A method, system, medium and product for estimating the rolling angle of a rotating guided projectile

Abstract

A method, system, medium and product for estimating the rolling angle of a rotating guided projectile, which relates to the field of projectile guidance and control. By adopting the above technical solutions, first, the guidance and control system collects the rotation speed signal and the speed change signal after the rotating guided projectile exits the muzzle, and then constructs an accurate kinematic equation set. Secondly, after separating the basic rotation speed component and the fluctuating rotation speed component, the guidance and control system combines them to obtain the actual rotation speed value, and obtains the estimated rotation speed value by constructing a state prediction equation, and then obtains the observation error value. Then, the guidance and control system calculates the Mahalanobis distance based on the observation error value, the error covariance matrix and the measurement noise covariance matrix, and determines the weight coefficient to obtain the filtered rotation speed sequence. Finally, the guidance and control system performs numerical integration on the filtered rotation speed sequence in a preset time interval to obtain the final rolling angle estimation value. Thus, the instantaneous rolling angle of the rotating guided projectile during flight can be accurately estimated.

Description

Technical Field

[0001] The present application relates to the field of artillery shell guidance and control, and in particular to a method, system, medium and product for estimating the roll angle of a rotary guided artillery shell. Background Art

[0002] Rotary guided projectiles play an important role in modern battlefields due to their excellent guidance accuracy and powerful penetration capability. During the flight of a rotary guided projectile, the roll angle is an important guidance parameter, and its accurate measurement has a significant impact on the guidance control and strike accuracy of the projectile. How to accurately obtain the roll angle information of a rotary guided projectile during flight has become a key technical problem that needs to be solved in the design of a guidance control system.

[0003] At present, the commonly used method for measuring the roll angle of a rotary guided projectile is to install a gyroscope inside the projectile to collect the projectile's attitude data in real time, and use the Kalman filter algorithm to process the collected data to obtain the projectile's roll angle information.

[0004] This method can meet the basic needs of artillery guidance to a certain extent. However, since the artillery shells will bear huge launch loads during the launch process, the drift error of the gyroscope will accumulate over time under high-speed rotation, resulting in large deviations in the measurement results. Summary of the invention

[0005] The present application provides a method, system, medium and product for estimating the roll angle of a rotary guided projectile, which are used to improve the accuracy of estimating the roll angle of a rotary guided projectile.

[0006] First aspect, the present application provides a method for estimating the rolling angle of a rotary guided projectile, which is applied to a guidance control system. The method includes: collecting the rotational speed signal and the speed change signal after the rotary guided projectile exits the muzzle to determine the angular velocity vector sequence and the acceleration vector sequence. The angular velocity vector sequence is used to represent the time serialization of the rotational speed signal, and the acceleration vector sequence is used to represent the time serialization of the speed change signal; according to the angular velocity vector sequence and the acceleration vector sequence, constructing a kinematic equation set of the rotary guided projectile in a weightless state, and based on the kinematic equation set, using the least squares method to separate the basic rotational speed component and the fluctuating rotational speed component. The basic rotational speed component is used to represent the stable rotational speed of the rotary guided projectile, and the fluctuating rotational speed component is used to represent the instantaneous disturbance of the rotary guided projectile; combining the basic rotational speed component and the fluctuating rotational speed component to obtain the first actual rotational speed value of the rotary guided projectile at the first moment and the second actual rotational speed value of the rotary guided projectile at the second moment; constructing a state prediction equation according to the first actual rotational speed value to obtain the second estimated rotational speed value at the second moment, and based on the second actual rotational speed value and the second estimated rotational speed value, obtaining an observation error value, which is used to represent the difference between the second actual rotational speed value and the second estimated rotational speed value; calculating the Mahalanobis distance based on the observation error value, the error covariance matrix and the measurement noise covariance matrix, and determining the weight coefficient according to the Mahalanobis distance to determine the filtered rotational speed sequence at the second moment; performing numerical integration on the filtered rotational speed sequence in a preset time interval to obtain the final rolling angle estimation value, which is used to represent the instantaneous rolling angle of the rotary guided projectile during flight.

[0007] By adopting the above technical solutions, first, the guidance control system collects the rotational speed signal and the speed change signal after the rotary guided projectile exits the muzzle, which can capture the dynamic changes of the rotary guided projectile, and then construct an accurate kinematic equation set. Secondly, the guidance control system separates the basic rotational speed component and the fluctuating rotational speed component, which can effectively filter out noise, extract the stable rotational speed of the rotary guided projectile, and reduce the influence of instantaneous disturbance. Then, the guidance control system combines the basic rotational speed component and the fluctuating rotational speed component to obtain the actual rotational speed value, and obtains the estimated rotational speed value by constructing a state prediction equation, and then obtains the observation error value, which can more reliably evaluate the accuracy of the rotational speed estimation. Next, the guidance control system calculates the Mahalanobis distance based on the observation error value, the error covariance matrix and the measurement noise covariance matrix, and determines the weight coefficient to obtain the filtered rotational speed sequence, fully considering various error factors, measuring the similarity between the data and the mean value by the Mahalanobis distance, and reasonably allocating the weight, making the filtered rotational speed sequence more accurate and reliable, and effectively reducing the influence of noise and error. Finally, the guidance control system performs numerical integration on the filtered rotational speed sequence in a preset time interval to obtain the final rolling angle estimation value, converting the discrete rotational speed data into continuous angle changes to accurately estimate the instantaneous rolling angle of the rotary guided projectile during flight.

[0008] In some embodiments in combination with some embodiments of the first aspect, kinematic equations of a spinning guided projectile in a weightless state are constructed based on an angular velocity vector sequence and an acceleration vector sequence, specifically including: mapping the angular velocity vector sequence to an Euler angle space to obtain an Euler angular velocity signal sequence; combining the Euler angular velocity signal sequence and the acceleration vector sequence to establish a kinematic state equation based on Euler angles; performing Taylor series expansion on the kinematic state equation and taking the first-order term to obtain a linearized kinematic equation set.

[0009] By adopting the above technical solutions, first, the guidance and control system maps the angular velocity vector sequence to the Euler angle space to obtain an Euler angular velocity signal sequence. The Euler angles can intuitively represent the rotation angles of the spinning guided projectile in different directions, making the subsequent analysis and calculation of the motion state of the spinning guided projectile more convenient. Secondly, the guidance and control system combines the Euler angular velocity signal sequence and the acceleration vector sequence to establish a kinematic state equation based on Euler angles, comprehensively considering the angular velocity information and acceleration information of the spinning guided projectile, so that the motion state of the spinning guided projectile can be described more comprehensively. Because the combination of angular velocity and acceleration can more accurately characterize the motion characteristics of the projectile during flight, it helps to improve the accuracy of roll angle estimation. Finally, the guidance and control system performs Taylor series expansion on the kinematic state equation and takes the first-order term to obtain a linearized kinematic equation set, linearizing the originally complex non-linear equation. The linearized equation set is more convenient in calculation and is conducive to using various numerical calculation methods for solution and analysis. At the same time, under certain conditions, the first-order approximation can greatly reduce the calculation complexity and improve the calculation efficiency without losing too much accuracy, enabling the motion state of the spinning guided projectile to be estimated and predicted quickly in practical applications.

