A method for attitude prediction type star tracking

Abstract

The present application relates to a kind of attitude prediction formula star tracking method, it is related to star sensor technical field.The method includes the following steps: obtaining historical angular velocity data;Predict the next frame angular velocity;Predict the next frame attitude quaternion;Project the sky area star to image plane;Window matching is carried out between projected star and the next frame observation star;Calculate the next frame accurate attitude quaternion;The target of window matching success is used for attitude solution, obtain the next frame accurate attitude;Repeat the above steps, realize autonomous star tracking.The attitude prediction formula star tracking method of the present application, by polynomial fitting historical angular velocity data, can quickly and accurately predict the next frame angular velocity, significantly improve real-time and accuracy;Can well adapt to large angular velocity maneuver, enhance the tracking ability of star sensor in complex dynamic environment;Reduce the dependence on external sensor, improve the independence and anti-interference ability of system, while simplifying the calculation process, improve overall computing efficiency.

Description

Technical Field

[0001] This invention relates to the field of star sensor technology, and in particular to an attitude prediction-based star tracking method. Background Technology

[0002] A star sensor is a high-precision astronomical navigation device primarily used for spacecraft attitude measurement. By identifying and tracking stars in the sky, a star sensor provides information about the spacecraft's current attitude, helping the navigation system achieve precise positioning and stable control. In modern space missions, star sensors are widely used for attitude control and navigation of satellites, space shuttles, and other manned or unmanned spacecraft.

[0003] Star sensors operate in two modes: initial attitude acquisition and star tracking. When a star sensor is disoriented in space, it operates in initial attitude acquisition mode, which has high computational complexity and poor real-time performance. Once initial attitude acquisition is successful, it enters star tracking mode. In star tracking mode, the star sensor can output real-time attitude information at a high data update rate. This high update frequency is particularly important for performing high-precision tasks, such as satellite communication, Earth observation, and deep space exploration, significantly improving the accuracy and effectiveness of mission execution. The core operation of the star sensor typically takes place in star tracking mode, which is crucial for ensuring the long-term stable attitude of the spacecraft.

[0004] Existing star tracking methods mainly include two types: one is to perform window matching by predicting the position of the star's center of mass, which performs poorly during high angular velocity maneuvers; the other is to rely on other sensors to provide attitude or angular velocity information for tracking, which increases the star sensor's dependence on external platforms and limits its autonomous operation capability.

[0005] In conclusion, it is particularly necessary to develop a star tracking method that can autonomously adapt to high angular velocity maneuvers in order to improve the reliability of star sensors in complex dynamic environments. Summary of the Invention

[0006] This invention aims to address the technical problems of poor performance of existing star tracking methods during high angular velocity maneuvers and excessive reliance of star sensors on external platforms, and provides an attitude prediction-based star tracking method.

[0007] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows:

[0008] An attitude prediction-based star tracking method includes the following steps:

[0009] Step 1: Obtain historical angular velocity data;

[0010] Extract the attitude quaternions from the historical N frames, and use the quaternion differential equations to obtain the required historical N frame angular velocity data through the correlation of time intervals;

[0011] Step 2: Fit the historical angular velocities to a second-order polynomial to predict the angular velocity in the next frame;

[0012] Polynomial fitting is performed on the angular velocity data of N historical frames to obtain the coefficients of the polynomial, and the obtained polynomial expression is used to predict the angular velocity of the next frame.

[0013] Step 3: Predict the pose quaternion for the next frame;

[0014] Based on the attitude quaternion of the current frame and the angular velocity of the next frame predicted by polynomial fitting, predict the attitude quaternion of the next frame.

[0015] Step 4: Project the stars of the sky onto the image plane;

[0016] Based on the predicted attitude quaternion for the next frame, the stars in the sky are projected onto the image plane;

[0017] Step 5: Match the projected star with the observed star in the next frame;

[0018] Step 6: Calculate the precise attitude quaternions for the next frame based on the successfully matched stars;

[0019] The target that is successfully matched by the window is used for pose calculation to obtain the accurate pose of the next frame;

[0020] Step 7: Repeat steps 1 to 6 to achieve autonomous satellite tracking.

[0021] In the above technical solution, step one specifically includes:

[0022] A quaternion Defined in the following form:

[0023]

[0024] in: = It is a quaternion. The real part; It is a quaternion. The imaginary part, For imaginary units;

[0025] The quaternion differential equation is:

[0026]

[0027] in, Representing quaternions from arrive Change express Quaternions of time, From arrive Angular velocity; then we have:

[0028]

[0029] Calculate the history using the above formula. Angular velocity data of the frame:

[0030] .

