Recognition method for the flight parameters of multiple projectiles with light-screen array sensor

In the dispersion measurements of multi-barrel rapid-firing guns (MBRFGs), the conventional measurement methods fail because multiple projectiles pass through the same detection plane. In this article, a method for measuring the flight parameters of multiple projectiles and recognizing their trajectory lines using a seven-light-screen array sensor (seven-LSAS) is proposed. The proposed seven-LSAS integrates two three-light-screen modules and one non-orthogonal single-light-screen to enhance multi-projectile detection capability. Based on ballistic principles, a mathematical model for the flight parameters (such as impact coordinate, flying velocity, azimuth and pitch angle) of multiple projectiles is established. The trajectory lines are calculated by the moment data of the projectile passing through the seven-LSAS. A full-moment vector space is constructed to calculate the potential trajectory lines corresponding to each moment vector. Using the spatial collinearity constraint inherent to trajectory lines of the same projectile, an association recognition algorithm for the trajectory line based on the collinearity judgment is proposed to achieve accurate recognition of the trajectory lines of multiple projectiles. The experimental results demonstrate that compared to traditional testing methods, the proposed recognition method can accurately recognize and calculate the flight parameters of multiple projectiles. Furthermore, the measurement error of the impact coordinates for recognized projectiles does not exceed 5 mm, with 50% improvement over existing recognition methods, validating the feasibility and effectiveness of the proposed recognition method.

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Publication Details

Journal
Scientific Reports
Published
2025-12-27
DOI
https://doi.org/10.1038/s41598-025-33196-z
Primary Topic
Advanced Measurement and Detection Methods
Type
article
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article

Recognition method for the flight parameters of multiple projectiles with light-screen array sensor

J. P. Li, Hui Tian, Hai Li, Jinping Ni et al.
Scientific Reports
Advanced Measurement and Detection Methods
article

Recognition method for the flight parameters of multiple projectiles with light-screen array sensor

J. P. Li, Hui Tian, Hai Li, Jinping Ni, Chenxi Duan
article en

Abstract

In the dispersion measurements of multi-barrel rapid-firing guns (MBRFGs), the conventional measurement methods fail because multiple projectiles pass through the same detection plane. In this article, a method for measuring the flight parameters of multiple projectiles and recognizing their trajectory lines using a seven-light-screen array sensor (seven-LSAS) is proposed. The proposed seven-LSAS integrates two three-light-screen modules and one non-orthogonal single-light-screen to enhance multi-projectile detection capability. Based on ballistic principles, a mathematical model for the flight parameters (such as impact coordinate, flying velocity, azimuth and pitch angle) of multiple projectiles is established. The trajectory lines are calculated by the moment data of the projectile passing through the seven-LSAS. A full-moment vector space is constructed to calculate the potential trajectory lines corresponding to each moment vector. Using the spatial collinearity constraint inherent to trajectory lines of the same projectile, an association recognition algorithm for the trajectory line based on the collinearity judgment is proposed to achieve accurate recognition of the trajectory lines of multiple projectiles. The experimental results demonstrate that compared to traditional testing methods, the proposed recognition method can accurately recognize and calculate the flight parameters of multiple projectiles. Furthermore, the measurement error of the impact coordinates for recognized projectiles does not exceed 5 mm, with 50% improvement over existing recognition methods, validating the feasibility and effectiveness of the proposed recognition method.

Scientific ReportsVol. 16(1)
Xi'an Technological University (CN)
Openalex Percentile: Top 42%
Advanced Measurement and Detection Methods
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