[0010] In some embodiments in combination with some embodiments of the first aspect, a Mahalanobis distance is calculated based on an observation error value, an error covariance matrix, and a measurement noise covariance matrix, specifically including: calculating a comprehensive error matrix based on the error covariance matrix and the measurement noise covariance matrix; calculating the Mahalanobis distance according to the observation error value and the comprehensive error matrix.

[0011] By adopting the above technical solutions, this distance measurement method based on statistical characteristics fully considers the influence of system noise and measurement error, thus providing an objective evaluation criterion. That is, the Mahalanobis distance can be used to more accurately judge the abnormality degree of the measurement value, providing a scientific basis for the determination of subsequent weight coefficients, thereby improving the filtering effect and estimation accuracy.

[0012] In some embodiments in combination with some embodiments of the first aspect, determining the weight coefficient according to the Mahalanobis distance specifically includes: when the Mahalanobis distance is less than or equal to the first threshold, setting the weight coefficient to 1; when the Mahalanobis distance is greater than or equal to the second threshold, setting the weight coefficient to 0; when the Mahalanobis distance is between the first threshold and the second threshold, inputting the Mahalanobis distance, the first threshold, and the second threshold into the weight calculation formula to obtain the weight coefficient; the weight calculation formula is: w(k) = (γ2 - d(k)) / (γ2 - γ1), where w(k) represents the weight coefficient, γ1 represents the first threshold, γ2 represents the second threshold, and d(k) represents the Mahalanobis distance.

[0013] By adopting the above technical solution, the guidance and control system designs a piecewise determination of the weight coefficient based on the Mahalanobis distance, realizing the accurate evaluation and dynamic weighting of the reliability of measurement data, avoiding the measurement mutation caused by the traditional fixed weight method, and thus being able to effectively cope with various complex disturbance situations, improving the filtering effect and the attitude estimation accuracy.

[0014] In some embodiments in combination with some embodiments of the first aspect, based on the kinematic equations, the least squares method is used to separate the basic rotational speed component and the fluctuating rotational speed component, specifically including: based on the kinematic equations, constructing a time-varying weighted least squares objective function; decomposing the rotational speed signal into a linear combination form of the basic rotational speed and the fluctuating rotational speed; solving the optimal parameters of the time-varying weighted least squares objective function to obtain the basic rotational speed component; subtracting the basic rotational speed component from the rotational speed signal to obtain the fluctuating rotational speed component.

[0015] By adopting the above technical solution, the guidance and control system uses the time-varying weighted least squares method to decompose the rotational speed signal to establish an efficient rotational speed component separation method. This method can accurately capture the steady-state rotational speed characteristics of the rotating guided projectile while retaining the transient disturbance information, avoiding the problem of signal distortion in the traditional method. At the same time, the decomposition method based on the physical model improves the accuracy of signal processing, laying a solid foundation for subsequent attitude estimation.

[0016] In some embodiments in combination with some embodiments of the first aspect, combining the basic rotational speed component and the fluctuating rotational speed component to obtain the first actual rotational speed value of the rotating guided projectile at the first moment and the second actual rotational speed value at the second moment, specifically including: performing a linear superposition on the basic rotational speed component and the fluctuating rotational speed component to obtain a sequence of rotational speed values of the rotating guided projectile at continuous time points; based on the sequence of rotational speed values, using the sliding window algorithm to extract the first actual rotational speed value of the rotating guided projectile at the first moment and the second actual rotational speed value at the second moment.

[0017] By adopting the above technical solution, the guidance and control system uses a signal reconstruction method of linear superposition with a sliding window to achieve accurate extraction of the actual rotational speed value. By calculating the first actual rotational speed value of the rotating guided projectile at the first moment and the second actual rotational speed value at the second moment, it provides a data basis for subsequent construction of the state prediction equation and prediction of the second estimated rotational speed value of the rotating guided projectile at the second moment.

[0018] Combined with some embodiments of the first aspect, in some embodiments, numerical integration is performed on the filtered rotational speed sequence within a preset time interval to obtain a final roll angle estimation value, which is used to represent the instantaneous roll angle of the rotating guided projectile during flight. Specifically, it includes: discretizing the filtered rotational speed sequence according to a preset sampling frequency to obtain a discretized filtered rotational speed sequence; performing numerical integration on the discretized filtered rotational speed sequence within the preset time interval to obtain an initial roll angle estimation value; using a high-order polynomial curve fitting method to fit the initial roll angle estimation value to obtain a normalized roll angle estimation value; and performing deviation correction on the normalized roll angle estimation value to obtain the final roll angle estimation value.

[0019] By adopting the above technical solution, the guidance and control system gradually processes and optimizes the filtered rotational speed sequence, from discretization, numerical integration to curve fitting and deviation correction, so as to be able to accurately estimate the final roll angle estimation value of the rotating guided projectile, effectively improving the accuracy and reliability of roll angle estimation.

[0020] In a second aspect, an embodiment of the present application provides a guidance and control system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, and the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the guidance and control system to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product containing instructions, which, when the computer program product runs on the guidance and control system, enables the guidance and control system to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, including instructions, which, when the instructions run on the guidance and control system, enable the guidance and control system to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0023] Understandably, the guidance control system provided in the second aspect above, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiments of the present application. Therefore, the beneficial effects they can achieve can refer to the beneficial effects in the corresponding method, which will not be elaborated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0025] 1. By adopting the above technical solutions, first, the guidance control system collects the rotation speed signal and the speed change signal after the rotation-guided projectile exits the muzzle, which can capture the dynamic changes of the rotation-guided projectile, and then constructs an accurate kinematic equation set. Second, the guidance control system separates the basic rotation speed component and the fluctuating rotation speed component, which can effectively filter out noise and extract the stable rotation speed of the rotation-guided projectile, reducing the influence of instantaneous disturbances. Then, the guidance control system combines the basic rotation speed component and the fluctuating rotation speed component to obtain the actual rotation speed value, and obtains the estimated rotation speed value by constructing a state prediction equation, and then obtains the observation error value, which can more reliably evaluate the accuracy of the rotation speed estimation. Next, the guidance control system calculates the Mahalanobis distance based on the observation error value, the error covariance matrix, and the measurement noise covariance matrix, and determines the weight coefficient to obtain the filtered rotation speed sequence, fully considering various error factors, measuring the similarity between the data and the mean by the Mahalanobis distance, and reasonably allocating the weights, making the filtered rotation speed sequence more accurate and reliable, and effectively reducing the influence of noise and errors. Finally, the guidance control system performs numerical integration on the filtered rotation speed sequence in a preset time interval to obtain the final roll angle estimation value, converting the discrete rotation speed data into continuous angle changes to accurately estimate the instantaneous roll angle of the rotation-guided projectile during flight.

