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Uncertainty characterization of small-angle azimuthal RCS for stealth-aircraft detectability assessment
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DOI：10.1016/j.dt.2026.07.024.png)
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Abstract
En 中文
Radar cross section (RCS) is a key metric for characterizing the electromagnetic scattering behavior and radar detectability of stealth aircraft. For platforms with established RCS databases, trajectory-based detectability analysis commonly maps angular-domain RCS data into time-domain sequences according to the relative aircraft–radar geometry. However, stealth aircraft can exhibit order-of-magnitude RCS variations within narrow azimuthal-angle intervals, such that minor attitude perturbations may induce pronounced fluctuations in radar-observed RCS. To characterize this local uncertainty and support uncertainty-aware radar threat assessment, this paper develops a data-supported statistical description of small-angle azimuthal RCS fluctuations. High-resolution X-band RCS datasets are first generated for three representative stealth-aircraft configurations using electromagnetic simulation. A three-stage data-driven screening framework is then employed to identify an appropriate local-domain statistical model. Under the present dataset and estimation setting, the lognormal distribution provides the best overall fit to azimuthal RCS fluctuations within 1.5° sliding windows. This lognormal assumption is consistent with compact-range measurements of a flying-wing prototype. Finally, the established model is incorporated into radar detectability analysis to illustrate how local RCS uncertainty broadens hazardous angular sectors beyond narrow deterministic peaks. The proposed framework supports uncertainty-aware radar threat assessment of stealth aircraft.
Keywords:
Stealth aircraft
RCS fluctuation
Uncertainty
Detectability assessment
Radar threat assessment
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