An In-orbit Calibration Method and Device for the Center-of-mass Offset of an Inertial Sensor

Abstract

The present invention relates to the technical field of data processing, and discloses a method and device for on-orbit calibration of the centroid offset of an inertial sensor. The method includes: obtaining the angular velocity and angular acceleration of the spacecraft after maneuvering through the inertial sensor; constructing a measurement observation model by using the angular velocity and angular acceleration of the spacecraft; processing the measurement observation model through a pre-constructed Kalman filter to obtain a predicted centroid offset; and calculating based on the predicted centroid offset and the acceleration output by the inertial sensor to obtain a calibration result of the centroid offset between the centroid of the inertial sensor and the center of gravity of the spacecraft. Through the above steps, the calibration of the centroid offset can be achieved within the short-period maneuver of the spacecraft. By means of one maneuver, the centroid offset and other parameters that need to be calibrated on orbit are calibrated simultaneously, reducing the maneuver cost.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and particularly to a method and device for on-orbit calibration of the centroid offset of an inertial sensor. Background Art

[0002] Traditional parameter calibration methods have been widely used in previous work. However, for the new scientific missions and design layouts of some special spacecraft, traditional methods are no longer applicable. Recently, the method for centroid calibration of the GRACE satellite is to apply an appropriate periodic magnetic torque to the satellite without the aid of thruster torque to drive the satellite. After obtaining the attitude quaternion simulation data and magnetometer data simulated by the accelerometer, the minimum variance estimation algorithm is used for data processing. Different from previous related work, due to the long distance from the Earth, some special spacecraft cannot utilize the Earth's magnetic field to drive the magnetometer, and the environmental noise they face also needs to be re-evaluated. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a method and device for on-orbit calibration of the centroid offset of an inertial sensor to solve the problem that traditional parameter calibration methods are no longer applicable to the new scientific missions and design layouts of some special spacecraft.

[0004] In a first aspect, an embodiment of the present invention provides a method for on-orbit calibration of the centroid offset of an inertial sensor, where the inertial sensor is disposed on a spacecraft, and the method includes:

[0005] Obtaining the angular velocity and angular acceleration of the spacecraft after maneuvering through the inertial sensor;

[0006] Constructing a measurement observation model using the angular velocity and angular acceleration of the spacecraft;

[0007] Processing the measurement observation model through a pre-constructed Kalman filter to obtain a predicted centroid offset;

[0008] Calculating based on the predicted centroid offset and the acceleration output by the inertial sensor to obtain a calibration result of the centroid offset between the centroid of the inertial sensor and the center of gravity of the spacecraft.

[0009] In an embodiment of the present application, the obtaining the angular velocity and angular acceleration of the spacecraft after maneuvering through the inertial sensor includes:

[0010] Detecting the attitude signal of the test mass generated by the inertial sensor, where the attitude signal is generated by the inertial sensor after the spacecraft maneuvers;

[0011] Analyzing the attitude signal to obtain the angular velocity and angular acceleration of the spacecraft.

[0012] In the embodiment of the present application, the measurement and observation model is as follows:

[0013]

[0014] Wherein, , The linear acceleration term of the non-conservative force acceleration coupled with the test mass can be processed by eliminating the linear trend.

[0015] In the embodiment of the present application, processing the measurement and observation model through a pre-constructed Kalman filter to obtain an estimated centroid offset includes:

[0016] Obtaining the working parameters of the Kalman filter and determining the update equation of the Kalman filter, wherein the working parameters include state variables, initial state estimates, and covariance matrices;

[0017] Preprocessing the angular velocity and the angular acceleration to obtain the processed angular velocity and angular acceleration;

[0018] Initializing the state variables and covariance matrices of the Kalman filter and using the initialized state variables and system model for prediction to obtain a prediction result;

[0019] Comparing the preprocessed angular velocity and angular acceleration with the prediction result to obtain a comparison result, and calculating the Kalman gain using the comparison result;

[0020] Calculating the updated values of the state variables and the updated values of the covariance matrix using the Kalman gain and the update equation;

[0021] Determining the estimated centroid offset based on the updated values of the state variables and the updated values of the covariance matrix.