[0026] 2. By adopting the above technical solution, firstly, the guidance and control system maps the angular velocity vector sequence to the Euler angle space to obtain the Euler angular velocity signal sequence. The Euler angles can intuitively represent the rotation angles of the rotating guided projectile in different directions, making the subsequent analysis and calculation of the motion state of the rotating guided projectile more convenient. Secondly, the guidance and control system combines the Euler angular velocity signal sequence with the acceleration vector sequence to establish the motion state equation based on Euler angles, comprehensively considering the angular velocity information and acceleration information of the rotating guided projectile, so that the motion state of the rotating guided projectile can be described more comprehensively. Because the combination of angular velocity and acceleration can more accurately characterize the motion characteristics of the projectile during flight, it helps to improve the accuracy of the roll angle estimation. Finally, the guidance and control system performs Taylor series expansion on the motion state equation and takes the first-order term to obtain the linearized kinematic equations, linearizing the originally complex non-linear equations. The linearized equations are more convenient in calculation and are easy to solve and analyze using various numerical calculation methods. At the same time, under certain conditions, the first-order approximation can greatly reduce the calculation complexity and improve the calculation efficiency without losing too much accuracy, enabling the rapid estimation and prediction of the motion state of the rotating guided projectile in practical applications.

[0027] 3. By adopting the above technical solution, the guidance and control system designs and determines the weight coefficients in segments based on the Mahalanobis distance, realizing the accurate evaluation and dynamic weighting of the reliability of measurement data, avoiding the measurement mutations caused by the traditional fixed weight method, and thus being able to effectively cope with various complex disturbance situations, improving the filtering effect and the attitude estimation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 is a flowchart of a method for estimating the roll angle of a rotating guided projectile in an embodiment of the present application;

[0029] Figure 2 is another flowchart of a method for estimating the roll angle of a rotating guided projectile in an embodiment of the present application;

[0030] Figure 3 is a schematic structural diagram of an entity device of a guidance and control system in an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of the present application, the singular forms "a", "an", "the above", "the", and "this" are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations including one or more of the listed items.

[0032] Hereinafter, the terms "first" and "second" are only used for descriptive purposes and should not be construed as implying or suggesting relative importance or implicitly indicating the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality" is two or more.

[0033] The following describes the process of the method provided in this embodiment. Please refer to Figure 1 , which is a schematic flowchart of a rolling angle estimation method for a spinning guided projectile in an embodiment of the present application.

[0034] S101. Collect the rotational speed signal and the speed change signal after the spinning guided projectile exits the muzzle to determine the angular velocity vector sequence and the acceleration vector sequence. The angular velocity vector sequence is used to represent the time serialization of the rotational speed signal, and the acceleration vector sequence is used to represent the time serialization of the speed change signal.

[0035] Among them, the spinning guided projectile refers to a launcher with spin stabilization ability and guidance function; the rotational speed signal refers to the angular velocity of the spinning guided projectile rotating around its own axis; the speed change signal refers to the rate of change of the velocity vector of the spinning guided projectile over time; the angular velocity vector sequence is used to represent an ordered sequence formed by angular velocity vectors measured at different sampling moments; the acceleration vector sequence is used to represent an ordered sequence formed by acceleration vectors measured at different sampling moments; time serialization refers to the process of arranging discrete measurement signals in a sequence according to the time order.

[0036] Specifically, first, the guidance control system collects the angular velocity data of the spinning guided projectile in real time through a gyroscope sensor installed on the spinning guided projectile, and at the same time collects the acceleration data of the spinning guided projectile in real time through an acceleration sensor. The guidance control system samples these raw data at a fixed sampling period (usually 1 - 10 ms), and performs signal conditioning and digital processing. Then, the guidance control system converts the processed data into angular velocity vectors and acceleration vectors respectively. Then, the guidance control system arranges these vectors in the sampling time order to form an angular velocity vector sequence and an acceleration vector sequence, providing basic data for subsequent attitude estimation.

[0037] Assume a sampling period of 10 ms, and the data of 5 sampling points are collected in a certain launch:

[0038] Angular velocity data (rad / s):

[0039] t = 0 ms: ω1 = [120, 0.5, 0.3] (representing the angular velocity components of the x, y, and z axes respectively);

[0040] t = 10 ms: ω2 = [118, 0.6, 0.4];

[0041] t = 20 ms: ω3 = [115, 0.8, 0.5];

[0042] t = 30 ms: ω4 = [112, 1.0, 0.6];

[0043] t = 40 ms: ω5 = [110, 1.2, 0.7];

[0044] It can be seen from this set of data that the rotational speed of the x-axis (the axial direction of the projectile) gradually decreases from 120 rad / s to 110 rad / s, and the angular velocities in the y-axis and z-axis directions increase slightly, indicating that the projectile has slight nutation.

[0045] Acceleration data (m / s²):

[0046] t = 0 ms: a1 = [850, 0.2, 0.1] (representing the acceleration components of the x, y, and z axes respectively);

[0047] t = 10 ms: a2 = [845, 0.3, 0.2];

[0048] t = 20 ms: a3 = [840, 0.4, 0.3];

[0049] t = 30 ms: a4 = [835, 0.5, 0.4];

[0050] t = 40 ms: a5 = [830, 0.6, 0.5];

[0051] It can be observed from this set of data that the acceleration in the x-axis direction decreases from 850 m / s² to 830 m / s², indicating that the projectile is affected by air resistance, and there are small accelerations in the y-axis and z-axis directions, indicating that the ballistic trajectory has a slight deviation.

[0052] S102. According to the angular velocity vector sequence and the acceleration vector sequence, construct the kinematic equations of the spinning guided projectile in the weightless state, and based on the kinematic equations, use the least squares method to separate the basic rotational speed component and the fluctuating rotational speed component. The basic rotational speed component is used to represent the stable rotational speed of the spinning guided projectile, and the fluctuating rotational speed component is used to represent the instantaneous perturbation of the spinning guided projectile;

[0053] Among them, the weightless state refers to the state in which the rotating guided projectile is under very little gravitational force during flight; the kinematic equation system refers to the mathematical equation system that describes the motion characteristics of the projectile; the least squares method refers to the mathematical method for parameter estimation by minimizing the sum of squared errors; the basic rotational speed component is used to represent the basic rotational speed of the rotating guided projectile during stable flight; the fluctuating rotational speed component is used to represent the instantaneous angular velocity deviation caused by external disturbances; the instantaneous perturbation refers to the influence caused by various short-term external forces acting on the rotating guided projectile.

[0054] Specifically, first, based on the rigid body dynamics principle, the guidance and control system establishes a mathematical model describing the three-dimensional motion of the projectile. This mathematical model takes into account factors such as the moment of inertia and aerodynamic moment of the rotating guided projectile to form a complete kinematic equation system. Then, the guidance and control system uses the time-varying weighted least squares algorithm to decompose the collected angular velocity signal into a steady-state component and a perturbation component. Among them, the steady-state component reflects the nominal rotational speed of the rotating guided projectile, and the perturbation component includes the fluctuations caused by factors such as airflow disturbance and asymmetric mass distribution. This decomposition can more accurately describe the actual motion state of the rotating guided projectile.

