A method for determining the attitude of a vehicle based on polarization vector space difference

Abstract

The application provides a kind of based on polarization vector space difference navigation and attitude determination method, including steps, attitude misalignment angle, gyro drift, gyro scale factor error are regarded as state quantity, and system state equation is established;Two ommatidium polarization units in the polarization sensor of different observation directions are used to measure atmospheric polarization vector and difference, eliminate the common error generated by aerodynamic light, aerodynamic heat and other interference to polarization sensor in high altitude high dynamic environment;Polarization vector space difference information is regarded as measurement, and the measurement equation of attitude misalignment angle is established, and filter design is completed;Unscented Kalman filter method is used to estimate attitude misalignment angle, and the correction of carrier attitude and heading is realized.The navigation and attitude determination method based on polarization vector space difference provided by the application eliminates the common error of polarization sensor by using polarization vector space difference information of different observation directions, and improves the heading and attitude precision of polarization integrated navigation system in high altitude high dynamic environment.

Description

Technical Field

[0001] This invention belongs to the field of biomimetic polarization navigation, specifically involving a method for attitude determination based on polarization vector spatial difference. This method can eliminate the common error of polarization sensors caused by interference from aero-optics, aero-thermal, etc., and improve the heading and attitude accuracy of polarization combined navigation systems in high-altitude and high-dynamic environments. Background Technology

[0002] Many organisms in nature, such as dragonflies and bees, can obtain attitude and orientation information using their own polarization compasses and halteres. Inspired by this biological fusion mechanism, polarization / inertial navigation (INS) combinations have developed into a novel autonomous navigation method. Due to its advantages such as strong anti-interference capability and no radiation, polarization / INS combinations have attracted widespread attention in the field of autonomous navigation, meeting the requirements for high-precision, long-endurance autonomous navigation.

[0003] To improve the accuracy of polarization / inertial navigation system (INS) integration, many research institutions have conducted extensive research on polarization / INS fusion methods. Chinese patent application "A Bionic Polarization Autonomous Navigation Method Based on Polarization Degree Weighting" (application number: CN201911250920.8) sets the polarization vector weights obtained at an observation point based on the magnitude of the polarization degree. Based on the Rayleigh scattering principle, an INS / polarization integrated navigation system model is established. Chinese patent application "An EKF Alignment Method for an Inertial / Polarized Light Integrated Navigation System with Large Misalignment Angles" (application number: CN201911131570.3) calculates the solar vector using the polarization azimuth angle and establishes a nonlinear measurement equation for polarized light; based on the velocity output of the INS, a static base velocity error measurement equation is established; and then, augmentation techniques are used to establish a unified INS / polarized light integrated navigation system model. Chinese patent application "A Rigorous Polarization / Inertial Navigation Integration Method Based on Self-Learning Multi-Rate Residual Correction" (Application No.: CN202010329675.6) converts the heading angle output by the inertial navigation system into the azimuth angle of the carrier axis relative to the solar meridian and uses it as a state variable. The azimuth angle of the carrier axis relative to the solar meridian calculated by the polarization navigation system is used as an observation, and then the two data are fused. The polarization / inertial navigation fusion method described in the above-mentioned Chinese patent application has been well applied in ground and low-altitude environments, but it does not consider the common errors caused by aerodynamic light and heat interference at high altitudes to the polarization sensor, and does not achieve compensation and suppression of these common errors. To address these issues, how to eliminate the common errors caused by aerodynamic light and heat interference to the polarization sensor and further improve the attitude accuracy of polarization / inertial navigation fusion in high-altitude, high-dynamic environments urgently needs further research. Summary of the Invention