[0022] In the embodiment of the present application, the formula of the Kalman filter is as follows:

[0023]

[0024]

[0025] is the state transition matrix during the prediction process, is the gain of the input U, W is the estimated process noise, V is the measurement noise, wherein the measured value Y, the estimated quantity , the observation matrix H, and the observation matrix H is:

[0026]

[0027]

[0028] 。

[0029] In the embodiment of the present application, the calibration result of the centroid offset between the centroid of the inertial sensor and the center of gravity of the spacecraft obtained by calculating based on the estimated centroid offset and the acceleration output by the inertial sensor includes:

[0030] Obtain the acceleration actually output by the inertial sensor currently;

[0031] Perform a de-linearization trend process on the acceleration to obtain the processed acceleration;

[0032] Obtain the linear acceleration caused by the estimated centroid offset;

[0033] Determine the difference between the processed acceleration and the linear acceleration, and determine the actual value of the centroid offset according to the difference;

[0034] Determine the calibration result of the centroid offset between the centroid of the inertial sensor and the center of gravity of the spacecraft according to the actual value of the centroid offset.

[0035] In the embodiment of the present application, the method further includes:

[0036] Collect the acceleration data output by the inertial sensor, and analyze the acceleration data to obtain a noise analysis result;

[0037] Determine the acceleration noise term coupled with the centroid offset according to the calibration result of the centroid offset and the noise analysis result;

[0038] Eliminate or reduce the acceleration noise term in the acceleration data to obtain the processed acceleration data, and evaluate the acceleration noise level corresponding to the processed acceleration data; if the acceleration noise level meets the preset conditions, use the processed acceleration data as the output.

[0039] In a second aspect, an on-orbit calibration device for the centroid offset of an inertial sensor provided by an embodiment of the present invention includes:

[0040] An acquisition module, configured to acquire the angular velocity and angular acceleration of the spacecraft after maneuvering through the inertial sensor;

[0041] A construction module, configured to construct a measurement observation model by using the angular velocity and angular acceleration of the spacecraft;

[0042] A processing module, configured to process the measurement observation model through a pre-constructed Kalman filter to obtain an estimated centroid offset;

[0043] A calibration module, configured to calculate based on the estimated centroid offset and the acceleration output by the inertial sensor, so as to obtain a calibration result of the centroid offset between the centroid of the inertial sensor and the center of gravity of the spacecraft.

[0044] In a third aspect, an embodiment of the present invention provides an electronic device, including: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to execute the method according to the first aspect or any corresponding implementation manner thereof.

[0045] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the method according to the first aspect or any corresponding implementation manner thereof.

[0046] In the embodiments of the present application, an inertial sensor can generally measure the angular velocity and angular acceleration of a spacecraft in different axes. These measurement values provide information about the rotational motion of the spacecraft. Based on the kinematic principles of the spacecraft, the angular velocity and angular acceleration can be related to the attitude changes of the spacecraft. Taking the angular velocity and angular acceleration as inputs, a measurement observation model is constructed to describe the attitude motion of the spacecraft. A Kalman filter processes the output of the measurement observation model to estimate the centroid offset. Then, the Kalman filter uses the previous estimate and the current measurement to continuously update and optimize the prediction of the centroid offset. Through filtering processing, the influence of measurement noise and uncertainty can be reduced, and the accuracy of the estimate can be improved. Finally, by combining the predicted centroid offset with the acceleration output by the inertial sensor, the centroid offset between the centroid of the inertial sensor and the center of gravity of the spacecraft can be further calculated. This calibration result can be used in subsequent navigation and control systems to improve the attitude control accuracy and stability of the spacecraft. Through the above steps, the calibration of the centroid offset can be achieved within the short-period maneuver of the spacecraft. By one maneuver, the centroid offset and other parameters that need to be calibrated on orbit are calibrated simultaneously, reducing the maneuver cost. Description of the Drawings

[0047] In order to more clearly illustrate the specific implementation manners of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific implementation manners or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0048] Figure 1 It is a schematic flowchart of a method for on-orbit calibration of the centroid offset of an inertial sensor according to some embodiments of the present invention;

[0049] Figure 2 Schematic diagram of the total torque signal according to some embodiments of the present invention;

[0050] Figure 3 Schematic diagram of the measured signal corresponding to the angular velocity according to some embodiments of the present invention;

[0051] Figure 4 Schematic diagram of the measured signal corresponding to the angular acceleration according to some embodiments of the present invention;

[0052] Figure 5 Schematic diagram of the centroid offset estimated by the Kalman filter according to some embodiments of the present invention;

