RCS Special Analysis Method for Non-Cooperative Aircraft Based on Inverse Reconfiguration Coupled with Aerodynamic Optimization

To address the challenge of evaluating a radar cross-section (RCS) for a non-cooperative aircraft with limited aerodynamic shape information, this paper presents a multi-source, data-driven inverse reconstruction method. This approach integrates data fusion techniques to facilitate an initial shape reconstruction, followed by an iterative optimization process that utilizes computational fluid dynamics (CFD) to enhance the shape, accounting for the aerodynamic performance. Additionally, an inverse deduction analysis is effectively employed to ascertain the characteristics of the power system, leading to the design of a double S-curved tail nozzle layout with stealth capabilities. An aerodynamic analysis demonstrates that at Mach 0.6, the lift-to-drag ratio peaks at 27.3 for the attack angle of 4°, after which it declines as the angle increases. At higher angles of attack, complex flow separation occurs and expands with the increasing angle. The electromagnetic simulation results indicate that under vertical polarization, the omnidirectional RCS reaches its peak as the incident angle is deflected downward by 10° and reduces with the growth of the angle, demonstrating angular robustness. Conversely, under horizontal polarization, the RCS is more sensitive to edge-induced rounding. The findings illustrate that this methodology enables accurate shape modeling for non-cooperative targets, thereby providing a fairly solid basis for stealth performance evaluation and the assessment of surprise effectiveness.

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Publication Details

Journal
Aerospace
Published
2025-06-24
DOI
https://doi.org/10.3390/aerospace12070573
Primary Topic
Advanced Aircraft Design and Technologies
Type
article
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article

RCS Special Analysis Method for Non-Cooperative Aircraft Based on Inverse Reconfiguration Coupled with Aerodynamic Optimization

G. Feng, Huang Jie, Yang Bai, Chuan Wei et al.
Aerospace
Advanced Aircraft Design and Technologies
article

RCS Special Analysis Method for Non-Cooperative Aircraft Based on Inverse Reconfiguration Coupled with Aerodynamic Optimization

G. Feng, Huang Jie, Yang Bai, Chuan Wei, Junyu Long
article en

Abstract

To address the challenge of evaluating a radar cross-section (RCS) for a non-cooperative aircraft with limited aerodynamic shape information, this paper presents a multi-source, data-driven inverse reconstruction method. This approach integrates data fusion techniques to facilitate an initial shape reconstruction, followed by an iterative optimization process that utilizes computational fluid dynamics (CFD) to enhance the shape, accounting for the aerodynamic performance. Additionally, an inverse deduction analysis is effectively employed to ascertain the characteristics of the power system, leading to the design of a double S-curved tail nozzle layout with stealth capabilities. An aerodynamic analysis demonstrates that at Mach 0.6, the lift-to-drag ratio peaks at 27.3 for the attack angle of 4°, after which it declines as the angle increases. At higher angles of attack, complex flow separation occurs and expands with the increasing angle. The electromagnetic simulation results indicate that under vertical polarization, the omnidirectional RCS reaches its peak as the incident angle is deflected downward by 10° and reduces with the growth of the angle, demonstrating angular robustness. Conversely, under horizontal polarization, the RCS is more sensitive to edge-induced rounding. The findings illustrate that this methodology enables accurate shape modeling for non-cooperative targets, thereby providing a fairly solid basis for stealth performance evaluation and the assessment of surprise effectiveness.

AerospaceVol. 12(7)
Nanjing University of Aeronautics and Astronautics (CN)
Openalex Percentile: Top 86%
Advanced Aircraft Design and Technologies
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RCS Special Analysis Method for Non-Cooperative Aircraft Based on Inverse Reconfiguration Coupled with Aerodynamic Optimization — G. Feng, Huang Jie, et al. · Aerospace (2025) | TGRS Research Map | TGRS