[0055] Optionally, generally, according to the angular velocity vector sequence and the acceleration vector sequence, the kinematic equation system of the rotating guided projectile in the weightless state can be constructed in the following way (not limited here): Map the angular velocity vector sequence to the Euler angle space to obtain the Euler angular velocity signal sequence; Combine the Euler angular velocity signal sequence with the acceleration vector sequence to establish the motion state equation based on Euler angles; Perform Taylor series expansion on the motion state equation and take the first-order term to obtain the linearized kinematic equation system.

[0056] Suppose there is a rotating guided projectile with a mass of 20 kg, and the moment of inertia matrix is Ix = 0.08 kg·m² (axial), Iy = 0.85 kg·m² (lateral), Iz = 0.85 kg·m² (lateral);

[0057] (1) Establishment of the kinematic equation system:

[0058] In the weightless state, the angular motion equation of the rotating guided projectile can be simplified as:

[0059] Ix·dωx / dt = Mx (aerodynamic moment);

[0060] Iy·dωy / dt = My (aerodynamic moment);

[0061] Iz·dωz / dt = Mz (aerodynamic moment);

[0062] (2) Example of measured angular velocity data (rad / s) (sampling period 10 ms):

[0063] t = 0 ms: ω = [120.5, 0.8, 0.6];

[0064] t = 10 ms: ω = [119.8, 1.2, 0.9];

[0065] t = 20 ms: ω = [120.2, 0.7, 0.5];

[0066] t = 30 ms: ω = [119.5, 1.1, 0.8];

[0067] t = 40 ms: ω = [120.1, 0.9, 0.7];

[0068] (3)Use the least squares method to separate the base speed and the fluctuation component:

[0069] A. Base speed component (steady state value):

[0070] ωx_base = 120.0 rad / s (axial base speed);

[0071] ωy_base = 0.9 rad / s (lateral base speed);

[0072] ωz_base = 0.7 rad / s (lateral base speed);

[0073] B. Fluctuating speed component (perturbation value):

[0074] t = 0 ms: Δω = [+0.5, -0.1, -0.1];

[0075] t = 10 ms: Δω = [-0.2, +0.3, +0.2];

[0076] t = 20 ms: Δω = [+0.2, -0.2, -0.2];

[0077] t = 30 ms: Δω = [-0.5, +0.2, +0.1];

[0078] t = 40 ms: Δω = [+0.1, +0.0, +0.0];

[0079] (4)Analysis results: The base speed shows that the projectile has a stable axial spin (120 rad / s) and a small steady-state angular velocity in the lateral direction (<1 rad / s), indicating a slightly inclined trajectory; the fluctuation component shows that the axial fluctuation is within the range of ±0.5 rad / s and the lateral fluctuation is within the range of ±0.3 rad / s. The fluctuation amplitude is relatively small compared to the base speed, indicating that the projectile attitude is relatively stable.

[0080] S103. Combine the base rotational speed component and the fluctuating rotational speed component to obtain the first actual rotational speed value of the spinning guided projectile at the first moment and the second actual rotational speed value at the second moment;

[0081] Among them, the base rotational speed component refers to the stable rotational speed component of the spinning guided projectile; the fluctuating rotational speed component refers to the speed fluctuations caused by various disturbances; the first moment represents a certain reference time point; the second moment represents a certain reference time point relative to after the first moment; the first actual rotational speed value is used to represent the actual rotational speed at the first moment; the second actual rotational speed value is used to represent the actual rotational speed at the second moment.

[0082] Specifically, the guidance control system uses the principle of linear superposition to reconstruct the decomposed base rotational speed component and fluctuating rotational speed component on the time axis. First, the control system establishes a sliding time window (typically 50 - 100 ms), and superimposes the base rotational speed and the fluctuating rotational speed at each sampling moment within the sliding time window. In this way, the guidance control system can obtain the actual rotational speed value at any moment. The guidance control system selects two specific moments (usually spaced 10 - 20 ms apart), and extracts the actual rotational speed values at these two specific moments, which are respectively used as the first actual rotational speed value and the second actual rotational speed value, and these values will be used for subsequent state prediction and error estimation.

[0083] Suppose a 50 - ms sliding time window is selected, the sampling period is 10 ms, and observations start at t = 100 ms, and the following data is obtained:

[0084] Base rotational speed component (rad / s):

[0085] ωx_base = 120.0 (axial)

[0086] ωy_base = 0.8 (lateral);

[0087] ωz_base = 0.6 (lateral);

[0088] Fluctuating rotational speed component (rad / s):

[0089] t = 100 ms (window start point): Δω = [+0.5, -0.2, -0.1];

[0090] t = 110 ms: Δω = [+0.3, -0.1, -0.2];

[0091] t = 120 ms: Δω = [-0.2, +0.1, +0.1];

[0092] t = 130 ms: Δω = [-0.4, +0.2, +0.0];

[0093] t = 140 ms: Δω = [-0.1, +0.1, -0.1];

[0094] Combined calculation of the actual rotational speed:

[0095] Select two specific moments:

[0096] The first moment: t1 = 100 ms;

[0097] The second moment: t2 = 120 ms (interval of 20 ms);

[0098] The actual value of the first rotational speed (t = 100 ms):

[0099] ωx_actual1 = 120.0 + 0.5 = 120.5 rad / s;

[0100] ωy_actual1 = 0.8 - 0.2 = 0.6 rad / s;

[0101] ωz_actual1 = 0.6 - 0.1 = 0.5 rad / s;

[0102] The actual value of the second rotational speed (t = 120 ms):

[0103] ωx_actual2 = 120.0 - 0.2 = 119.8 rad / s;

[0104] ωy_actual2 = 0.8 + 0.1 = 0.9 rad / s;

[0105] ωz_actual2 = 0.6 + 0.1 = 0.7 rad / s;

[0106] Analyzing the data at these two moments reveals that:

[0107] Axial rotational speed:

[0108] At t1, it is higher than the base rotational speed (+0.5 rad / s);

[0109] At t2, it is lower than the base rotational speed (-0.2 rad / s);

[0110] This indicates a deceleration trend within 20 ms;

[0111] Lateral rotational speed:

[0112] In the y-axis direction, it increases from 0.6 rad / s to 0.9 rad / s;

[0113] In the z-axis direction, it increases from 0.5 rad / s to 0.7 rad / s;

[0114] This indicates that the projectile may have been subjected to lateral disturbances.

[0115] S104. Construct a state prediction equation based on the actual first rotational speed value to obtain the estimated second rotational speed value at the second moment. Based on the actual second rotational speed value and the estimated second rotational speed value, obtain an observation error value, which is used to represent the difference between the actual second rotational speed value and the estimated second rotational speed value.