[0053] Figure 6 Schematic diagram of the comparison between the calibrated centroid offset and the true value according to some embodiments of the present invention;

[0054] Figure 7 Block diagram of the on-orbit calibration device for the centroid offset of the inertial sensor according to an embodiment of the present invention;

[0055] Figure 8 Schematic diagram of the hardware structure of the electronic device according to an embodiment of the present invention. Detailed implementation manners

[0056] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0057] According to an embodiment of the present invention, there is provided a method and device for on-orbit calibration of the centroid offset of an inertial sensor. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0058] In this embodiment, there is provided a method for on-orbit calibration of the centroid offset of an inertial sensor, Figure 1 which is a flowchart of a method for on-orbit calibration of the centroid offset of an inertial sensor according to an embodiment of the present invention. As Figure 1 shown, the process includes the following steps:

[0059] Step S11, obtaining the angular velocity and angular acceleration of the spacecraft after maneuvering through the inertial sensor.

[0060] In the embodiments of the present application, the spacecraft is targeted at the Taiji-2 satellite. Since the Taiji-2 satellite cannot utilize the Earth's magnetic field to drive the magnetic torquer, the environmental noise it faces also needs to be reconsidered. In terms of accuracy requirements, the acceleration noise index of the Taiji-2 is 10 -14 ms -2 / Hz 1 / 2 order of magnitude, which is much higher than the requirement of 3 10 -9 ms -2 / Hz 1 / 2 for the Taiji-1. The Taiji-2 adopts a brand-new design layout, and two sets of inertial sensor systems are set on each satellite. Therefore, in an ideal situation, there is a deviation of about 0.1 m in the sensitive axis direction between the centroid of the test mass and the centroid of the satellite. Therefore, the present application provides an on-orbit parameter calibration scheme for the inertial sensors of the Taiji-2.

[0061] In the embodiments of the present application, the angular velocity and angular acceleration of the spacecraft after maneuvering are obtained through the inertial sensors, including: detecting the attitude signal of the test mass generated by the inertial sensor, where the attitude signal is generated by the inertial sensor after the spacecraft maneuvers; and analyzing the attitude signal to obtain the angular velocity and angular acceleration of the spacecraft.

[0062] Specifically, since there are two sets of inertial sensor systems in the Taiji-2, there is a deviation of 0.1 m in the sensitive axis direction between the test mass block in each set of inertial sensor systems and the satellite center in design. Due to the existence of the electrostatic suspension system, the test mass makes synchronous attitude movement with the spacecraft. Therefore, the angular velocity and angular acceleration of the test mass also generate attitude movements with the same magnitudes as the angular velocity and angular acceleration of the spacecraft. Through a maneuver of the satellite, the front-end electronics model of the inertial sensor records the attitude signal of the test mass. Analyzing these signals can obtain the angular velocity and angular acceleration of the spacecraft. For example, by processing and analyzing the data measured by the accelerometer and gyroscope, the angular velocity and angular acceleration of the spacecraft can be calculated.

[0063] It should be noted that the Taiji program plans to form an equilateral triangle gravitational wave detection satellite group with three satellites orbiting the sun in an orbit about 50 million kilometers away from the Earth. Since it is far from the Earth, the Earth's magnetic field cannot be used to drive the magnetic torquer. Therefore, three groups of micro-thrusters are used to drive a single satellite. The thrust range of the micro-thruster is 2 to 100 micronewtons, and the thrust resolution is 0.1 micronewton. According to the rigid body rotation law, torques in the order of about 10 to the power of negative 6 newton meters to 10 to the power of negative 4 newton meters can be generated.

[0064] Step S12, constructing a measurement observation model by using the angular velocity and angular acceleration of the spacecraft.

[0065] In the embodiments of the present application, the measurement observation model is as follows:

[0066] 。

[0067] Among them:

[0068] , The linear term of the acceleration coupling the non-conservative force acceleration and the test mass can be processed by eliminating the linear trend.

[0069] It should be noted that the attitude motion of the spacecraft will cause the test mass to be subjected to a coupling acceleration by means of the center-of-mass offset vector which can be expressed as:

[0070] 。

[0071] At this time, the actual output acceleration of the inertial sensor:

[0072] 。

[0073] Among them, is the gravitational gradient acceleration received by the satellite. Since Taiji-2 orbits the sun at a relatively far distance from the earth, the accelerometer measurement model ignores the perturbations caused by solid earth tides, ocean tides, etc. is the non-conservative force acceleration received by the test mass, including atmospheric drag, solar radiation pressure, and earth radiation pressure, etc., which can be approximated by a linear function of time. The above gives the components of the linear acceleration of the test mass when there is a center-of-mass offset. The accelerometer observation model can be simplified as:

[0074] 。

[0075] Step S13, process the measurement observation model through a pre-constructed Kalman filter to obtain a predicted center-of-mass offset.

