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Performance Evaluation of High Power Microwave Systems Against UAVs A Probabilistic Antenna Propagation Framework with Sensitivity Analysis

Signal Processing 2025-10-21 v1

Abstract

We develop a probabilistic, antenna- and propagation-centric framework to quantify the effectiveness of high-power microwave (HPM) engagements against unmanned aerial vehicles (UAVs). The model couples stochastic UAV kinematics, a beam-steering jitter-to-gain mapping, and atmospheric propagation (free-space spreading with gaseous and rain loss) to obtain closed-form statistics of the received pulse energy. From these, we derive analytically evaluable per-pulse and cumulative neutralization probabilities using log-normal closures and Gaussian--Hermite quadrature, and we provide a dwell-time expression under a standard pulse-independence assumption. Analytical predictions closely match large-scale Monte-Carlo simulations across broad parameter ranges. For a representative commercial threshold Eth=102JE_{\mathrm{th}} = 10^{-2}\,\mathrm{J}, the model predicts Pˉkill0.4\bar{P}_{\mathrm{kill}} \gtrsim 0.4 per pulse and Pkill,tot>99%P_{\mathrm{kill,tot}} > 99\% within about 0.1s0.1\,\mathrm{s} at kHz PRF; for hardened platforms with Eth=101JE_{\mathrm{th}} = 10^{-1}\,\mathrm{J}, Pˉkill<1%\bar{P}_{\mathrm{kill}} < 1\% and Pkill,tot<20%P_{\mathrm{kill,tot}} < 20\% after 1s1\,\mathrm{s}. A closed-form sensitivity (elasticity) analysis shows performance is dominated by slant range (SRˉ2S_{\bar{R}} \approx -2), with strong secondary dependence on aperture diameter and transmit power; pointing jitter and atmospheric variability are comparatively less influential in the evaluated regimes. The framework yields fast, accurate, and physics-faithful performance predictions and exposes clear antenna/propagation design levers for HPM system sizing and risk-aware mission planning.

Keywords

Cite

@article{arxiv.2510.16495,
  title  = {Performance Evaluation of High Power Microwave Systems Against UAVs A Probabilistic Antenna Propagation Framework with Sensitivity Analysis},
  author = {Muhammad Khalil and Ke Wang and Jinho Choi},
  journal= {arXiv preprint arXiv:2510.16495},
  year   = {2025}
}

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