[0004] To address the aforementioned problems and overcome the shortcomings of existing technologies, this invention proposes a flight attitude determination method based on polarization vector spatial difference. The attitude misalignment angle, gyroscope drift, and gyroscope calibration factor error are used as state variables to establish the system's state equation. Spatial difference is performed using two polarization vectors from different observation directions in a simulated compound eye polarization sensor to obtain the polarization vector spatial difference component, eliminating the common error caused by aerodynamic light, aerodynamic heat, and other interferences on the polarization sensor. The polarization vector spatial difference information is used as a measurement to establish a measurement equation for the attitude misalignment angle, completing the design of the system filter. Finally, an unscented Kalman filter is used to estimate the attitude misalignment angle, achieving correction of the carrier's attitude and heading.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A method for determining attitude based on polarization vector spatial difference includes the following steps:

[0007] Step 1) Using attitude misalignment angle, gyroscope drift, and gyroscope calibration factor error as state variables, establish the system's state equation; the system state variables are: x = [φG b G s ] T 9×1 φ represents the three-dimensional attitude misalignment angle, G b Indicates gyroscope drift, G s This indicates the error of the three-axis scale factor of the gyroscope;

[0008] Step 2) To address the common error of polarization sensors caused by aerodynamic light and heat interference in high-altitude, high-dynamic environments, the polarization vectors measured by any two monocular polarization units in the simulated compound eye polarization sensor are subtracted to obtain the spatial difference component of the polarization vector. Eliminate the influence of common errors on polarization sensors;

[0009] Step 3) Utilize the spatial difference component of the polarization vector from Step 2) Based on the perpendicular relationship between the solar vector and the polarization vector, a mapping model with the attitude misalignment angle in the system state variables is established, and the system measurement equations are designed.

[0010] Step 4) Use unscented Kalman filtering to estimate the attitude misalignment angle, thereby correcting the carrier's attitude and heading.

[0011] Furthermore, in step 1), the state equation is expressed as:

[0012]

[0013] Where w represents the noise in the system state equations, and F is the state transition matrix, expressed as:

[0014] (2)

[0015] in, The rotation matrix of the geographic frame relative to the inertial frame in the geographic frame is represented by matrix A in the state transition matrix as follows:

[0016]

[0017] In matrix A Let G represent the ideal attitude transition matrix. x G y G z These represent the angular velocities measured by the gyroscope along the x, y, and z axes, respectively.

[0018] Furthermore, in step 2),

[0019] The polarization vector measured by any two monocular polarization units in a simulated compound eye polarization sensor is represented as: Spatial difference was performed on the polarization vectors of the two different observation directions to obtain:

[0020]

[0021] Where m1 and m2 represent two monocular polarization units, This represents the transformation matrix between the coordinate system containing m1 and the load system. This represents the transformation matrix between the coordinate system containing m2 and the load system.

[0022] Furthermore, in step 3), based on the perpendicular relationship between the solar vector and the polarization vector, the polarization vector measured by the monocular polarization unit m1 is... Establish a mapping model between attitude misalignment angle and attitude misalignment angle:

[0023]

[0024] Polarization vector measured by a single-eye polarization unit m2 The relationship between attitude misalignment angle and attitude misalignment angle is expressed as:

[0025]

[0026] in, This represents the attitude transformation matrix with errors. These represent the measurement noise corresponding to the measurement equations constructed by the monocular polarization units m1 and m2, respectively. and s represents the ideal polarization vector of monocular polarization units m1 and m2. n Indicates the solar vector in the navigation system;

[0027] Spatial difference is performed on equations (5) and (6) to establish the relationship between the spatial difference component of the polarization vector and the attitude misalignment angle:

[0028]

[0029] By rearranging equation (7), a measurement equation based on the spatial difference component of the polarization vector is established:

[0030]

[0031] in, Based on equation (8), the design of the system measurement equation is completed.

