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Intelligent Reflecting Surface-Aided Radar Spoofing

Haozhe Wang, Beixiong Zheng, Xiaodan Shao, Rui Zhang

TL;DR

This work introduces an IRS-aided radar spoofing approach in which an IRS mounted on a moving target suppresses echoes toward a hostile radar while redirecting energy to surrounding clutter to create deceptive AoA information. The problem is formulated as a non-convex optimization to maximize clutter-directed power under a target power constraint, and two solutions are proposed: a high-performance but heavier SDR-based method and a low-complexity Majorization-Minimization (MM) algorithm. Results show that the IRS-aided design significantly increases the clutter echo received by the radar while keeping the target echo under the detection threshold, with the MM method closely matching SDR performance and offering real-time feasibility. This approach offers a flexible, hardware-light alternative to active jamming for radar spoofing with potential implications for electronic warfare and stealth strategies.

Abstract

Electronic countermeasure (ECM) technology plays a critical role in modern electronic warfare, which can interfere with enemy radar detection systems by noise or deceptive signals. However, the conventional active jamming strategy incurs additional hardware and power costs and has the potential threat of exposing the target itself. To tackle the above challenges, we propose a new intelligent reflecting surface (IRS)-aided radar spoofing strategy in this letter, where IRS is deployed on the surface of a target to help eliminate the signals reflected towards the hostile radar to shield the target, while simultaneously redirecting its reflected signal towards a surrounding clutter to generate deceptive angle-of-arrival (AoA) sensing information for the radar. We optimize the IRS's reflection to maximize the received signal power at the radar from the direction of the selected clutter subject to the constraint that its received power from the direction of the target is lower than a given detection threshold. We first solve this non-convex optimization problem using the semidefinite relaxation (SDR) method and further propose a lower-complexity solution for real-time implementation. Simulation results validate the efficacy of our proposed IRS-aided spoofing system as compared to various benchmark schemes.

Intelligent Reflecting Surface-Aided Radar Spoofing

TL;DR

This work introduces an IRS-aided radar spoofing approach in which an IRS mounted on a moving target suppresses echoes toward a hostile radar while redirecting energy to surrounding clutter to create deceptive AoA information. The problem is formulated as a non-convex optimization to maximize clutter-directed power under a target power constraint, and two solutions are proposed: a high-performance but heavier SDR-based method and a low-complexity Majorization-Minimization (MM) algorithm. Results show that the IRS-aided design significantly increases the clutter echo received by the radar while keeping the target echo under the detection threshold, with the MM method closely matching SDR performance and offering real-time feasibility. This approach offers a flexible, hardware-light alternative to active jamming for radar spoofing with potential implications for electronic warfare and stealth strategies.

Abstract

Electronic countermeasure (ECM) technology plays a critical role in modern electronic warfare, which can interfere with enemy radar detection systems by noise or deceptive signals. However, the conventional active jamming strategy incurs additional hardware and power costs and has the potential threat of exposing the target itself. To tackle the above challenges, we propose a new intelligent reflecting surface (IRS)-aided radar spoofing strategy in this letter, where IRS is deployed on the surface of a target to help eliminate the signals reflected towards the hostile radar to shield the target, while simultaneously redirecting its reflected signal towards a surrounding clutter to generate deceptive angle-of-arrival (AoA) sensing information for the radar. We optimize the IRS's reflection to maximize the received signal power at the radar from the direction of the selected clutter subject to the constraint that its received power from the direction of the target is lower than a given detection threshold. We first solve this non-convex optimization problem using the semidefinite relaxation (SDR) method and further propose a lower-complexity solution for real-time implementation. Simulation results validate the efficacy of our proposed IRS-aided spoofing system as compared to various benchmark schemes.
Paper Structure (9 sections, 20 equations, 4 figures)

This paper contains 9 sections, 20 equations, 4 figures.

Table of Contents

  1. Introduction
  2. System Model
  3. Channel Model
  4. Signal Model
  5. Problem Formulation and Solution
  6. SDR-based Solution
  7. Low-Complexity Solution
  8. Numerical Results
  9. Conclusion

Figures (4)

  • Figure 1: An IRS-aided radar spoofing system.
  • Figure 2: Adversarial radar's received power versus AoA direction
  • Figure 3: Received signal power at the adversarial radar from the target/clutter direction versus radar detection threshold, $\gamma$.
  • Figure 4: $\overline{P}_C$ versus radar-clutter angle difference, $\delta_\mathrm{diff}$.