@inproceedings{e01436484b38422aa1bc4a48293797a1,
title = "Adjoint-Based RCS Surface Sensitivity Calculation and Aero/RCS Optimization",
abstract = "Adjoint-based RCS gradient computation approach is introduced, and an adjoint-based RCS surface sensitivity analysis method is proposed. Existing adjoint approaches, the needs to fill impedance matrix repeatedly during gradient calculation lead to low efficiency when the number of design variables and incident angles are large. This paper proposes an approach to calculate radar cross section surface sensitivity based on adjoint and automatic differentiation method. And a sparse matrix storage method considering the characters of RWG basis function is adopted to reduce the memory requirements of impedance matrix differentiation. The proposed method can obtain the surface sensitivity of all surface nodes with one matrix differentiation calculation. For different incident angle, the calculation of design variable gradients of any number will not exceed 16 matrix-vector products. The proposed surface sensitivity calculation approach can effectively improve the efficiency of gradient calculation and provide intuitive guidance for optimal design.",
keywords = "automatic differentiation, electromagnetic adjoint equation, radar cross section, surface sensitivity",
author = "Lin Zhou and Xian Chen and Jiangtao Huang and Jun Deng and Zhenghong Gao",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; Asia-Pacific International Symposium on Aerospace Technology, APISAT 2023 ; Conference date: 16-10-2023 Through 18-10-2023",
year = "2024",
doi = "10.1007/978-981-97-4010-9_133",
language = "英语",
isbn = "9789819740093",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "1715--1730",
editor = "Song Fu",
booktitle = "2023 Asia-Pacific International Symposium on Aerospace Technology, APISAT 2023, Proceedings - Volume II",
}