Research On Multi-Source Data Fusion And Dynamic Calibration Technology For Exterior Ballistic Test

In recent years,with the development of weapon systems,the demand for long-range ballistic testing at the range has been increasing.At the same time,the needs of national defense modernization construction also require the range to handle more data work on missile systems.Among them,ballistic estimation accuracy is the core of external ballistic estimation,while high precision ballistic parameters are the basis of external ballistic estimation.High-precision ballistic parameters are obtained through measurement equipment.However,the measurement data can have certain errors due to the relevant environment and the equipment itself,which can lead to the subsequent inability to continue the data fusion process.Therefore,calibration of equipment accuracy and data fusion processing are important aspects to improve ballistic estimation accuracy.This paper is based on the project "Photoelectric latitude and longitude instrument postmortem data comprehensive processing software",for the external ballistic post-mortem data processing ballistic accuracy problems to carry out research.Firstly,the calibration of the equipment is completed by combining the systematic error analysis of the photoelectric meridian with the error model and using the dynamic calibration method.Secondly,by combining the ballistic data with the target motion model,an empirical mode decomposition(EMD)algorithm is employed to accurately select the ballistic feature points,and a fitting algorithm is then applied to acquire the full ballistic trajectory.Finally,the data fusion method is used to obtain highprecision ballistic parameters,so as to obtain high-precision ballistic trajectories.The main contributions of the paper are as follows.(1)To address the issue of error correction in the ballistic optical measurement system,a dynamic calibration method for an unmanned aerial vehicle(UAV)platform was designed.Firstly,the sources of error in the measurement data produced by the electro-optical theodolite were analyzed.Secondly,an error model for the system error of the electro-optical theodolite was established,and the UAV-mounted Global Navigation Satellite System(GNSS)was used to obtain an approximate true value of the trajectory,with the data obtained by the measurement equipment serving as the measurement value.By employing the least squares technique,the model coefficients were estimated and solved,thus rectifying the measurement data.Simulation experiments demonstrate that this approach can accurately calibrate the equipment’s system error.(2)To address the problem of selecting and identifying ballistic characteristic points during the remote ballistic main/passive phase and maneuvering phase,the empirical mode decomposition algorithm was used for feature point extraction,which achieved good results.Firstly,based on the flight characteristics of the missile in different phases,the flight was segmented,and a motion model was established for each segment.Secondly,the Kalman filter algorithm was used to solve the missile trajectory to obtain the missile’s velocity and acceleration during flight.The points of acceleration change were identified as feature points.The empirical mode decomposition algorithm was used to extract ballistic characteristic points to determine segmentation across the entire trajectory.Finally,the least squares method was used to obtain the complete trajectory of the missile.Simulation experiments demonstrated that this method can effectively extract ballistic characteristic points,improve trajectory accuracy,and achieve trajectory fitting.(3)In order to address the stability issue of the model in post-flight data fusion processing for ballistic trajectories,a spline-constrained optimal estimation algorithm based on multiple electro-optical theodolites is employed.Firstly,measurement data is acquired using multiple electro-optical theodolites,and the target coordinates are solved by combining them with the measurement data using an equipment error model.Secondly,EMD is employed to extract spline nodes in order to approximate the trajectory,and nonlinear least squares is utilized to calculate the ballistic parameters.Finally,the accuracy of ballistic trajectory can be effectively enhanced by obtaining the system error parameters of the equipment,as demonstrated by simulation experiments.Finally,this method is used to enhance the accuracy of ballistic estimation.This paper’s findings have been implemented in practical engineering projects and have yielded satisfactory outcomes.