the observation vector Based on the above relationship, the polarization vector is established. Medium polarization azimuth With moon vector Functional relationship Where h represents the polarization azimuth With moon vector The functional relationship between them.

[0065] In l i Under the system, the moon vector is Observation vector Based on the perpendicular relationship between the polarization vector, the observation vector and the moon vector, the polarization vector It can be expressed as:

[0066]

[0067] According to formula (6), the polarization azimuth and The relationship can be expressed as:

[0068]

[0069] in, Representative vector The mold length.

[0070] Step 4: Model based on the i-th polarization unit in the microarray polarization camera Further combined with the polarization azimuth angle established in step (3) With moon vector The functional relationship of the camera model parameter measurement equation based on the polarization output light intensity is established. in, represents the incident light intensity, d i represents the degree of polarization, y i,j represents the output light intensity of the jth optical path, g i (·), L i (·) represent the functional relationship between the input parameters and the polarization output light intensity.

[0071] The j-th optical path channel model of the i-th polarization unit in the microarray polarization camera is expressed as:

[0072]

[0073] Among them, y i,j Indicates the output light intensity, represents the incident light intensity, d i represents the degree of polarization, Indicates the polarization azimuth; light intensity gain coefficient Polarization coefficient Analyzer angle α i,j are the polarization camera model parameters to be estimated;

[0074] The polarization azimuth in formula (7) With moon vector Substitute the relationship into formula (8) to establish the measurement equation based on the output light intensity of the optical path channel:

[0075]

[0076] Among them, ν i,j represents the measurement noise.

[0077] Step 5: Combine the state equations and measurement equations of the microarray polarization camera parameters in steps (1) and (4) to establish an online calibration model for the microarray polarization camera parameters assisted by a star sensor. Based on the characteristics of the model, the unscented Kalman filter method is used to online estimate the model parameters of each polarization unit in the microarray polarization camera, thereby improving the nighttime navigation accuracy and environmental adaptability of the polarization camera.

[0078] Combining formulas (1) and (9), the online calibration model of micro-array polarization camera model parameters based on star-sensor assistance can be expressed as:

[0079]

[0080] The foregoing is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the aforementioned embodiments. All technical solutions based on the principles of the present invention are within the scope of protection of the present invention. It should be noted that improvements and modifications made by persons of ordinary skill in the art without departing from the principles of the present invention are within the scope of protection of the present invention. Any content not described in detail in this specification is within the common knowledge of those skilled in the art.

Claims

1. A method for online calibration of micro-array polarization camera parameters based on star sensors, characterized in that: The implementation steps are as follows: Step (1) is to use the light intensity gain coefficient of each polarization unit of the microarray polarization camera , polarization coefficient , polarization direction angle As a state quantity ,in Represents the serial number of the polarization unit, , represents the first polarization unit optical path channel; The state quantity of each polarization unit is expressed as: , establish the state equation of polarization camera parameters ;in, is the state quantity Its first-order derivative The functional relationship between Step (2): Use star sensor to measure Individual carrier systems ( b Star vector under the system ,in ; Get the geographical coordinate system according to the astronomical calendar ( n System) Star vector information And moon vector information ; Based on the principle that the vector dot product remains unchanged under different coordinate systems, the equation is established , get the moon vector under the carrier system ; Further, according to b The coordinate system of each polarization unit ( The coordinate transformation relationship of the system is obtained Moon vector ; Step (3) Polarization vector under the system Perpendicular to the moon vector and the observation vector Based on the above relationship, the polarization vector Medium polarization azimuth With moon vector Functional relationship ;in, Indicates the polarization azimuth With moon vector The functional relationship between Step (4), based on the microarray polarization camera Model of a polarization unit , further combined with the polarization azimuth angle established in step (3) With moon vector The functional relationship of the camera model parameter measurement equation based on the polarization output light intensity is established. ;in, represents the incident light intensity, represents the degree of polarization, Indicates the The output light intensity of each optical path is 、 Respectively represent the functional relationship between input parameters and polarized output light intensity; Step (5) combines the state equations and measurement equations of the microarray polarization camera parameters in steps (1) and (4) to establish an online calibration model for the microarray polarization camera parameters assisted by a star sensor; based on the characteristics of the model, the unscented Kalman filter method is used to online estimate the model parameters of each polarization unit in the microarray polarization camera to improve the night navigation accuracy and environmental adaptability of the polarization camera.

