RIS-Enabled Spoofing Against Adversary Sensing: CRB-Maximizing Design and Decoying Analysis

TL;DR

This work demonstrates how a RIS coated UE can deceive a monostatic radar by nulling the true reflection while creating a controllable decoy at a chosen angle. A compact RIS kernel model links the radar's angular response to the RIS phase profile, enabling CRB/Fisher information analysis that shows AoA accuracy scales with kernel power. The authors formulate and solve an RIS design using an alternating-projection approach to enforce deep nulls on the true AoA and maximize decoy gain, and they introduce the ρ-deception criterion and a decoy-angle score to quantify and guide deception. Numerical results confirm deep nulls at the true AoA and a pronounced decoy peak, making ML-based AoA estimation unreliable for the RIS-covered target, highlighting the practical potential and limits of RIS-enabled spoofing in ISAC contexts.

Abstract

This paper studies the capability of a Reconfigurable Intelligent Surface (RIS), when transparently covering a User Equipment (UE), to deceive an adversary monostatic radar system. A compact RIS kernel model that explicitly links the radar's angular response to the RIS phase profile is introduced, enabling an analytical investigation of the Angle of Arrival (AoA) estimation accuracy with respect to the kernel's power. This model is also leveraged to formulate an RIS-based spoofing design with the dual objective to enforce strict nulls around the UE's true reflection AoA and maximize the channel gain towards a decoy direction. The RIS's deception capability is quantified using point-wise and angle-range robust criteria, and a configuration-independent placement score guiding decoy selection is proposed. Selected numerical results confirm deep nulls at the true reflection AoA together with a pronounced decoy peak, rendering maximum-likelihood sensing at the adversary radar unreliable.

Figures (4)

• Figure 1: Normalized RIS beampattern gain (left) and corresponding ML-based AoA spectrum (right) considering a radar BS with $N=16$ antennas and an RIS with $M=32$ elements. $K=10$ nulling angles have been imposed over a $\Delta=3^{\circ}$ angle window; the decoy and true AoAs were $\theta_{\text{fake}}=-48^{\circ}$ and $\theta_{\text{true}}=20^{\circ}$, respectively.
• Figure 2: PEB heatmaps before (left) and after (right) the proposed RIS-enabled spoofing using the parameters of Fig. \ref{['fig:beam_ML']}. Before optimization, the monostatic radar exhibits a sharp PEB with a minimum at the true AoA, whereas, after optimization, the PEB minimum shifts to the prescribed decoy angle, while the true angle is obfuscated without any distinct minimum remaining at the actual UE direction.
• Figure 3: Leakage ratio $L_{\rm true}(\boldsymbol{\omega})/|\bar{\beta}(\theta_{\text{fake}};\boldsymbol{\omega})|$ versus the decoy angle $\theta_{\text{fake}}$ including the thresholds $\sqrt{\kappa(\theta_{\text{fake}})/(\rho\kappa_{\min})}$ for various $\rho$-deception levels, using the optimized RIS phase profile of Fig. \ref{['fig:beam_ML']}. It is shown that, although the design yields low leakage at $\theta_{\text{fake}}=-48^{\circ}$, it is not globally optimal, as the hard-null constraint prioritizes enforcing a banded null around the angle $\theta_{\text{true}}=20^{\circ}$.
• Figure 4: The upper bound $\rho_{\text{UB}}$ versus the decoy AoA $\theta_{\text{fake}}$ for several leakage caps $\overline{L}$. As observed, varying $\overline{L}$ scales the bound vertically without shifting the peak. The plot also delineates the nulled window around $\theta_{\text{true}}$ where deception is unattainable from the region of the feasible decoy AoAs.