[0031] In the above technical solution, step two specifically involves:

[0032] Step 2.1 Use the least squares method to perform polynomial fitting on the angular velocity data of the historical N frames; taking second-order polynomial fitting as an example, the expression of the second-order polynomial function is:

[0033]

[0034] Using the least squares method for fitting, the sum of squared errors is expressed as:

[0035]

[0036] make If the minimum is:

[0037]

[0038] in, Denotes the independent variable of a second-order polynomial. Representing history Frame angular velocity measurement.

[0039] From the above formula, the coefficient matrix of the second-order polynomial is:

[0040]

[0041] Using the above formulas, the angular velocities of the three axes were respectively... , , Perform fitting;

[0042] Step 2.2 Using the polynomial expression obtained in Step 2.1, predict the triaxial angular velocity of the next frame:

[0043]

[0044] in, It is the value of the second-order polynomial independent variable, used to calculate the triaxial angular velocity of the next frame through the fitted function.

[0045] In the above technical solution, step three specifically involves:

[0046] The quaternion differential equation is expressed as:

[0047]

[0048] Depend on Time Quaternion predict Time Quaternion Represented as:

[0049]

[0050] in, It is the predicted quaternion for the next moment. It is the identity matrix. Represents the quaternion at the current time. Indicates the prediction from arrive The three-axis angular velocity, It's time.

[0051] In the above technical solution, step four specifically involves:

[0052] Step 4.1 Convert the attitude quaternion into a rotation matrix:

[0053]

[0054] Predict Time Quaternion Transform the above formula into a rotation matrix ;

[0055] Step 4.2 Project the star onto the image plane; given a star, its star vector in the inertial frame.

[0056] , , , Inertial frames of reference axis, axis, The coordinate values ​​on the axis; the vector transformed to the star sensor coordinate system is , , , In the star sensor coordinate system axis, axis, Coordinate values ​​on the axis;

[0057] but:

[0058]

[0059] The phase plane coordinates of the projected star are:

[0060]

[0061]

[0062] in, and Indicates the principal point of the camera. Indicates the angular distance of the camera. Indicates the pixel size. and Star vectors The coordinates projected onto the image plane.

[0063] In the above technical solution, step five specifically refers to:

[0064] Set a window matching threshold When the observed target Target_ and Target_ With the projected star, it satisfies:

[0065]

[0066] The stars were considered a match.

[0067] In the above technical solution, step six specifically involves: using the successfully matched target from the window for pose calculation to obtain... Precise attitude quaternion at time .

[0068] The present invention has the following beneficial effects:

[0069] The attitude prediction-based star tracking method of this invention, firstly, by fitting historical angular velocity data using polynomials, can quickly and accurately predict the angular velocity of the next frame, significantly improving real-time performance and accuracy; secondly, it can adapt well to high angular velocity maneuvers, enhancing the tracking capability of star sensors in complex dynamic environments; furthermore, it reduces dependence on external sensors, improving system independence and anti-interference capabilities, while simplifying the calculation process and improving overall computational efficiency. These advantages of the attitude prediction-based star tracking method of this invention will further promote the application and development of star sensors in modern aerospace missions. Attached Figure Description

[0070] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0071] Figure 1This is a schematic diagram of the steps of the attitude prediction star tracking method of the present invention. Detailed Implementation

[0072] The inventive concept of this invention is as follows:

[0073] The attitude prediction-based star tracking method of this invention achieves autonomous tracking mainly through the following steps: First, a polynomial fitting method is used to predict the angular velocity of the next frame based on historical angular velocity data. Then, the attitude of the next frame is calculated by combining the attitude quaternions of the current frame. Next, the predicted attitude is used to project stars in the sky onto the image plane, and the star positions are matched with the target measurement coordinates by the projected coordinates. Finally, the attitude is updated using the matching results to complete the tracking of the next frame. This method significantly improves the real-time performance and accuracy of star sensors under rapid maneuvering conditions and has good adaptability.

[0074] The present invention will now be described in detail with reference to the accompanying drawings.

[0075] like Figure 1 As shown, the attitude prediction-based star tracking method of the present invention is implemented by the following steps:

[0076] Step 1: Obtain historical angular velocity data.

