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A New Intelligent Reflecting Surface-Aided Electromagnetic Stealth Strategy

Xue Xiong, Beixiong Zheng, A. Lee Swindlehurst, Jie Tang, Wen Wu

TL;DR

This work tackles electromagnetic stealth by integrating an Intelligent Reflecting Surface (IRS) with conventional Electromagnetic Wave Absorbing Materials (EWAM) on a moving target to suppress radar echoes. The authors formulate a convex QCQP to minimize the radar's received $\mathrm{SNR}$ under per-element modulus constraints on the IRS, deriving a semi-closed-form solution via the Karush-Kuhn-Tucker (KKT) framework and solving the dual with SDP. Simulation results demonstrate that the IRS-aided ES system consistently outperforms baselines, achieving near-zero or zero $\mathrm{SNR}$ for sufficiently many IRS elements and across EW absorbing efficiencies, with phase-shift control offering the best performance. The approach enables faster adaptation in dynamic environments and highlights a practical pathway to enhanced stealth through IRS-EWAM cooperation, rather than relying on EWAM alone.

Abstract

Electromagnetic wave absorbing material (EWAM) plays an essential role in manufacturing stealth aircraft, which can achieve the electromagnetic stealth (ES) by reducing the strength of the signal reflected back to the radar system. However, the stealth performance is limited by the coating thickness, incident wave angles, and working frequencies. To tackle these limitations, we propose a new intelligent reflecting surface (IRS)-aided ES system where an IRS is deployed at the target to synergize with EWAM for effectively mitigating the echo signal and thus reducing the radar detection probability. Considering the monotonic relationship between the detection probability and the received signal-to-noise-ratio (SNR) at the radar, we formulate an optimization problem that minimizes the SNR under the reflection constraint of each IRS element, and a semi-closed-form solution is derived by using Karush-Kuhn-Tucker (KKT) conditions. Simulation results validate the superiority of the proposed IRS-aided ES system compared to various benchmarks.

A New Intelligent Reflecting Surface-Aided Electromagnetic Stealth Strategy

TL;DR

This work tackles electromagnetic stealth by integrating an Intelligent Reflecting Surface (IRS) with conventional Electromagnetic Wave Absorbing Materials (EWAM) on a moving target to suppress radar echoes. The authors formulate a convex QCQP to minimize the radar's received under per-element modulus constraints on the IRS, deriving a semi-closed-form solution via the Karush-Kuhn-Tucker (KKT) framework and solving the dual with SDP. Simulation results demonstrate that the IRS-aided ES system consistently outperforms baselines, achieving near-zero or zero for sufficiently many IRS elements and across EW absorbing efficiencies, with phase-shift control offering the best performance. The approach enables faster adaptation in dynamic environments and highlights a practical pathway to enhanced stealth through IRS-EWAM cooperation, rather than relying on EWAM alone.

Abstract

Electromagnetic wave absorbing material (EWAM) plays an essential role in manufacturing stealth aircraft, which can achieve the electromagnetic stealth (ES) by reducing the strength of the signal reflected back to the radar system. However, the stealth performance is limited by the coating thickness, incident wave angles, and working frequencies. To tackle these limitations, we propose a new intelligent reflecting surface (IRS)-aided ES system where an IRS is deployed at the target to synergize with EWAM for effectively mitigating the echo signal and thus reducing the radar detection probability. Considering the monotonic relationship between the detection probability and the received signal-to-noise-ratio (SNR) at the radar, we formulate an optimization problem that minimizes the SNR under the reflection constraint of each IRS element, and a semi-closed-form solution is derived by using Karush-Kuhn-Tucker (KKT) conditions. Simulation results validate the superiority of the proposed IRS-aided ES system compared to various benchmarks.
Paper Structure (7 sections, 21 equations, 4 figures)

This paper contains 7 sections, 21 equations, 4 figures.

Table of Contents

  1. Introduction
  2. System Model
  3. Problem Formulation and Solution
  4. Problem Formulation
  5. Solution of the Proposed Problem
  6. Simulation Results and Discussions
  7. Conclusion

Figures (4)

  • Figure 1: IRS-aided electromagnetic stealth (ES) scenario.
  • Figure 2: SNR versus the number of passive reflecting elements $N_1$ with $N=70$ and $p=0.7$.
  • Figure 3: SNR versus the EW absorbing efficiency $p$ with $N=70$ and $N_1=20$.
  • Figure 4: SNR versus the number of passive reflecting elements $N_1$ with $p=0.7$ and $N_2=40$.