Experimental research on the muzzle response characteristics of small unmanned ground vehicles with small arms

Ding, Yugang; Zhou, Kesong; He, Li; Yang, Haomin

doi:10.1177/09544062211057045

Cited by 3 publications

(2 citation statements)

References 21 publications

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“…The R 2 score was used as the evaluation citation of the model of bullet prediction for impact points, as shown in equation (2). The R 2 score of the bullet landing prediction model is shown in Table 1, and the R 2 values of the numerical predictions of the horizontal and vertical offsets of the bullet landing are both greater than 0.9, which showed that the model of bullet prediction for impact points is accurate for the prediction for impact points.…”

Section: Fig4 Network Structure Diagram Of Prediction For Impact Pointsmentioning

confidence: 99%

“…Small-caliber unmanned intelligent weapons (SCUIW) are autonomous fire strike systems that combine traditional weapons, optoelectronic sights, and servo control modules [1][2][3]. Firing accuracy is the most important performance index of small-caliber unmanned intelligent weapons, and the main influence factors are hit probability estimation accuracy, image servo tracking accuracy, and firing timing [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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Precise Firing Methods for Small-caliber Unmanned Intelligent Firearms Based on BP Neural Network and Model Predictive Control

Gao,

Wang

2024

Preprint

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The firing accuracy of small-caliber unmanned intelligent weapons has an important impact on killing effectiveness. In order to improve the firing accuracy of small-caliber unmanned intelligent weapons against moving humanoid targets, hit probability estimation and image servo control are investigated in this paper. Firstly, a method to predict the impact points based on supervised learning is proposed. An corrected ballistic trajectory model is applied to generate training samples, and the mapping relationship that expresses the state of the impact points is formed. Then, a bullet dispersion acquisition experiment is carried out, and a model of bullet dispersion based on a two-dimensional Gaussian distribution is established by analyzing the distribution characteristics of the impact points. Meanwhile, the estimation method of hit probability applied to image detection is formed. In addition, an image servo control method based on model predictive control and human key point detection is proposed, which effectively improves the tracking accuracy of moving humanoid targets. Finally, numerical simulation and firing experiment validation are carried out, and the results show that the precision firing method of small-caliber unmanned intelligent weapons proposed in this paper can effectively improve the firing accuracy of small-caliber unmanned intelligent weapons.

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Section: Fig4 Network Structure Diagram Of Prediction For Impact Pointsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Precise Firing Methods for Small-caliber Unmanned Intelligent Firearms Based on BP Neural Network and Model Predictive Control

Gao,

Wang

2024

Preprint

View full text Add to dashboard Cite

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Dynamic Simulation and Experiment of Marching Small Unmanned Ground Vehicles with Small Arms

Ding

Zhou

et al. 2022

Arab J Sci Eng

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High-speed rotating mechanism based on multi-sensor data fusion end face displacement determination method

Li,

Liang,

Zhang

et al. 2024

AIP Advances

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As a type of transmission actuator commonly used in mechanical structures, high-speed rotary mechanisms are widely used in the machinery, energy, civil engineering, and military industries. The main working part of the mechanism is the end face, and the vibration characteristics of the end face directly affect the accuracy and completeness of the whole mechanism. In terms of performance, the end face vibration characteristics reflect the degree of change in the machine’s end face displacement. The traditional end face displacement test method uses a single contact sensor for measurement, but the degree of error in the system is large. It is also difficult to adapt this method to the current high-precision working conditions under the requirements for accurate vibration prediction and control technology. Therefore, this work proposes a test method based on multi-sensor acquisition and data fusion, using different sensors to form a sensor test network. It seeks to address the limitations of the conventional test method that relies on a single-frequency domain, using high-frequency domain impact signals, medium-frequency domain vibration signals, and low-frequency domain rotational speed signals for multi-sensor data fusion to achieve a complete high-speed rotating mechanism with a particular focus on full-area coverage. In order to better obtain the test data, the sensor layout network is optimized through the optimization design method, and the optimal sensor installation scheme is proposed. Finally, the data fusion algorithm and sensor layout scheme are experimentally verified with a typical high-speed rotating mechanism.

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Experimental research on the muzzle response characteristics of small unmanned ground vehicles with small arms

Cited by 3 publications

References 21 publications

Precise Firing Methods for Small-caliber Unmanned Intelligent Firearms Based on BP Neural Network and Model Predictive Control

Precise Firing Methods for Small-caliber Unmanned Intelligent Firearms Based on BP Neural Network and Model Predictive Control

Dynamic Simulation and Experiment of Marching Small Unmanned Ground Vehicles with Small Arms

High-speed rotating mechanism based on multi-sensor data fusion end face displacement determination method

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