[0116] Among them, the state prediction equation refers to a mathematical equation used to predict the future state of a spinning guided projectile; the estimated second rotational speed value refers to the expected rotational speed value at the second moment calculated through the state prediction equation; the observation error value is used to represent the deviation between the predicted value and the actual value; the actual first rotational speed value refers to the actual rotational speed measured at the first moment; the actual second rotational speed value refers to the actual rotational speed measured at the second moment; the difference refers to the quantitative difference between the two values of the actual second rotational speed value and the estimated second rotational speed value.

[0117] Specifically, first, the guidance control system establishes a state prediction equation based on the dynamic characteristics of the spinning guided projectile. This state prediction equation includes parameters such as the moment of inertia and damping coefficient. The guidance control system substitutes the actual first rotational speed value at the first moment into the state prediction equation and obtains the expected rotational speed value at the second moment, that is, the estimated second rotational speed value, through numerical calculation. Then, the guidance control system compares the actual second rotational speed value and the estimated second rotational speed value, calculates the difference between them, and obtains the observation error. This observation error reflects the accuracy of the state prediction equation and the degree of influence of external disturbances, providing an important basis for subsequent filtering processing.

[0118] Optionally, generally, combining the basic rotational speed component and the fluctuating rotational speed component, the actual first rotational speed value of the spinning guided projectile at the first moment and the actual second rotational speed value at the second moment can be obtained in the following way (not limited here): linearly superimpose the basic rotational speed component and the fluctuating rotational speed component to obtain a sequence of rotational speed values of the spinning guided projectile at consecutive time points; based on the sequence of rotational speed values, use a sliding window algorithm to extract the actual first rotational speed value of the spinning guided projectile at the first moment and the actual second rotational speed value at the second moment.

[0119] Assume that the actual first rotational speed value (t = 100 ms) is known, ω1_actual = [120.5, 0.6, 0.5] rad / s ([x-axis, y-axis, z-axis]).

[0120] State prediction equation (simplified model considering air resistance):

[0121] ω2_prediction = ω1 + (M / I - k·ω1)·Δt;

[0122] Where:

[0123] -M: Aerodynamic moment [0.2, 0.1, 0.1] N·m;

[0124] -I: Moment of inertia [0.08, 0.85, 0.85] kg·m²;

[0125] -k: Damping coefficient [0.001, 0.002, 0.002] 1 / s;

[0126] -Δt: Time interval 0.02 s (20 ms).

[0127] Calculate the second rotational speed estimated value (t = 120 ms):

[0128] X-axis: ω2x_estimated = 120.5 + (0.2 / 0.08 - 0.001 × 120.5) × 0.02 = 120.55 rad / s;

[0129] Y-axis: ω2y_estimated = 0.6 + (0.1 / 0.85 - 0.002 × 0.6) × 0.02 = 0.602 rad / s;

[0130] Z-axis: ω2z_estimated = 0.5 + (0.1 / 0.85 - 0.002 × 0.5) × 0.02 = 0.502 rad / s;

[0131] Actual value of the second rotational speed (t = 120 ms): ω2_actual = [119.8, 0.9, 0.7] rad / s;

[0132] Calculate the observation error value: Observation error = ω2_actual - ω2_estimated = [119.8 - 120.55, 0.9 - 0.602, 0.7 - 0.502] = [-0.75, +0.298, +0.198] rad / s;

[0133] Analysis result: Error of the X-axis (axial direction): The predicted value is 0.75 rad / s higher than the actual value, indicating that the actual resistance may be greater than the model prediction. Errors of the Y-axis and Z-axis (lateral directions): The actual values are 0.298 and 0.198 rad / s greater than the predicted values respectively, indicating that there may be unmodeled lateral disturbances.

[0134] S105. Based on the observation error value, error covariance matrix, and measurement noise covariance matrix, calculate the Mahalanobis distance, and determine the weight coefficient according to the Mahalanobis distance to determine the filtered rotational speed sequence at the second moment;

[0135] Among them, the error covariance matrix refers to the matrix that describes the statistical characteristics of the shell state estimation error; the measurement noise covariance matrix refers to the statistical characteristics of the noise in the measurement process; the Mahalanobis distance is used to represent the standardized distance metric considering the error distribution; the weight coefficient is the factor used to adjust the filtering intensity; the filtered rotational speed sequence refers to the rotational speed data sequence after filtering processing.

[0136] Specifically, first, the guidance and control system estimates the error covariance matrix based on historical data and obtains the measurement noise covariance matrix through sensor calibration. The guidance and control system combines these matrices with the observation error to calculate the Mahalanobis distance. Then, the guidance and control maps the Mahalanobis distance to a weight coefficient between 0 and 1 according to preset thresholds (usually γ1 = 2.5, γ2 = 4). A smaller Mahalanobis distance corresponds to a larger weight coefficient, indicating that the measurement value is more reliable; a larger Mahalanobis distance corresponds to a smaller weight coefficient, indicating that the measurement value may be significantly disturbed. The guidance and control system uses this weight coefficient to perform weighted averaging on the original data to obtain a more accurate filtered rotational speed sequence.

[0137] Optionally, generally, based on the observation error value, the error covariance matrix, and the measurement noise covariance matrix, the calculation of the Mahalanobis distance can be achieved in the following manner, which is not limited herein: based on the error covariance matrix and the measurement noise covariance matrix, calculate the comprehensive error matrix; according to the observation error value and the comprehensive error matrix, calculate the Mahalanobis distance.

[0138] Optionally, generally, the determination of the weight coefficient according to the Mahalanobis distance can be achieved in the following manner, which is not limited herein: when the Mahalanobis distance is less than or equal to the first threshold, let the weight coefficient be 1; when the Mahalanobis distance is greater than or equal to the second threshold, let the weight coefficient be 0; when the Mahalanobis distance is between the first threshold and the second threshold, input the Mahalanobis distance, the first threshold, and the second threshold into the weight calculation formula to obtain the weight coefficient; the weight calculation formula is: w(k) = (γ2 - d(k)) / (γ2 - γ1), where w(k) represents the weight coefficient, γ1 represents the first threshold, γ2 represents the second threshold, and d(k) represents the Mahalanobis distance.

[0139] The known observation error e = [-0.75, +0.298, +0.198] rad / s.

