Combat effectiveness evaluation of air-crystal C4ISR early warning detection system based on improved ADC

Xiaolin Wang; Jihui Xu; Yujin Chen

doi:10.1117/12.2517696

12 March 2019 Combat effectiveness evaluation of air-crystal C⁴ISR early warning detection system based on improved ADC

Xiaolin Wang, Jihui Xu, Yujin Chen

Proceedings Volume 11023, Fifth Symposium on Novel Optoelectronic Detection Technology and Application; 110234T (2019) https://doi.org/10.1117/12.2517696
Event: Fifth Symposium on Novel Optoelectronic Detection Technology and Application, 2018, Xi'an, China

Abstract

With the reform of the new military revolution, the pace of war is accelerating, the operational environment is increasingly complex, and weapons and equipment are constantly being upgraded. How to scientifically and effectively evaluate the effectiveness of weapon systems is particularly important. In this paper, the aerospace C⁴ISR early warning detection system is taken as the research object, and the improved ADC method is used to evaluate its operational effectiveness. Firstly, the structure, mission requirements and functional requirements of the C⁴ISR early warning detection system are analyzed, and the operational effectiveness evaluation index system of the early warning detection system is constructed. Secondly, the traditional ADC model is improved by using information entropy and grey relational clustering method. The operational effectiveness of the C⁴ISR early warning detection system was evaluated. Finally, combined with an air defense brigade, the example application analysis and model validity verification were carried out, and relevant countermeasures and suggestions were provided for its system construction optimization based on the evaluation results.

Citation Download Citation

Xiaolin Wang, Jihui Xu, and Yujin Chen "Combat effectiveness evaluation of air-crystal C⁴ISR early warning detection system based on improved ADC", Proc. SPIE 11023, Fifth Symposium on Novel Optoelectronic Detection Technology and Application, 110234T (12 March 2019); https://doi.org/10.1117/12.2517696

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KEYWORDS

Intelligence systems

Reconnaissance systems

Data processing

Reconnaissance

Aerospace engineering

Reliability

Systems modeling

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