CN-119642663-B - Guided projectile model/inertial autonomous navigation method and system

CN119642663BCN 119642663 BCN119642663 BCN 119642663BCN-119642663-B

Abstract

The invention provides a guided projectile model/inertial autonomous navigation method and system, which are suitable for autonomous navigation positioning of the whole guided projectile process, wherein the framework mainly comprises two parts, namely a filtering model construction part and a filtering method design part, a system state equation is constructed according to a ballistic dynamics model, and a measurement equation is constructed by taking the output angular rate of a gyroscope and the output specific force of an accelerometer as observables based on the parameter coupling relation between an inertial device and the ballistic model; based on the filter innovation information and the historical data, the innovation UKF based on data driving is designed, the measurement variance matrix can be adjusted in real time, the fusion precision of the model/inertial parameters is improved, and the autonomous navigation of the high-precision guided projectile is realized. The method is suitable for guidance shell navigation under a high dynamic environment.

Inventors

WANG JINWEN
YANG LI
CHEN SIYUAN
HUANG QILONG
HE LIU

Assignees

南京理工大学

Dates

Publication Date: 20260512
Application Date: 20241016

Claims (5)

1. A guided projectile model/inertial autonomous navigation method, comprising: Step 1, constructing a system state equation according to a six-degree-of-freedom rigid body ballistic model of a guided projectile; Step 2, analyzing the coupling relation between the trajectory data and the measurement information of the inertial device based on a system state equation, and constructing a system measurement equation; Step 3, constructing a guided projectile model/inertial autonomous navigation filtering model according to a system state equation and a system measurement equation; step 4, designing a data-driven innovation UKF based on the filter innovation information and the historical data, and estimating a built guided projectile model/inertial autonomous navigation filtering model to realize autonomous navigation of the guided projectile; The six-degree-of-freedom rigid body ballistic model of the guided projectile in the step 1 is as follows: In the formula, Respectively representing the mass center speed, the speed high-low angle, the speed direction angle, the triaxial angular speed rotating around the mass center, the bullet axis high-low angle, the bullet axis azimuth angle, the bullet rolling angle and the bullet mass center triaxial position; the three-axis component of the external moment in the spring axis coordinate system is expressed, Representing the triaxial components of the external force in the ballistic coordinate system, Respectively representing the mass, polar moment of inertia and equatorial moment of inertia of the projectile; The system state equation is: In the formula, ; Step 2, constructing a system measurement equation by taking the output angular rate of the gyroscope and the output specific force of the accelerometer as observables; The gyroscope output angular rate is: In the formula, A nonlinear equation representing ballistic data versus gyroscope output angular rate, Represents the i-th element in X, Outputting an angular rate for the gyroscope; the accelerometer output specific force is as follows: In the formula, A nonlinear equation representing ballistic data versus accelerometer output force, Is the acceleration of the three axes, For the east, north and heaven speeds, For local gravitational acceleration, state matrix ; The system measurement equation is: Wherein, the Outputting an angular rate for the gyroscope; The specific force is output for the accelerometer and, A nonlinear equation representing ballistic data versus gyroscope output angular rate, Represents the i-th element in X, A nonlinear equation representing ballistic data versus accelerometer output specific force; the step 4 specifically includes: First initialize state estimation Sum-of-state error covariance matrix Calculating sigma points through UT conversion; The 4RK method is adopted to update the system state and state error covariance matrix in time, and UT conversion is carried out again to generate a new sigma point set; based on the guided projectile model/inertial autonomous navigation filtering model, measuring and updating are carried out, and information is calculated; according to the information, evaluating the deviation between the system measurement prediction and the information measurement, and determining the deviation degree; Based on the deviation degree, calculating the mean value of the angular rate and the specific force deviation degree, and designing a self-adaptive measurement mean square error matrix based on data driving; calculating Kalman gain matrix and updating system state and covariance to realize autonomous navigation of guided projectile The innovation is as follows: In the formula, Angular velocity and specific force information output by the inertial device at the moment k, 。
2. The guided projectile model/inertial autonomous navigation method of claim 1, wherein the system state and state error covariance matrix is updated in time using a 4RK method: In the formula, As a system variance matrix, variables The weight coefficients are calculated as follows: in the coefficients The value range is , Is a coefficient.
3. A guided projectile model/inertial autonomous navigation method according to claim 1, wherein the degree of deviation is: In the formula, Indicating the degree of deviation of the measured angular rate of the measuring gyroscope, Indicating the degree of deviation of the measured specific force of the accelerometer, The first 3 elements representing the innovation, Representing the last 3 elements of the innovation.
4. The guided projectile model/inertial autonomous navigation method of claim 1, wherein the adaptive measurement mean square error matrix is: In the formula, Representing the elements on the diagonal of the measurement mean square error matrix, Indicating the degree of deviation coefficient of intensity.
5. A guided projectile model/inertial autonomous navigation system implementing the method of any of claims 1-4, comprising: the system state equation construction unit is used for constructing a system state equation according to the six-degree-of-freedom rigid body ballistic model of the guided projectile; the system measurement equation construction unit is used for analyzing the coupling relation between the trajectory data and the measurement information of the inertial device based on the system state equation to construct a system measurement equation; The filtering model construction unit is used for constructing a guided shell model/inertial autonomous navigation filtering model according to a system state equation and a system measurement equation; And the navigation control unit is used for designing the innovation UKF based on data driving based on the filter innovation information and the historical data, estimating the built guided projectile model/inertial autonomous navigation filtering model and realizing autonomous navigation of the guided projectile.

