Electronic countermeasure (ECM) is crucial for preventing target exposure. However, traditional ECM technologies may exhibit limited adaptability or incur high hardware costs, and may even risk exposing the target. To tackle the above challenges, we propose in this paper an intelligent reflecting surface (IRS)-aided electromagnetic spoofing system, where an IRS is mounted on the target to redirect the reflected signals toward surrounding clusters to create decoy targets for confusing radar detection, while simultaneously making the genuine target invisible to radars. Specifically, we optimize the IRS reflection to maximize the sum received signal power at all radars from the cluster direction and ensure that each radar’s received signal power from the target direction remains below a given detection threshold. For the single-radar and single-cluster setup, we solve the IRS reflection optimization problem by using the Lagrange multiplier method and derive a semi-closed-form optimal solution, which is then generalized to the multi-radar and multi-cluster case. Furthermore, a spoofing performance upper bound for the single-radar case is obtained based on the phase alignment method, and a low-complexity closed-form solution based on minimum mean-square error (MMSE) criteria is developed for the multi-radar case. Additionally, we propose practical low-complexity estimation schemes at the target to acquire angle-of-arrival (AoA) and/or signal power gain information via a small number of receive sensing devices. Simulation results validate the performance advantages of our proposed IRS-aided electromagnetic spoofing system with the proposed IRS reflection designs, as compared to the baseline systems.

This paper investigates the problem of robust beamforming design for dual-function radar-communication (DFRC) systems in complex environments where there exist multiple targets, signal-dependent interferences, imperfect knowledge of the interferences and communication channel state information (CSI). By taking these aspects into account, a robust design is devised via minimizing the total transmit power under the individual SINR constraints on the radar receiver and communication users. An iterative algorithm is developed to optimize the transmit beamformer and radar receive filter. Specifically, the receive filter is first obtained with the aid of the generalized eigenvalue decomposition, then the transmit beamformer is optimized by leveraging the semidefinite relaxation (SDR) technique and Bernstein-type inequality. Numerical simulations are conducted to demonstrate the effectiveness and robustness of the proposed design.

While traditional electromagnetic stealth materials/metasurfaces can render a target virtually invisible to some extent, they lack flexibility and adaptability, and can only operate within a limited frequency and angle range, making it challenging to ensure the expected stealth performance. In view of this, we propose in this paper a new intelligent reflecting surface (IRS)-aided electromagnetic stealth system mounted on targets to evade radar detection, by utilizing the tunable passive reflecting elements of IRS to achieve flexible and adaptive electromagnetic stealth in a cost-effective manner. Specifically, we optimize the IRS's reflection at the target to minimize the sum received signal power of all adversary radars. We first address the IRS's reflection optimization problem using the Lagrange multiplier method and derive a semi-closed-form optimal solution. To meet real-time processing requirements, we further propose a low-complexity closed-form solution based on the minimum mean-square error (MMSE) principle. Simulation results validate the performance advantages of our proposed IRS-aided electromagnetic stealth system with the proposed IRS reflection designs.

High-speed train (HST) communication plays a crucial role in providing reliable data services to passengers inside the trains. However, due to the train’s high mobility, a fast time-varying channel generally exists between the static BS and high-speed users, resulting in severe communication performance degradation. To address this issue, we propose in this paper an intelligent reflecting surface (IRS)-aided HST relaying system, where an IRS is integrated with the relay to aid the data transmission from the BS to the relay. Specifically, an optimization problem is formulated to maximize the received signal-to-noise ratio (SNR) at the relay by jointly optimizing the active transmit beamforming at the BS, the active receive beamforming at the relay, and the passive reflect beamforming at the IRS. To solve this problem, we first decouple it into two simpler sub-problems by leveraging the low-dimensional channel decomposition of the high-dimensional BS-relay channel matrix, and then solve them in closed-form with low complexity. Additionally, an efficient transmission protocol tailored for HST communication systems is proposed to implement channel estimation and beam tracking with low complexity. Simulation results verify the performance gains of the proposed IRS-aided HST relaying system, compared with the traditional relaying scheme without IRS and other benchmark schemes.