Adaptive optimization of ballistic dispersion for maneuvering target interception

Mei, Wei; Zheng, Changyan; Liu, Heng

doi:10.1109/chicc.2015.7259651

Cited by 2 publications

(3 citation statements)

References 3 publications

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Section: Introductionmentioning

confidence: 99%

“…With the development of missile technology, threats to ground and maritime equipment continue to increase [1], and air defense missiles play an important role in protecting the equipment [2]. The interception probability of air defense missiles affects the selection of combat plans, the calculation of weapon combat effectiveness, and the design of weapons [1,3,4]. The interception probability of a single missile is the basis for calculating the interception probability of multiple missiles [5], also a key performance indicator to measure air defense missile weapon systems [6].…”

Section: Introductionmentioning

confidence: 99%

“…The performance evaluation method uses advanced evaluation algorithms to evaluate the interception probability under different performance parameters based on expert experience or existing indicators. In [1], the analytic hierarchy process was used to establish the kill probability model. By this method, the killing probability of air defense missiles can be evaluated on the basis of a small amount of range data.…”

Section: Introductionmentioning

confidence: 99%

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Influencing Factor Analysis of Interception Probability and Classification-Regression Neural Network Based Estimation

Nan,

Yi,

et al. 2023

J. of Syst. Eng. Electron.

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The interception probability of a single missile is the basis for combat plan design and weapon performance evaluation, while its influencing factors are complex and mutually coupled. Existing calculation methods have very limited analysis of the influence mechanism of influencing factors, and none of them has analyzed the influence of the guidance law. This paper considers the influencing factors of both the interceptor and the target more comprehensively. Interceptor parameters include speed, guidance law, guidance error, fuze error, and fragment killing ability, while target performance includes speed, maneuverability, and vulnerability. In this paper, an interception model is established, Monte Carlo simulation is carried out, and the influence mechanism of each factor is analyzed based on the model and simulation results. Finally, this paper proposes a classification-regression neural network to quickly estimate the interception probability based on the value of influencing factors. The proposed method reduces the interference of invalid interception data to valid data, so its prediction accuracy is significantly better than that of pure regression neural networks.

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