[0077] The attitude quaternions of the current frame and the N frames preceding it are extracted. Using quaternion differential equations, the required angular velocity data for the previous N frames is obtained through the correlation of time intervals. The current frame and the N frames preceding it in the above description refer to the historical N frames. It should be noted that to obtain N frames of angular velocity data, N+1 frames of attitude quaternion data are needed (an angular velocity value can be calculated from every two adjacent frames of attitude quaternions). Therefore, the attitude quaternions extracted here are the sum of the previous N frames and the current frame.

[0078] A quaternion It can be defined in the following form:

[0079] (1)

[0080] in: = It is a quaternion. The real part; It is a quaternion. The imaginary part, This is a virtual part unit.

[0081] The first form of the quaternion differential equation is:

[0082] (2)

[0083] in, Representing quaternions from arrive Change express Quaternions of time, From arrive The three-axis angular velocities. Then we have:

[0084] (3)

[0085] Calculate the history using formula (3) Angular velocity data of the frame:

[0086] (4)

[0087] Step 2: Fit the historical angular velocities using a second-order polynomial to predict the angular velocity in the next frame.

[0088] The least squares method is used to perform polynomial fitting on the angular velocity data of N historical frames to obtain the coefficients of the polynomial, and the obtained polynomial expression is used to predict the angular velocity of the next frame.

[0089] Step 2.1 Use the least squares method to perform polynomial fitting on the angular velocity data of the historical N frames. Taking second-order polynomial fitting as an example, the expression of the second-order polynomial function is:

[0090] (5)

[0091] Using the least squares method for fitting, the sum of squared errors is expressed as:

[0092] (6)

[0093] make If the minimum is:

[0094] (7)

[0095] in, Denotes the independent variable of a second-order polynomial. Representing history Frame angular velocity measurement.

[0096] From formula (7), the coefficient matrix of the second-order polynomial is:

[0097] (8)

[0098] Using formula (8), the angular velocities of the three axes were respectively... , , Perform fitting.

[0099] Step 2.2 Using the polynomial expression obtained in Step 2.1, predict the triaxial angular velocity of the next frame:

[0100] (9)

[0101] in, It is the value of the second-order polynomial independent variable, used to calculate the triaxial angular velocity of the next frame through the fitted function.

[0102] Step 3: Predict the pose quaternion for the next frame.

[0103] Based on the attitude quaternion of the current frame and the angular velocity of the next frame predicted by polynomial fitting, predict the attitude quaternion of the next frame.

[0104] The second form of the quaternion differential equation is:

[0105] (10)

[0106] Depend on Time Quaternion predict Time Quaternion It can be represented as:

[0107] (11)

[0108] in, It is the predicted quaternion for the next moment. It is the identity matrix. Represents the quaternion at the current time. Indicates the prediction from arrive angular velocity, It's time.

[0109] Step 4: Project the stars in the sky onto the image plane.

[0110] Based on the predicted attitude quaternion for the next frame, the stars in the sky are projected onto the image plane.

[0111] Step 4.1 Convert the attitude quaternion into a rotation matrix:

[0112] (12)

[0113] The predicted prediction Time Quaternion Transform it into a rotation matrix using formula (12). .

[0114] Step 4.2 Project the star onto the image plane; given a star, its star vector in the inertial frame.

[0115] , , , Inertial frames respectively axis, axis, The coordinate values ​​on the axis; the vector transformed to the star sensor coordinate system is , , , In the star sensor coordinate system axis, axis, Coordinate values ​​on the axis;

[0116] but:

[0117] (13)

[0118] The phase plane coordinates of the projected star are:

[0119] (14)

[0120] (15)

[0121] in, and Indicates the principal point of the camera. Indicates the angular distance of the camera. Indicates the pixel size. and Star vector The coordinates projected onto the image plane.

[0122] Step 5: Match the projected star with the observed star in the next frame.

[0123] When performing window matching between the projected satellite and the observed target in the next frame, a window matching threshold is set. In this example, When the observed target Target_ and Target_ With the projected star, it satisfies:

[0124] (16)

[0125] The stars were considered a match.

[0126] Step 6: Calculate the precise attitude quaternion for the next frame based on the successfully matched stars.

[0127] The targets that are successfully matched by the window are used for attitude calculation to obtain... Precise attitude quaternion at time .

[0128] Step 7: Repeat steps 1 to 6 to achieve autonomous satellite tracking.