[0076] In the embodiment of the present application, processing the measurement observation model through a pre-constructed Kalman filter to obtain a predicted center-of-mass offset includes: obtaining the working parameters of the Kalman filter, and determining the Kalman filter update equation, where the working parameters include state variables, initial state estimates, and covariance matrices; preprocessing the angular velocity and angular acceleration to obtain the processed angular velocity and angular acceleration; initializing the state variables and covariance matrices of the Kalman filter, and using the initialized state variables and system model for prediction to obtain a prediction result; comparing the preprocessed angular velocity and angular acceleration with the prediction result to obtain a comparison result, and calculating the Kalman gain using the comparison result; calculating the updated values of the state variables and the updated values of the covariance matrices using the Kalman gain and the update equation; determining the predicted center-of-mass offset based on the updated values of the state variables and the updated values of the covariance matrices.

[0077] It should be noted that after obtaining the satellite angular velocity and angular acceleration signals, a Kalman filter is constructed to calibrate the centroid offset:

[0078] .

[0079] .

[0080] is the state transition matrix during the prediction process, is the gain of the input U, W is the estimated process noise, V is the measurement noise, where the measured value is Y, the estimated quantity , and the observation matrix H, the observation matrix H is:

[0081] .

[0082] .

[0083]

[0084] Because the centroid offset has no dynamic characteristics, so , .

[0085] Posteriori estimation:

[0086] .

[0087] Specifically, first, initialize the working parameters of the Kalman filter, select appropriate state variables to describe the system. For example, when modeling the angular velocity and angular acceleration, they can be selected as state variables. Estimate the initial state of the system, such as the initial angular velocity and initial angular acceleration. Initialize the covariance matrix, which represents the uncertainty of the state variables. Secondly, preprocess the angular velocity and angular acceleration, such as removing noise, filtering, etc., to obtain the processed angular velocity and angular acceleration. At the same time, use the initial state estimate as the state variable of the Kalman filter. Initialize the covariance matrix to an appropriate value.

[0088] Then, use the initialized state variables and the system model for prediction, that is, according to the system model, use the current state variables to predict the state at the next moment. Calculate the covariance matrix of the prediction result. Calculate the difference between the preprocessed angular velocity and angular acceleration and the prediction result. Calculate the Kalman gain using the comparison result, the Kalman gain:

[0089] .

[0090] Finally, the updated values of the state variables and the updated value of the covariance matrix are calculated using the Kalman gain and the update equations, and the estimated centroid offset is determined based on the updated values of the state variables and the covariance matrix. Update the error covariance matrix:

[0091] 。

[0092] Step S14: Based on the calculation of the estimated centroid offset and the acceleration output by the inertial sensor, obtain the calibration result of the centroid offset between the centroid of the inertial sensor and the center of gravity of the spacecraft.

[0093] In the embodiment of the present application, based on the calculation of the estimated centroid offset and the acceleration output by the inertial sensor, obtaining the calibration result of the centroid offset between the centroid of the inertial sensor and the center of gravity of the spacecraft includes: obtaining the acceleration actually output by the inertial sensor currently; performing a detrending process on the acceleration to obtain the processed acceleration; obtaining the linear acceleration caused by the estimated centroid offset; determining the difference between the processed acceleration and the linear acceleration, and determining the actual value of the centroid offset according to the difference; and determining the calibration result of the centroid offset between the centroid of the inertial sensor and the center of gravity of the spacecraft according to the actual value of the centroid offset.

