Mapping Radar Cross-Section Hotspots with Statistical Characterization & Detection Probability Analysis of Stealth Aircraft

Abstract

The Radar Cross Section (RCS) of stealth aircraft exhibits strong dependence on azimuth angle, requiring a statistical approach for analyzing probability of detection under variable illumination conditions. This study investigates the RCS behavior of the B-2 Spirit at 300 MHz under monostatic and bistatic radar configurations incorporating both vertical and horizontal polarizations. High-resolution RCS simulations are performed using a validated CAD model, and heatmaps are generated to identify angular regions that exhibit peak scattering. These scattering hotspots are shown to occur only at specific incidence angles, strongly influencing detection outcomes. To statistically quantify this behavior, the RCS data are segmented into angular sectors and modeled with simple unimodal distributions. Probability of detection is estimated using Monte Carlo simulations across all sectors under varying signal-to-noise ratios. The results reveal that certain bistatic configurations achieve higher detection probabilities at lower SNRs compared to monostatic setups, emphasizing the role of geometrical diversity in enhancing stealth detectability. Furthermore, small variations in illumination angle produce large differences in detection performance, reflecting the aerodynamic and structural shaping strategies used in stealth design. These findings highlight the importance of localized statistical characterization for stealth targets and offer a foundation for optimizing radar deployment and detection strategy planning in operational scenarios.