2. The method for online calibration of parameters of a micro-array polarization camera based on a star sensor according to claim 1, characterized in that: In the step (1), the light intensity gain coefficient of each polarization unit of the microarray polarization camera is , polarization coefficient , polarization direction angle As a state quantity ,in Represents the serial number of the polarization unit, , represents the first polarization unit optical path channel; The state quantity of each polarization unit is expressed as: , establish the state equation of polarization camera parameters ;in, is the state quantity Its first-order derivative The functional relationship between In each polarization unit of the microarray polarization camera, the model parameters can be approximately considered to be constant values ​​per unit time and are slowly varying state quantities. Therefore, the state equation can be expressed as: (1)。 3. The method for online calibration of parameters of a micro-array polarization camera based on a star sensor according to claim 1, characterized in that: In step (2), the star sensor is used to measure Individual carrier systems ( b Star vector under the system ,in ; Get the geographical coordinate system according to the astronomical calendar ( n System) Star vector information And moon vector information ; Based on the principle that the vector dot product remains unchanged under different coordinate systems, the equation is established , get the moon vector under the carrier system ; Further, according to b The coordinate system of each polarization unit ( The coordinate transformation relationship of the system is obtained Moon vector ; Define the following formula: (2) in, The matrix is ​​composed of and The angle between them; Based on the least squares method, the moon vector under the carrier system can be expressed as: (3) Furthermore, the coordinate system of each polarization unit in the microarray polarization camera is defined as System; According to the center point of the micro-array polarization camera and optical focal length , Department and b The coordinate transformation matrix of the system can be expressed as: (4) in, , , For the The center point coordinates of each polarization unit; therefore, Moon vector It can be expressed as: (5) in, Upper right corner is the transpose symbol.

4. The method for online calibration of parameters of a micro-array polarization camera based on a star sensor according to claim 1, wherein: In the step (3), Polarization vector under the system Perpendicular to the moon vector and the observation vector Based on the above relationship, the polarization vector Medium polarization azimuth With moon vector Functional relationship ;in, Indicates the polarization azimuth With moon vector The functional relationship between exist Under the system, the moon vector is , observation vector Based on the perpendicular relationship between the polarization vector, the observation vector and the moon vector, the polarization vector It can be expressed as: (6) According to formula (6), the polarization azimuth and The relationship can be expressed as: (7) in, Representative vector The mold length.

5. The method for online calibration of parameters of a micro-array polarization camera based on a star sensor according to claim 4, characterized in that: In the step (4), based on the first Model of a polarization unit , further combined with the polarization azimuth angle established in step (3) With moon vector The functional relationship of the camera model parameter measurement equation based on the polarization output light intensity is established. ;in, represents the incident light intensity, represents the degree of polarization, Indicates the The output light intensity of each optical path is 、 Respectively represent the functional relationship between input parameters and polarized output light intensity; Micro-array polarization camera The first polarization unit The optical path channel model is expressed as: (8) in, Indicates the output light intensity, represents the incident light intensity, represents the degree of polarization, Indicates the polarization azimuth; light intensity gain coefficient , polarization coefficient , polarization direction angle are the polarization camera model parameters to be estimated; The polarization azimuth in formula (7) With moon vector Substitute the relationship into formula (8) to establish the measurement equation based on the output light intensity of the optical path channel: (9) in, represents the measurement noise.

6. The method for online calibration of parameters of a micro-array polarization camera based on a star sensor according to claim 5, characterized in that: In the step (5), the state equations and measurement equations of the microarray polarization camera parameters in steps (1) and (4) are combined to establish an online calibration model of the microarray polarization camera parameters assisted by a star sensor; based on the characteristics of the model, the unscented Kalman filter method is used to online estimate the model parameters of each polarization unit in the microarray polarization camera, thereby improving the nighttime navigation accuracy and environmental adaptability of the polarization camera; Combining formulas (1) and (9), the online calibration model of micro-array polarization camera model parameters based on star-sensor assistance can be expressed as: (10)。

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