[0094] Specifically, multiple inertial sensors are installed on the structure of the spacecraft to ensure that the three components of acceleration can be measured. Determine the reference coordinate system and inertia characteristics of the spacecraft. Use the inertial sensors to measure the acceleration of the structure and record the measurement data. These data will serve as the basis for subsequent analysis. Obtain the acceleration data actually output by the inertial sensor currently. Then perform a detrending process on the acceleration data to remove the linear trend caused by gravity and other external forces to obtain more accurate acceleration data. Use low-pass filtering, high-pass filtering or other appropriate filtering techniques to filter the acceleration data. According to the design model of the spacecraft, analyze the possible offset situations of the centroid, and combine information such as mass distribution and rotational inertia to generate a model for estimating the centroid offset acceleration. Then use mathematical modeling, finite element analysis or other methods to calculate the acceleration data caused by the estimated centroid offset. And calculate the difference between the accelerations based on the processed acceleration data and the estimated centroid offset acceleration.

[0095] Finally, use the improved least squares method or other appropriate algorithms to analyze and process the acceleration difference, and store the processing result in a variable. By calculating the difference value, the actual value of the centroid offset can be obtained and aligned with the reference coordinate system.

[0096] In an embodiment of the present application, the method further includes: collecting acceleration data output by an inertial sensor, and analyzing the acceleration data to obtain a noise analysis result; determining an acceleration noise term coupled with the centroid offset according to the calibration result of the centroid offset and the noise analysis result; eliminating or reducing the acceleration noise term in the acceleration data to obtain processed acceleration data, and evaluating the acceleration noise level corresponding to the processed acceleration data; if the acceleration noise level meets a preset condition, using the processed acceleration data as an output.

[0097] Specifically, after the acceleration data is collected, it needs to be analyzed to determine the characteristics and level of the noise. This can be achieved by using various noise analysis techniques, such as time-domain analysis, frequency-domain analysis, or statistical analysis, etc. The result of the noise analysis will help to understand information such as the type, amplitude, and frequency distribution of the noise. Since in some cases, the centroid offset may cause additional acceleration noise. By calibrating the centroid offset and combining the noise analysis result, the acceleration noise term related to the centroid offset can be determined. These noise terms may be caused by mechanical vibrations, friction, or other factors due to the centroid offset. When the acceleration noise term coupled with the centroid offset is determined, corresponding measures can be taken to eliminate or reduce these noises. This includes using filtering techniques, digital signal processing algorithms, or other noise cancellation methods. By processing the acceleration data, the influence of the noise on the data can be reduced or eliminated, improving the quality and accuracy of the data.

[0098] After the noise elimination or reduction process, the processed acceleration data is obtained. At this time, it is necessary to evaluate the acceleration noise level of the processed data to determine whether it meets the preset conditions. Various evaluation indicators can be used, such as the root mean square (RMS) of the noise, the signal-to-noise ratio (SNR), or other relevant indicators to evaluate the noise level. If the acceleration noise level of the processed data meets the preset conditions, then these data can be considered reliable and can be used as an output for subsequent applications or analysis. If the noise level does not meet the conditions, it may be necessary to further optimize the processing method or re-evaluate the performance of the system.

[0099] In the embodiments of the present application, an inertial sensor can generally measure the angular velocity and angular acceleration of a spacecraft in different axial directions. These measured values provide information on the rotational motion of the spacecraft. Based on the kinematic principles of the spacecraft, the angular velocity and angular acceleration can be related to the attitude changes of the spacecraft. Taking the angular velocity and angular acceleration as inputs, a measurement observation model is constructed to describe the attitude motion of the spacecraft. A Kalman filter processes the output of the measurement observation model to estimate the centroid offset. Then, the Kalman filter uses the previous estimate and the current measurement to continuously update and optimize the prediction of the centroid offset. Through filtering processing, the influence of measurement noise and uncertainty can be reduced, and the accuracy of the estimate can be improved. Finally, by combining the predicted centroid offset with the acceleration output by the inertial sensor, the centroid offset between the centroid of the inertial sensor and the center of gravity of the spacecraft can be further calculated. This calibration result can be used in subsequent navigation and control systems to improve the attitude control accuracy and stability of the spacecraft. Through the above steps, the calibration of the centroid offset can be achieved within the short-period maneuver of the spacecraft. By one maneuver, the centroid offset and other parameters that need to be calibrated on orbit are calibrated simultaneously, reducing the maneuver cost.

