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Ballistic Fitting Impact Point Prediction Based on Improved Crayfish Optimization Algorithm

Authors :
Baolu Yang
Liangming Wang
Jian Fu
Source :
Aerospace, Vol 11, Iss 11, p 908 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

To solve the problem of difficulty in predicting the impact point clearly and promptly during projectile flight, this paper proposes an improved ballistic-impact-point prediction method. A certain type of high-spinning tailed projectile is taken as the research object for online real-time landing point prediction research. This study comprehensively utilizes the real-time radar measurement data and the geomagnetic data measured by the bomb-carried geomagnetic sensor. It applies the four-degree-of-freedom ballistic model to predict the landing point. First, the roll angular velocity is calculated based on the geomagnetic data, after which the radar real-time measurement data are segmentally fitted using the improved crayfish algorithm. Then, the fitted parameters are substituted into the four-degree-of-freedom ballistic model. Finally, the C-K method is used to identify the aerodynamic parameters, and the identified aerodynamic parameters are used for fallout prediction. The simulation results show a small deviation between the predicted and actual impact points using the improved ballistic-impact-point prediction method.

Details

Language :
English
ISSN :
22264310
Volume :
11
Issue :
11
Database :
Directory of Open Access Journals
Journal :
Aerospace
Publication Type :
Academic Journal
Accession number :
edsdoj.89174abfeb1d48b99a689befae31711a
Document Type :
article
Full Text :
https://doi.org/10.3390/aerospace11110908