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Ballistic Fitting Impact Point Prediction Based on Improved Crayfish Optimization Algorithm
- 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