[0129] The attitude prediction-based star tracking method of this invention, firstly, by fitting historical angular velocity data using polynomials, can quickly and accurately predict the angular velocity of the next frame, significantly improving real-time performance and accuracy; secondly, it can adapt well to high angular velocity maneuvers, enhancing the tracking capability of star sensors in complex dynamic environments; furthermore, it reduces dependence on external sensors, improving system independence and anti-interference capabilities, while simplifying the calculation process and improving overall computational efficiency. These advantages of the attitude prediction-based star tracking method of this invention will further promote the application and development of star sensors in modern aerospace missions.

[0130] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. An attitude prediction-based star tracking method, characterized in that, Includes the following steps: Step 1: Obtain historical angular velocity data; Extract the attitude quaternions from the historical N frames, and use the quaternion differential equations to obtain the required historical N frame angular velocity data through the correlation of time intervals; Step 2: Fit the historical angular velocities to a second-order polynomial to predict the angular velocity in the next frame; Polynomial fitting is performed on the angular velocity data of N historical frames to obtain the coefficients of the polynomial, and the obtained polynomial expression is used to predict the angular velocity of the next frame. Step 3: Predict the pose quaternion for the next frame; Based on the attitude quaternion of the current frame and the angular velocity of the next frame predicted by polynomial fitting, predict the attitude quaternion of the next frame. Step 4: Project the stars of the sky onto the image plane; Based on the predicted attitude quaternion for the next frame, the stars in the sky are projected onto the image plane; Step 5: Match the projected star with the observed star in the next frame; Step 6: Calculate the precise attitude quaternions for the next frame based on the successfully matched stars; The target that is successfully matched by the window is used for pose calculation to obtain the accurate pose of the next frame; Step 7: Repeat steps 1 to 6 to achieve autonomous satellite tracking.

2. The attitude prediction-based star tracking method according to claim 1, characterized in that, Step one is as follows: A quaternion Defined in the following form: in: = It is a quaternion. The real part; It is a quaternion. The imaginary part, For imaginary units; The quaternion differential equation is: in, Representing quaternions from arrive Change express Quaternions of time, From arrive Angular velocity; then we have: Calculate the history using the above formula. Angular velocity data of the frame: 。 3. The attitude prediction-based star tracking method according to claim 1, characterized in that, Step two is as follows: Step 2.1 Use the least squares method to perform polynomial fitting on the angular velocity data of the historical N frames; taking second-order polynomial fitting as an example, the expression of the second-order polynomial function is: Using the least squares method for fitting, the sum of squared errors is expressed as: make If the minimum is: in, Denotes the independent variable of a second-order polynomial. Representing history Frame angular velocity measurement; From the above formula, the coefficient matrix of the second-order polynomial is: Using the above formulas, the angular velocities of the three axes were respectively... , , Perform fitting; Step 2.2 Using the polynomial expression obtained in Step 2.1, predict the triaxial angular velocity of the next frame: in, It is the value of the second-order polynomial independent variable, used to calculate the triaxial angular velocity of the next frame through the fitted function.

4. The attitude prediction-based star tracking method according to claim 1, characterized in that, Step three specifically involves: The quaternion differential equation is expressed as: Depend on Time Quaternion predict Time Quaternion Represented as: in, It is the predicted quaternion for the next moment. It is the identity matrix. Represents the quaternion at the current time. Indicates the prediction from arrive The three-axis angular velocity, It's time.

5. The attitude prediction-based star tracking method according to claim 1, characterized in that, Step four is as follows: Step 4.1 Convert the attitude quaternion into a rotation matrix: Predict Time Quaternion Transform the above formula into a rotation matrix ; Step 4.2 Project the star onto the image plane; given a star, its star vector in the inertial frame. , , , Inertial frames respectively axis, axis, The coordinate values ​​on the axis; the vector transformed to the star sensor coordinate system is , , , In the star sensor coordinate system axis, axis, Coordinate values ​​on the axis; but: The phase plane coordinates of the projected star are: in, and Indicates the principal point of the camera. Indicates the angular distance of the camera. Indicates the pixel size. and Star vectors The coordinates projected onto the image plane.

6. The attitude prediction-based star tracking method according to claim 1, characterized in that, Step five is as follows: Set a window matching threshold When the observed target Target_ and Target_ With the projected star, it satisfies: The stars were considered a match.

7. The attitude prediction-based star tracking method according to claim 1, characterized in that, Step six specifically involves using the successfully matched targets within the window for pose calculation to obtain... Precise attitude quaternion at time .

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