[0100] The following is a complete example. Using the short-period maneuver of a satellite (the maneuver duration is taken as 250 s), the micro-thrusters of Taiji-2 swing the satellite to generate: a square-wave attitude maneuver signal with an amplitude of 10 -6 N·m magnitude, simulating the ringing phenomenon of signal instantaneous transition caused by impedance mismatch of the transmission line. In the space environment, it is expected that the noise amplitude of the micro-thruster within the measured frequency band is 10 - 7 N·m magnitude, causing slight jitter in the amplitude and duty cycle of the signal, plus slight line drift and ramp to simulate the instability caused by fuel supply and control system errors during the micro-thruster maneuver. Based on this, substituting into the dynamic equation of the satellite maneuver, the overall torque signal obtained is as Figure 2 shown.

[0101] It should be noted that the overall torque signal is a signal used to simulate the total torque generated during the satellite maneuver. It mainly considers the swing of the micro-thruster and the associated noise and instability. This signal is mainly used to analyze and study the dynamic characteristics of the satellite during the maneuver. When the satellite maneuvers, the overall torque signal will affect the attitude of the satellite. The inertial sensor can sense the attitude change of the satellite and generate corresponding attitude signals.

[0102] Then, the angular velocity (as Figure 3 shown) and angular acceleration ( Figure 4 shown) are determined according to the attitude signal of the inertial sensor. The inertial sensor measures the angular velocity and angular acceleration , thus constructing an accelerometer observation model.

[0103] After obtaining the satellite angular velocity and angular acceleration signals, a Kalman filter is constructed for the calibration of the centroid offset:

[0104] 。

[0105] 。

[0106] is the state transition matrix during the prediction process, is the gain of the input U, W is the estimated process noise, V is the measurement noise, where the measured value is Y, the estimated quantity , the observation matrix H, and the observation matrix H is:

[0107]

[0108]

[0109]

[0110] Because the centroid offset has no dynamic characteristics, so , 。

[0111] During the calibration process, the variables that need to be iteratively updated are:

[0112] Kalman gain:

[0113] 。

[0114] Posterior estimate:

[0115] 。

[0116] Update the error covariance matrix:

[0117] 。

[0118] After performing Kalman filter estimation, the centroid offset is obtained. As Figure 5 shown, Figure 5 gives the calibration result of the centroid offset , and the corresponding centroid offset records are as follows:

[0119] Table 1 - Comparison between the true value and the calibration result of the centroid offset

[0120]

[0121] Using the short-period maneuver of the spacecraft (the maneuver duration is 250 s), the inertial sensors are obtained Calibration results of the centroid offset of the axis. The calibrated results are as Figure 6 shown. The simulated three-axis calibration accuracy of the centroid offset of Taiji-2 is about 10 µm.

[0122] In the actual output acceleration of the inertial sensor, the non-conservative force acceleration mainly dominated by solar radiation pressure is the leading term noise amplitude of 10 -8 ms -2 order of magnitude. The maneuver time window is limited within 250 s to maintain the linear characteristics of the non-conservative force, and the de-linearization trend processing is performed on the linear acceleration readout signal of the inertial sensor. The processed signal is compared with the linear acceleration caused by the centroid offset estimated by the Kalman filter. After completing the calibration of the centroid offset, the identification and elimination of the centroid offset coupling acceleration noise term of the inertial sensor can be carried out according to the calibration results, and then the acceleration noise level of the inertial sensor during calibration can be reduced to the bottom noise of the inertial sensor.

[0123] In this embodiment, an on-orbit calibration device for the centroid offset of an inertial sensor is also provided. This device is used to implement the above-mentioned embodiments and preferred implementation manners, and those that have been described will not be repeated. As used hereinafter, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0124] This embodiment provides an on-orbit calibration device for the centroid offset of an inertial sensor, as Figure 7 shown, including:

[0125] An acquisition module 71, configured to obtain the angular velocity and angular acceleration of the spacecraft after maneuvering through an inertial sensor;

[0126] A construction module 72, configured to construct a measurement observation model by using the angular velocity and angular acceleration of the spacecraft;

[0127] A processing module 73, configured to process the measurement observation model through a pre-constructed Kalman filter to obtain a predicted centroid offset;

[0128] A calibration module 74, configured to calculate based on the predicted centroid offset and the acceleration output by the inertial sensor to obtain the calibration result of the centroid offset between the centroid of the inertial sensor and the center of gravity of the spacecraft.

[0129] In the embodiment of the present application, the acquisition module 71 is configured to detect the attitude signal of the test mass generated by the inertial sensor, where the attitude signal is generated by the inertial sensor after the spacecraft maneuvers; and analyze the attitude signal to obtain the angular velocity and angular acceleration of the spacecraft.