[0032] Further, in step 4), based on the characteristics of the system model, an unscented Kalman filter is used to estimate the attitude misalignment angle, enabling the correction of the carrier's attitude and heading using polarization vector space difference information in high-altitude, high-dynamic environments. The advantages of this invention compared to existing technologies are: For the first time, a method for determining attitude based on polarization vector space difference is proposed to address the common errors caused by aerodynamic light and heat interference to polarization sensors in high-altitude, high-dynamic environments. By utilizing the polarization vector space difference components in different observation directions, a measurement equation for the inertial navigation attitude misalignment angle is established, eliminating the influence of common errors on the polarization sensor, improving the system's estimation accuracy of the inertial navigation attitude misalignment angle, and thus enhancing the system's attitude accuracy. Attached Figure Description

[0033] Figure 1 This is a flowchart of an attitude determination method based on polarization vector spatial difference according to the present invention. Detailed Implementation

[0034] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the protection scope of the present invention.

[0035] Interferences such as aero-optical light and aero-thermal radiation in high-altitude, high-dynamic environments can affect the measurement accuracy of polarization sensors, and consequently, the accuracy of the polarization / inertial navigation system (INS) combination. To address this issue, this invention proposes a flight attitude determination method based on polarization vector spatial difference. The attitude misalignment angle, gyroscope drift, and gyroscope calibration factor error are used as state variables to establish the system's state equation. Spatial difference is performed between two polarization vectors in different observation directions of the simulated compound eye polarization sensor to obtain the polarization vector spatial difference component, eliminating the common error caused by aero-optical light and aero-thermal radiation to the polarization sensor. The polarization vector spatial difference information is used as a measurement to establish a measurement equation for the attitude misalignment angle, completing the design of the system filter. Finally, an unscented Kalman filter is used to estimate the attitude misalignment angle, enabling correction of the carrier's attitude and heading, and improving the system's attitude accuracy in high-altitude, high-dynamic environments.

[0036] like Figure 1 As shown, the specific implementation steps of the attitude determination method based on polarization vector spatial difference of the present invention are as follows:

[0037] Step 1) Using attitude misalignment angle, gyroscope drift, and gyroscope calibration factor error as state variables, establish the system's state equation. State variable: x = [φG b G s ] T 9×1 φ represents the three-dimensional attitude misalignment angle, G b Indicates gyroscope drift, G s This indicates the error of the three-axis scale factor of the gyroscope.

[0038] The state equation can be expressed as:

[0039]

[0040] Where w represents the noise in the system state equations, and F is the state transition matrix, which can be expressed as:

[0041] (2)

[0042] in, The rotation matrix of the geographic frame relative to the inertial frame in the geographic frame can be represented as:

[0043]

[0044] In matrix A Let G represent the ideal attitude transition matrix. x G y G z These represent the angular velocities measured by the gyroscope along the x, y, and z axes, respectively.

[0045] Step 2) To address the common error of polarization sensors caused by aerodynamic light and heat interference in high-altitude, high-dynamic environments, the polarization vectors measured by any two monocular polarization units in the simulated compound eye polarization sensor are subtracted to obtain the spatial difference component of the polarization vector. Eliminate the influence of common errors on polarization sensors.

[0046] The polarization vector measured by any two monocular polarization units in a compound eye-like polarization sensor can be expressed as: Spatial difference analysis of the polarization vectors in the two different observation directions yields:

[0047]

[0048] Where m1 and m2 represent two monocular polarization units, This represents the transformation matrix between the coordinate system containing m1 and the load system. This represents the transformation matrix between the coordinate system containing m2 and the load system.

[0049] Step 3) Utilize the spatial difference component of the polarization vector from Step 2) Based on the perpendicular relationship between the solar vector and the polarization vector, a mapping model with the attitude misalignment angle in the system state variables is established, and the system measurement equations are designed.

[0050] Based on the perpendicular relationship between the solar vector and the polarization vector, the polarization vector measured by the monocular polarization unit m1 is... A mapping model between attitude misalignment angles can be established:

[0051]

[0052] Polarization vector measured by a single-eye polarization unit m2 The relationship between attitude misalignment angle and attitude misalignment angle can be expressed as:

[0053]

[0054] in, This represents the attitude transformation matrix with errors. These represent the measurement noise corresponding to the measurement equations constructed by the monocular polarization units m1 and m2, respectively. and This represents the ideal polarization vectors of monocular polarization units m1 and m2.

