Multi-domain evaluation method for RF stealth performance based on IFA-TOPSIS with hesitant fuzzy sets

Chengxiu Yang; Qianzhe Wang; Weidong Peng; Shaoting Pei

doi:10.1117/12.2540058

18 December 2019 Multi-domain evaluation method for RF stealth performance based on IFA-TOPSIS with hesitant fuzzy sets

Chengxiu Yang, Qianzhe Wang, Weidong Peng, Shaoting Pei

Proceedings Volume 11334, AOPC 2019: Optoelectronic Devices and Integration; and Terahertz Technology and Applications; 1133409 (2019) https://doi.org/10.1117/12.2540058
Event: Applied Optics and Photonics China (AOPC2019), 2019, Beijing, China

Abstract

With the development of airborne passive detection equipment, radio frequency (RF) stealth performance evaluation becomes more and more important. This is a comprehensive and complex problem. Firstly, RF stealth performance evaluation is not the optimization of a few indices but a comprehensive evaluation model. Secondly, it is a combination of technology and military tactics, which also needs to be integrated with practical application. In views of this problem, this paper proposes an evaluation method for RF stealth performance based on improved firefly algorithm (IFA) and technique for order preference by similarity to ideal solution (TOPSIS) with hesitant fuzzy sets. From the perspective of the radar radiating, a multi-domain evaluation system is established, which divided into four sub-indicators. Then the optimal attribute weights are obtained based on analyzing attributes and solutions. According to the closeness between different solutions and ideal solutions, the radar RF stealth performance ranking is obtained. Finally, numerical simulations demonstrate the effectiveness of the proposed new approach.

Citation Download Citation

Chengxiu Yang, Qianzhe Wang, Weidong Peng, and Shaoting Pei "Multi-domain evaluation method for RF stealth performance based on IFA-TOPSIS with hesitant fuzzy sets", Proc. SPIE 11334, AOPC 2019: Optoelectronic Devices and Integration; and Terahertz Technology and Applications, 1133409 (18 December 2019); https://doi.org/10.1117/12.2540058

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