[0140] Error covariance matrix P (3×3 symmetric matrix):

[0141] P = [0.25 0.02 0.01] [0.02 0.16 0.03] [0.01 0.03 0.16]

[0144] Measurement noise covariance matrix R (3×3 symmetric matrix):

[0145] R = [0.36 0.01 0.01] [0.01 0.25 0.02] [0.01 0.02 0.25]

[0148] Calculate the Mahalanobis distance d² = e'(P + R)⁻¹e

[0149] Specific calculation:

[0150] S = P + R = [0.61 0.03 0.02] [0.03 0.41 0.05] [0.02 0.05 0.41]

[0153] d² = [-0.75 0.298 0.198] × [1.67 -0.11 -0.07] × [-0.75]

[0154] [-0.11 2.49 -0.30] × [0.298]

[0155] [-0.07 -0.30 2.48] × [0.198]

[0156] = 1.86

[0157] Determine the weight coefficient according to the Mahalanobis distance:

[0158] If d² ≤ γ1² (2.5² = 6.25): β = 1;

[0159] If γ1² < d² ≤ γ2² (4² = 16): β = (γ2² - d²) / (γ2² - γ1²);

[0160] If d² > γ2²: β = 0;

[0161] Here d² = 1.86 < γ1², so β = 1;

[0162] Calculate the filtered rotational speed:

[0163] The estimated value of the second rotational speed at the second moment: ω2_estimated = [120.55, 0.602, 0.502] rad / s;

[0164] The actual value of the second rotational speed at the second moment: ω2_actual = [119.8, 0.9, 0.7] rad / s;

[0165] Calculation of the filtered rotational speed: ω2_filtered = β · ω2_actual + (1 - β) · ω2_estimated;

[0166] Since β = 1, ω2_filtered = 1 × [119.8, 0.9, 0.7] + 0 × [120.55, 0.602, 0.502] = [119.8, 0.9, 0.7] rad / s.

[0167] S106. Numerically integrate the filtered rotational speed sequence over a preset time interval to obtain the final roll angle estimate, which is used to represent the instantaneous roll angle of the spinning guided projectile during flight.

[0168] Among them, the preset time interval refers to the time range for integral calculation; numerical integration refers to the numerical method for calculating definite integrals through discrete data points; the roll angle estimate is used to represent the angle by which the spinning guided projectile rotates around its own axis; the instantaneous roll angle refers to the angle of rotation of the projectile relative to its initial position at a certain moment.

[0169] Specifically, first, the guidance control system discretizes the filtered rotational speed sequence at a fixed sampling frequency (usually 100 - 200 Hz). Then, the guidance control system selects a suitable numerical integration method (such as the trapezoidal method or the Runge - Kutta method) to perform integral operations on the discretized data within the preset time interval (usually 0.5 - 1 s). To improve accuracy, the guidance control system uses a high - order polynomial (usually 5 - 7 orders) to perform curve fitting on the integration result and corrects the error according to the physical characteristics of the spinning guided projectile. The obtained final roll angle estimate will be used for the attitude control and trajectory correction of the projectile.

[0170] Optionally, generally, numerically integrating the filtered rotational speed sequence over a preset time interval to obtain the final roll angle estimate, which is used to represent the instantaneous roll angle of the spinning guided projectile during flight can be achieved in the following way (not limited here): Discretize the filtered rotational speed sequence at a preset sampling frequency to obtain a discretized filtered rotational speed sequence; Numerically integrate the discretized filtered rotational speed sequence over the preset time interval to obtain an initial roll angle estimate; Use a high - order polynomial curve fitting method to fit the initial roll angle estimate to obtain a normalized roll angle estimate; Perform deviation correction on the normalized roll angle estimate to obtain the final roll angle estimate.

[0171] Suppose within a preset time interval of 0.5 s, the sampling frequency is 100 Hz (sampling period 10 ms), and the following filtered rotational speed sequence (rad / s) is obtained:

[0172] t = 0 ms: ω = 119.8;

[0173] t = 10 ms: ω = 119.6;

[0174] t = 20 ms: ω = 119.5;

[0175] t = 30 ms: ω = 119.3;

[0176] t = 40 ms: ω = 119.2;

[0177] t = 50 ms: ω = 119.0;

[0178] …… (intermediate data omitted)

[0179] t = 480 ms: ω = 118.2;

[0180] t = 490 ms: ω = 118.1;

[0181] t = 500 ms: ω = 118.0;

[0182] Using the trapezoidal method for numerical integration: θ = ∫ω(t)dt ≈ Δt / 2 × [ω(0) + 2ω(1) + 2ω(2) + …… + 2ω(n - 1) + ω(n)];

[0183] Where:

[0184] Δt = 0.01 s (10 ms);

[0185] n = 50 (number of sampling points);

[0186] Calculating in segments (showing the calculation process for the first 0.05 s): θ1 = 0.01 / 2 × [119.8 + 2(119.6 + 119.5 + 119.3 + 119.2 + 119.0)] = 6.565 rad;

[0187] Integral result for the complete 0.5 s: θtotal = 59.48 rad ≈ 3409.6 degrees;

[0188] Using a 7th - order polynomial fitting and correction: The correction coefficient k considering air resistance and nutation effects is 0.985;

[0189] θcorrected = θtotal × k = 59.48 × 0.985 = 58.59 rad ≈ 3358.5 degrees;

[0190] Analysis of the final estimated roll angle: Approximately 9.33 rotations were completed within 0.5 s, the average angular velocity was about 119.0 rad / s, and the angular velocity showed a slow downward trend: starting at 119.8 rad / s, ending at 118.0 rad / s, and the rate of decrease was about - 3.6 rad / s².

[0191] By adopting the above technical solution, first, the guidance and control system collects the rotation speed signal and the speed change signal after the rotary guided projectile exits the muzzle, which can capture the dynamic changes of the rotary guided projectile, and then constructs an accurate kinematic equation set. Second, the guidance and control system separates the basic rotation speed component and the fluctuating rotation speed component, which can effectively filter out noise, extract the stable rotation speed of the rotary guided projectile, and reduce the influence of instantaneous disturbances. Then, the guidance and control system combines the basic rotation speed component and the fluctuating rotation speed component to obtain the actual rotation speed value, and obtains the estimated rotation speed value by constructing a state prediction equation, and then obtains the observation error value, which can more reliably evaluate the accuracy of the rotation speed estimation. Next, the guidance and control system calculates the Mahalanobis distance based on the observation error value, the error covariance matrix, and the measurement noise covariance matrix, and determines the weight coefficient to obtain the filtered rotation speed sequence, fully considering various error factors, measuring the similarity between the data and the mean by the Mahalanobis distance, and reasonably allocating the weight, so that the filtered rotation speed sequence is more accurate and reliable, and effectively reduces the influence of noise and errors. Finally, the guidance and control system performs numerical integration on the filtered rotation speed sequence in a preset time interval to obtain the final roll angle estimation value, converting the discrete rotation speed data into continuous angular changes to accurately estimate the instantaneous roll angle of the rotary guided projectile during flight.

[0192] The following further describes the more specific process of the method provided in this embodiment. Please refer to Figure 2 , which is another process schematic diagram of the roll angle estimation method for the rotary guided projectile in the embodiment of the present application.

[0193] Step S102 can also be implemented in the following manner, which is not limited herein:

[0194] S201. Based on the kinematic equation set, construct a time-varying weighted least squares objective function;

[0195] Among them, the kinematic equation set refers to a mathematical equation system that describes the motion state of the rotary guided projectile in three-dimensional space; time-varying weighting refers to a weighting method in which the weight coefficient changes with time; the least squares objective function refers to a mathematical function used to minimize the sum of the squares of the errors between the predicted value and the actual value; the objective function refers to a mathematical expression used for optimization and solution; the weight coefficient is used to represent the importance of data at different times; the sum of the squares of the errors refers to the accumulation of the squares of the differences between the predicted value and the actual value.