[0130] In the embodiment of the present application, the measurement observation model is as follows:

[0131] 。

[0132] Among them, , the linear acceleration term of the non-conservative force acceleration coupled with the test mass can be processed by eliminating the linear trend.

[0133] In an embodiment of the present application, a processing module 73 is configured to obtain operating parameters of a Kalman filter and determine a Kalman filter update equation, where the operating parameters include state variables, an initial state estimate, and a covariance matrix; preprocess angular velocity and angular acceleration to obtain processed angular velocity and angular acceleration; initialize the state variables and the covariance matrix of the Kalman filter, and use the initialized state variables and a system model to perform prediction to obtain a prediction result; compare the preprocessed angular velocity and angular acceleration with the prediction result to obtain a comparison result, and calculate a Kalman gain using the comparison result; calculate updated values of the state variables and updated values of the covariance matrix using the Kalman gain and the update equation; determine a predicted centroid offset based on the updated values of the state variables and the updated values of the covariance matrix.

[0134] In an embodiment of the present application, a calibration module 74 is configured to obtain the acceleration actually output by an inertial sensor currently; perform a detrending process on the acceleration to obtain processed acceleration; obtain the linear acceleration caused by the predicted centroid offset; determine the difference between the processed acceleration and the linear acceleration, and determine the actual value of the centroid offset according to the difference; determine a calibration result of the centroid offset between the centroid of the inertial sensor and the center of gravity of the spacecraft according to the actual value of the centroid offset.

[0135] In an embodiment of the present application, the device further includes: an evaluation module, configured to collect acceleration data output by the inertial sensor, and analyze the acceleration data to obtain a noise analysis result; determine an acceleration noise term coupled with the centroid offset according to the calibration result of the centroid offset and the noise analysis result; eliminate or reduce the acceleration noise term in the acceleration data to obtain processed acceleration data, and evaluate the acceleration noise level corresponding to the processed acceleration data; if the acceleration noise level meets a preset condition, use the processed acceleration data as an output.

[0136] Please refer to Figure 8 , Figure 8 which is a schematic structural diagram of an electronic device provided by an alternative embodiment of the present invention, as Figure 8As shown, the electronic device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including a high-speed interface and a low-speed interface. Each component communicates with each other using different buses and can be installed on a common main board or installed in other ways as needed. The processor can process instructions executed within the electronic device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some alternative embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories. Similarly, multiple electronic devices can be connected, and each device provides some necessary operations (for example, as a server array, a set of blade servers, or a multi-processor system). Figure 8 In this case, a processor 10 is taken as an example.

[0137] The processor 10 can be a central processing unit, a network processor, or a combination thereof. Among them, the processor 10 can further include a hardware chip. The above hardware chip can be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The above programmable logic device can be a complex programmable logic device, a field programmable gate array, a generic array logic, or any combination thereof.

[0138] Among them, the memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiments.

[0139] The memory 20 can include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the electronic device presented by a kind of small program landing page, etc. In addition, the memory 20 can include a high-speed random access memory and can also include a non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some alternative embodiments, the memory 20 can optionally include a memory remotely set relative to the processor 10, and these remote memories can be connected to the electronic device through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0140] The memory 20 can include a volatile memory, such as a random access memory; the memory can also include a non-volatile memory, such as a flash memory, a hard disk, or a solid-state drive; the memory 20 can also include a combination of the above types of memories.

[0141] The electronic device further includes a communication interface 30 for the electronic device to communicate with other devices or communication networks.

[0142] Embodiments of the present invention also provide a computer-readable storage medium. The method according to the embodiments of the present invention can be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented as computer code that is originally stored in a remote storage medium or a non-transitory machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored as such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code, and when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the method shown in the above embodiments is implemented.