[0055] Spatial difference is performed on equations (5) and (6) to establish the relationship between the spatial difference component of the polarization vector and the attitude misalignment angle:

[0056]

[0057] By rearranging formula (7), a measurement equation based on the spatial difference component of the polarization vector is established:

[0058]

[0059] in, Based on formula (8), the system measurement equations are designed.

[0060] Step 4) Based on the characteristics of the system model, the attitude misalignment angle is estimated using the unscented Kalman filter method to correct the carrier's attitude and heading.

[0061] The above description is merely a preferred embodiment of the present invention, and the scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principle of the present invention should be considered within the scope of protection of the present invention. Contents not described in detail in this specification are common knowledge to those skilled in the art.

Claims

1. A method for determining the attitude of a vehicle based on polarization vector space difference, characterized in that, Includes the following steps: Step 1), attitude misalignment angle, gyro drift, and gyro scale factor error are taken as state variables to establish the state equation of the system; the state variables of the system are: , represents the three-dimensional attitude misalignment angle, represents the gyro drift, represents the gyro three-axis scale factor error; the state equation is represented as: (1) in, The noise representing the system state equation, The state transition matrix is ​​expressed as: (2) in, The matrix representing the rotation of the geographic frame relative to the inertial frame within the geographic frame, and the matrix in the state transition matrix. Represented as: (3) In the matrix Represents the ideal attitude transition matrix. These represent the angular velocities measured by the gyroscope along the x, y, and z axes, respectively. Step 2) To address the common error of polarization sensors caused by aerodynamic light and heat interference in high-altitude, high-dynamic environments, the polarization vectors measured by any two monocular polarization units in the simulated compound eye polarization sensor are subtracted to obtain the spatial difference component of the polarization vector. To eliminate the influence of common errors on the polarization sensor; the polarization vector measured by any two monocular polarization units in the simulated compound eye polarization sensor is expressed as: Spatial difference analysis of the polarization vectors in the two different observation directions yields: (4) in, and These represent two monocular polarization units. express The transformation matrix between the coordinate system and the carrier system. express The transformation matrix between the coordinate system in which it is located and the system of carriage; Step 3) Utilize the spatial difference component of the polarization vector from Step 2) Based on the perpendicular relationship between the solar vector and the polarization vector, a mapping model with the attitude misalignment angle in the system state variables is established, and the system measurement equations are designed. Based on the perpendicular relationship between the solar vector and the polarization vector, a monocular polarization unit... Measured polarization vector Establish a mapping model between attitude misalignment angle and attitude misalignment angle: (5) Monocular polarization unit Measured polarization vector The relationship between attitude misalignment angle and attitude misalignment angle is expressed as: (6) in, This represents the attitude transformation matrix with errors. , They represent and Measurement noise corresponding to the measurement equation constructed by a single-eye polarization unit. and express and The ideal polarization vector of a monocular polarization unit Indicates the solar vector in the navigation system; Spatial difference is performed on equations (5) and (6) to establish the relationship between the spatial difference component of the polarization vector and the attitude misalignment angle: (7) By rearranging equation (7), a measurement equation based on the spatial difference component of the polarization vector is established: (8) in, Based on equation (8), the system measurement equations are designed. Step 4) Use unscented Kalman filtering to estimate the attitude misalignment angle, thereby correcting the carrier's attitude and heading.

2. The attitude determination method based on polarization vector spatial difference according to claim 1, characterized in that: In step 4), based on the characteristics of the system model, the attitude misalignment angle is estimated using the unscented Kalman filter method, so as to realize the correction of the carrier attitude and heading by using the polarization vector spatial difference information in high-altitude and high-dynamic environments.

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