[0196] Specifically, first, based on the established kinematic equations, the guidance and control system constructs an objective function that reflects the deviation between the predicted value and the actual value. This objective function uses time-varying weight coefficients to assign different importance to data at different times. Newer data has a larger weight, and older data has a smaller weight, which can better reflect the dynamic characteristics of the spinning guided projectile. The specific form of the objective function is the weighted sum of squared errors with a time decay factor. By minimizing this objective function, the optimal state estimation result of the spinning guided projectile can be obtained.

[0197] Assume that at a certain moment \(t_0 = 100\mathrm{ms}\), the angular velocity data of the first 5 sampling points (sampling period \(10\mathrm{ms}\)) are collected:

[0198] Measured value \(\omega_{\text{measured}}\) (rad / s):

[0199] \(t = 60\mathrm{ms}\): 121.5;

[0200] \(t = 70\mathrm{ms}\): 121.2;

[0201] \(t = 80\mathrm{ms}\): 120.8;

[0202] \(t = 90\mathrm{ms}\): 120.5;

[0203] \(t = 100\mathrm{ms}\): 120.2;

[0204] Predicted value \(\omega_{\text{predicted}}\) (rad / s) based on the kinematic equations:

[0205] \(t = 60\mathrm{ms}\): 121.8;

[0206] \(t = 70\mathrm{ms}\): 121.4;

[0207] \(t = 80\mathrm{ms}\): 121.0;

[0208] \(t = 90\mathrm{ms}\): 120.6;

[0209] \(t = 100\mathrm{ms}\): 120.3;

[0210] Calculation of time-varying weight coefficients:

[0211] Adopt the form of exponential decay: \(w(t)=\exp(-\lambda(t_0 - t))\);

[0212] where \(\lambda = 0.01\) is the decay coefficient and \(t_0 = 100\mathrm{ms}\) is the current moment, and the weights at each moment are obtained:

[0213] \(t = 60\mathrm{ms}\): \(w_1=\exp(-0.01\times40)=0.670\);

[0214] \(t = 70\mathrm{ms}\): \(w_2=\exp(-0.01\times30)=0.741\);

[0215] At t = 80 ms: w3 = exp(-0.01×20) = 0.819;

[0216] At t = 90 ms: w4 = exp(-0.01×10) = 0.905;

[0217] At t = 100 ms: w5 = exp(-0.01×0) = 1.000;

[0218] Construct the objective function J: J = Σwᵢ(ω_measuredᵢ - ω_predictedᵢ)²;

[0219] Calculate the squared error terms at each moment:

[0220] At t = 60 ms: (121.5 - 121.8)²×0.670 = 0.060;

[0221] At t = 70 ms: (121.2 - 121.4)²×0.741 = 0.030;

[0222] At t = 80 ms: (120.8 - 121.0)²×0.819 = 0.033;

[0223] At t = 90 ms: (120.5 - 120.6)²×0.905 = 0.009;

[0224] At t = 100 ms: (120.2 - 120.3)²×1.000 = 0.010;

[0225] The final value of the objective function: J = 0.060 + 0.030 + 0.033 + 0.009 + 0.010 = 0.142.

[0226] S202. Decompose the rotational speed signal into a linear combination form of the basic rotational speed and the fluctuating rotational speed;

[0227] Among them, the linear combination refers to the form of adding two or more components in a certain proportion; decomposition refers to the process of splitting a complex signal into simple components.

[0228] Specifically, after obtaining the rotational speed signal, the guidance and control system represents it as a linear superposition form of the basic rotational speed and the fluctuating rotational speed. The basic rotational speed reflects the angular velocity characteristics of the rotating guided projectile in a stable flight state, while the fluctuating rotational speed contains the speed disturbances caused by factors such as air resistance and asymmetric mass distribution. This decomposition can help the guidance and control system process the steady-state motion and transient disturbances separately, thereby improving the accuracy of state estimation. The guidance and control system uses mathematical modeling methods to establish the expression of signal decomposition and determines the coefficients of each component through parameter identification.

[0229] S203. Solve the optimal parameters for the time-varying weighted least squares objective function to obtain the basic rotational speed component;

[0230] Among them, the time-varying weighted least squares objective function refers to the sum of squared error function containing time-varying weights; the optimal parameters refer to the parameter values corresponding to the minimum value of the objective function; solving refers to the process of obtaining the solution of the equation through mathematical methods; the basic rotational speed component is used to represent the steady-state angular velocity of the spinning guided projectile.

[0231] Specifically, after establishing the time-varying weighted least squares objective function, the guidance and control system uses the gradient descent method to optimize and solve the objective function. The guidance and control system first sets the initial parameter values, then calculates the partial derivatives of the objective function with respect to each parameter, and gradually adjusts the parameter values based on the direction of the partial derivatives. In each iteration, the guidance and control system calculates the value of the objective function under the new parameter values. When the change in the objective function values between two adjacent iterations is less than the preset threshold, it is considered that the optimal solution has been reached. The optimal parameters obtained in this way are the basic rotational speed component, which reflects the steady-state rotation characteristics of the spinning guided projectile. To improve the solution efficiency, the guidance and control system also uses the conjugate gradient method to accelerate the convergence process.

[0232] S204. Subtract the basic rotational speed component from the rotational speed signal to obtain the fluctuating rotational speed component.

[0233] Specifically, after obtaining the basic rotational speed component, the guidance and control system separates the fluctuating rotational speed component through signal subtraction operations. The guidance and control system first aligns the rotational speed signal and the basic rotational speed component to the same time point, and then performs point-by-point subtraction operations. To ensure the operation accuracy, the guidance and control system uses high-precision numerical calculation methods and rounds the intermediate results. The obtained fluctuating rotational speed component contains the speed perturbation information caused by factors such as air resistance and asymmetric mass distribution. The guidance and control system also performs statistical analysis on the fluctuating rotational speed component and calculates its characteristic quantities such as the mean and variance to evaluate the intensity and characteristics of the perturbation.

[0234] The following describes the guidance and control system in the embodiments of the present invention application from the perspective of hardware processing. Please refer to Figure 3 , which is a schematic structural diagram of an entity device of the guidance and control system in the embodiments of the present application.

[0235] It should be noted that Figure 3 The structure of the guidance and control system shown is only an example and should not bring any limitations to the functions and application ranges of the embodiments of the present invention.

[0236] Such as Figure 3As shown, the guidance and control system includes a CPU 301 which can perform various appropriate actions and processes according to a program stored in a read-only memory ROM 302 or a program loaded into a random access memory RAM 303 from a storage section 308, such as executing the method described in the above embodiments. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other via a bus 304. An I / O interface 305 is also connected to the bus 304.

[0237] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD), an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as required. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as required so that a computer program read from it can be installed into the storage section 308 as required.