Description

Guided projectile model/inertial autonomous navigation method and system Technical Field The invention belongs to the field of guided projectile navigation in a high dynamic environment, and relates to a guided projectile model/inertial autonomous navigation method and system. Background Guided projectiles are increasingly important in national security and in the development of weaponry. How to obtain the navigation information with high precision is a key technology for realizing accurate target hitting of guided shells, and the navigation precision directly influences the precision of the target hitting of the guided shells. Because GNSS belongs to weak signals of wireless communication, satellite signals are easily interfered by complex environments such as clouds, lightning, solar storms and the like in natural environments, satellite constellation safety is threatened by anti-defensive missiles, laser weapons, electromagnetic impact and the like in actual battlefield environments, and satellite receivers are easily interfered or deceived by electrons and cannot be positioned accurately. Therefore, aiming at the urgent need of developing and developing a new-era battlefield environment by taking inertial guidance as a core under the satellite rejection condition, the research of the inertial autonomous navigation method of the guided projectile under the high dynamic environment is of great significance. The method aims at the research of the navigation method of the information fusion of various multisource sensors in the whole process of autonomous navigation of guided projectiles under the satellite rejection condition. The national army research laboratory proposes to use a multisource fusion scheme of accelerometer, gyroscope and magnetometer combination to realize the calculation of the projectile attitude and the motion navigation. An advanced inertial microsensor was developed to provide stable navigational performance under extreme conditions, starting an accurate robust inertial guided munition project in the country of 2015. The Alicia Roux et al, style.Louis, france, effectively estimates projectile trajectories using EKF and incomplete right-invariant EKF, which focuses on the study of filter estimation algorithms with little analysis of projectile itself and its environmental characteristics. Recently, alicia Roux et al have proposed a depth Kalman filtering method, which estimates the projectile trajectory of a satellite under a rejection environment by using only a reference magnetic field and an inertial measurement unit consisting of an accelerometer, a gyroscope and a magnetometer, and achieves a good effect, and which focuses on the application of depth learning in the Kalman filtering field, lacks the association with the motion characteristics and environmental characteristics of an actual projectile, and does not satisfy the problem of inertial navigation accuracy under a complex disturbance environment. Disclosure of Invention Aiming at the problem of insufficient inertial navigation precision in a complex disturbance environment, the invention provides a guided projectile model/inertial autonomous navigation method and system, which improve navigation autonomy. The technical solution for realizing the purpose of the invention is as follows: a guided projectile model/inertial autonomous navigation method comprising: Step 1, constructing a system state equation according to a six-degree-of-freedom rigid body ballistic model of a guided projectile; Step 2, analyzing the coupling relation between the trajectory data and the measurement information of the inertial device based on a system state equation, and constructing a system measurement equation; Step 3, constructing a guided projectile model/inertial autonomous navigation filtering model according to a system state equation and a system measurement equation; and 4, designing a data-driven innovation UKF based on the filter innovation information and the historical data, and estimating a built guided projectile model/inertial autonomous navigation filtering model to realize autonomous navigation of the guided projectile. Further, the six-degree-of-freedom rigid body ballistic model of the guided projectile in the step 1 is as follows: In the formula, Respectively representing the mass center speed, the speed high-low angle, the speed direction angle, the triaxial angular speed rotating around the mass center, the bullet axis high-low angle, the bullet axis azimuth angle, the bullet rolling angle and the bullet mass center triaxial position; the three-axis component of the external moment in the spring axis coordinate system is expressed, Representing the triaxial components of the external force in the ballistic coordinate system,Respectively representing the mass, polar moment of inertia and equatorial moment of inertia of the projectile; The system state equation is: In the formula, 。 Further, the step 2 is to construct a sys