[0143] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. An on-orbit calibration method for inertial sensor center of mass offset, characterized in that: The inertial sensor is arranged on the spacecraft, and the method comprises: angular velocity and angular acceleration of the spacecraft after the maneuver by the inertial sensor; constructing a metrological observation model using the angular velocity of the spacecraft and the angular acceleration; The measurement observation model is processed by a pre-constructed Kalman filter to obtain an estimated center of mass offset; Obtaining a calibration result of a center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft based on the estimated center of mass offset and the acceleration calculated by the inertial sensor output; The method of processing the metrology observation model by using a pre-built Kalman filter to obtain an estimated centroid shift includes: Acquire the working parameters of the Kalman filter, and determine the Kalman filter update equation, wherein the working parameters include state variables, initial state estimates and covariance matrices; preprocess the angular velocity and the angular acceleration to obtain processed angular velocity and angular acceleration; initialize the state variables and covariance matrix of the Kalman filter, and use the initialized state variables and the system model to predict and obtain prediction results; compare the preprocessed angular velocity and angular acceleration with the prediction results to obtain comparison results, and use the comparison results to calculate the Kalman gain; use the Kalman gain and the update equation to calculate the updated value of the state variable and the updated value of the covariance matrix; determine the estimated center of mass offset based on the updated value of the state variable and the updated value of the covariance matrix; wherein, update the error covariance matrix: ； The method of obtaining a calibration result of the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft based on the acceleration calculation outputted by the estimated center of mass offset and the inertial sensor includes: obtaining the acceleration currently actually outputted by the inertial sensor; performing delinearization trend processing on the acceleration to obtain the processed acceleration; obtaining the linear acceleration caused by the estimated center of mass offset; determining the difference between the processed acceleration and the linear acceleration, and determining the actual value of the center of mass offset according to the difference; and determining the calibration result of the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft according to the actual value of the center of mass offset.

2. The method according to claim 1, characterized in that The angular velocity and angular acceleration measured by the inertial sensor after the spacecraft maneuvers include: Detecting an attitude signal of test quality generated by an inertial sensor, wherein the attitude signal is generated by the inertial sensor after the spacecraft maneuvers; The attitude signal is analyzed to obtain the angular velocity and angular acceleration of the spacecraft.

3. The method according to claim 1, characterized in that The measurement observation model is as follows: in, , The linear term of acceleration as a non-conservative force coupled with the test mass can be treated by eliminating the linear trend.

4. The method according to claim 1, characterized in that: The formula of the Kalman filter is as follows: is the state transfer matrix in the prediction process, is the gain of input U, W is the estimated process noise, and V is the measurement noise, where the measured value Y, the estimated , the observation matrix H is: 。 5. The method according to claim 1, characterized in that The method further comprises: Collecting acceleration data output by the inertial sensor, and analyzing the acceleration data to obtain a noise analysis result; Determining an acceleration noise term coupled with the mass center offset according to the calibration result of the mass center offset and the noise analysis result; Eliminating or reducing acceleration noise items in the acceleration data to obtain processed acceleration data, and evaluating the acceleration noise level corresponding to the processed acceleration data; If the acceleration noise level meets the preset condition, the processed acceleration data is used as output.

6. An on-orbit calibration device for inertial sensor mass center offset, characterized in that: The device comprises: An acquisition module, used for obtaining the angular velocity and angular acceleration of the spacecraft after the maneuver occurs through the inertial sensor; A construction module, used to construct a metrology observation model using the angular velocity of the spacecraft and the angular acceleration; A processing module, used for processing the metrology observation model through a pre-built Kalman filter to obtain an estimated centroid offset; A calibration module, configured to obtain a calibration result of a mass center offset between the mass center of the inertial sensor and the center of gravity of the spacecraft based on the estimated mass center offset and the acceleration calculation output by the inertial sensor; The processing module is specifically used to obtain the working parameters of the Kalman filter and determine the Kalman filter update equation, wherein the working parameters include state variables, initial state estimates and covariance matrices; preprocess the angular velocity and the angular acceleration to obtain processed angular velocity and angular acceleration; initialize the state variables and covariance matrix of the Kalman filter, and use the initialized state variables and the system model to predict and obtain prediction results; compare the preprocessed angular velocity and angular acceleration with the prediction results to obtain comparison results, and use the comparison results to calculate the Kalman gain; use the Kalman gain and the update equation to calculate the updated value of the state variable and the updated value of the covariance matrix; determine the estimated center of mass offset based on the updated value of the state variable and the updated value of the covariance matrix, and update the error covariance matrix: ； The calibration module is specifically used to obtain the acceleration currently actually output by the inertial sensor; perform delinearization trend processing on the acceleration to obtain the processed acceleration; obtain the linear acceleration caused by the estimated center of mass offset; determine the difference between the processed acceleration and the linear acceleration, and determine the actual value of the center of mass offset according to the difference; determine the calibration result of the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft according to the actual value of the center of mass offset.

7. An electronic device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 5 by executing the computer instructions.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 5.

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