[0238] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product which includes a computer program carried on a computer-readable medium, and the computer program contains a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 309, and / or installed from the removable medium 311. When the computer program is executed by the CPU 301, various functions defined in the present invention are executed.

[0239] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fibers, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In the present invention, a computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0240] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. Among them, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the above module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings.

[0241] Specifically, the guidance control system of this embodiment includes a processor and a memory. A computer program is stored on the memory. When the computer program is executed by the processor, the rolling angle estimation method for the rotating guided projectile provided in the above embodiment is implemented.

[0242] On the other hand, the present invention also provides a computer-readable storage medium. This storage medium can be included in the guidance control system described in the above embodiment; or it can exist separately and not be assembled into the guidance control system. The above storage medium carries one or more computer programs. When the one or more computer programs are executed by a processor of the guidance control system, the guidance control system implements the rolling angle estimation method for the rotating guided projectile provided in the above embodiment.

[0243] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the various embodiments of the present application.

[0244] As used in the foregoing embodiments, depending on the context, the term "when" may be interpreted to mean "if", "after", "in response to determining", or "in response to detecting". Similarly, depending on the context, the phrase "upon determining" or "if (the stated condition or event) is detected" may be interpreted to mean "if determined", "in response to determining", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0245] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the foregoing embodiments can be implemented by a computer program instructing relevant hardware. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the foregoing method embodiments. The foregoing storage medium includes various media that can store program codes, such as ROM, random access memory (RAM), magnetic disks, or optical discs.

Claims

1. A method for estimating the rolling angle of a rotating guided projectile, characterized in that Applied to a guidance and control system, the method includes: Collecting the rotational speed signal and the speed change signal after the rotary guided projectile exits the muzzle to determine the angular velocity vector sequence and the acceleration vector sequence, where the angular velocity vector sequence is used to represent the time serialization of the rotational speed signal, and the acceleration vector sequence is used to represent the time serialization of the speed change signal; According to the angular velocity vector sequence and the acceleration vector sequence, constructing the kinematic equations of the rotary guided projectile in a weightless state, and based on the kinematic equations, using the least squares method to separate the basic rotational speed component and the fluctuating rotational speed component, where the basic rotational speed component is used to represent the stable rotational speed of the rotary guided projectile, and the fluctuating rotational speed component is used to represent the instantaneous perturbation of the rotary guided projectile; Combining the basic rotational speed component and the fluctuating rotational speed component to obtain the first actual rotational speed value of the rotary guided projectile at the first moment and the second actual rotational speed value at the second moment; Constructing a state prediction equation according to the first actual rotational speed value to obtain the second estimated rotational speed value at the second moment, and based on the second actual rotational speed value and the second estimated rotational speed value, obtaining an observation error value, where the observation error value is used to represent the difference between the second actual rotational speed value and the second estimated rotational speed value; Calculating the Mahalanobis distance based on the observation error value, the error covariance matrix, and the measurement noise covariance matrix, and determining a weight coefficient according to the Mahalanobis distance to determine the filtered rotational speed sequence at the second moment; Performing numerical integration on the filtered rotational speed sequence in a preset time interval to obtain a final roll angle estimate value, where the final roll angle estimate value is used to represent the instantaneous roll angle of the rotary guided projectile during flight.

2. The method according to claim 1, wherein The constructing the kinematic equations of the rotary guided projectile in a weightless state according to the angular velocity vector sequence and the acceleration vector sequence specifically includes: Mapping the angular velocity vector sequence to the Euler angle space to obtain an Euler angular velocity signal sequence; Combining the Euler angular velocity signal sequence and the acceleration vector sequence to establish a motion state equation based on Euler angles; Performing Taylor series expansion on the motion state equation and taking the first-order term to obtain a linearized kinematic equation set.

3. The method according to claim 1, wherein The calculating the Mahalanobis distance based on the observation error value, the error covariance matrix, and the measurement noise covariance matrix specifically includes: Calculating a comprehensive error matrix based on the error covariance matrix and the measurement noise covariance matrix; Calculating the Mahalanobis distance according to the observation error value and the comprehensive error matrix.

4. The method according to claim 3, characterized in that The determining the weight coefficient according to the Mahalanobis distance specifically includes: When the Mahalanobis distance is less than or equal to the first threshold, setting the weight coefficient to 1; When the Mahalanobis distance is greater than or equal to the second threshold, setting the weight coefficient to 0; When the Mahalanobis distance is between the first threshold and the second threshold, inputting the Mahalanobis distance, the first threshold, and the second threshold into a weight calculation formula to obtain the weight coefficient; The weight calculation formula is: w(k) = (γ2 - d(k)) / (γ2 - γ1), where w(k) represents the weight coefficient, γ1 represents the first threshold, γ2 represents the second threshold, and d(k) represents the Mahalanobis distance.

5. The method according to claim 1, wherein Based on the kinematic equations, the least squares method is used to separate the basic rotational speed component and the fluctuating rotational speed component, which specifically includes: Based on the kinematic equations, a time-varying weighted least squares objective function is constructed; The rotational speed signal is decomposed into a linear combination form of the basic rotational speed and the fluctuating rotational speed; The optimal parameters of the time-varying weighted least squares objective function are solved to obtain the basic rotational speed component; The rotational speed signal is subtracted from the basic rotational speed component to obtain the fluctuating rotational speed component.

6. The method according to claim 1, wherein The combination of the basic rotational speed component and the fluctuating rotational speed component to obtain the first actual rotational speed value of the spinning guided projectile at the first moment and the second actual rotational speed value at the second moment specifically includes: Performing a linear superposition on the basic rotational speed component and the fluctuating rotational speed component to obtain a sequence of rotational speed values of the spinning guided projectile at consecutive time points; Based on the sequence of rotational speed values, a sliding window algorithm is used to extract the first actual rotational speed value of the spinning guided projectile at the first moment and the second actual rotational speed value at the second moment.

7. The method according to claim 1, characterized in that The numerical integration of the filtered rotational speed sequence in a preset time interval to obtain the final roll angle estimate value, which is used to represent the instantaneous roll angle of the spinning guided projectile during flight, specifically includes: The filtered rotational speed sequence is discretized according to a preset sampling frequency to obtain a discretized filtered rotational speed sequence; Performing numerical integration on the discretized filtered rotational speed sequence within the preset time interval to obtain an initial roll angle estimate value; Using a high-order polynomial curve fitting method to fit the initial roll angle estimate value to obtain a normalized roll angle estimate value; Performing a deviation correction on the normalized roll angle estimate value to obtain the final roll angle estimate value.

8. A guidance control system, characterized in that, The guidance control system includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, and the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the guidance control system to execute the method according to any one of claims 1-7.

9. A computer-readable storage medium, comprising instructions, characterized in that, When the instruction runs on the guidance control system, it enables the guidance control system to execute the method according to any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product runs on the guidance control system, it enables the guidance control system to execute the method according to any one of claims 1-7.

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