This paper proposes an intelligent reflecting surface (IRS)-aided electromagnetic stealth (ES) system to enhance stealth performance by combining IRS with electromagnetic wave absorbing material (EWAM). The system aims to reduce the radar detection probability by mitigating the echo signal through optimized IRS reflection coefficients. The optimization problem is formulated to minimize the received signal-to-noise ratio (SNR) at the radar under the reflection constraints of each IRS element. A semi-closed-form solution is derived using Karush-Kuhn-Tucker (KKT) conditions. Simulation results show that the proposed IRS-aided ES system outperforms traditional methods in reducing the SNR, achieving lower radar detection probabilities. The system effectively combines the destructive interference of IRS and EWAM reflections to suppress the echo signal, leading to improved stealth performance. The results demonstrate that the proposed system can achieve ideal stealth effectiveness when the number of IRS elements exceeds a certain threshold. The study highlights the potential of IRS in enhancing stealth performance by intelligently controlling the reflection coefficients to reduce or eliminate the reflected signal power towards the radar.This paper proposes an intelligent reflecting surface (IRS)-aided electromagnetic stealth (ES) system to enhance stealth performance by combining IRS with electromagnetic wave absorbing material (EWAM). The system aims to reduce the radar detection probability by mitigating the echo signal through optimized IRS reflection coefficients. The optimization problem is formulated to minimize the received signal-to-noise ratio (SNR) at the radar under the reflection constraints of each IRS element. A semi-closed-form solution is derived using Karush-Kuhn-Tucker (KKT) conditions. Simulation results show that the proposed IRS-aided ES system outperforms traditional methods in reducing the SNR, achieving lower radar detection probabilities. The system effectively combines the destructive interference of IRS and EWAM reflections to suppress the echo signal, leading to improved stealth performance. The results demonstrate that the proposed system can achieve ideal stealth effectiveness when the number of IRS elements exceeds a certain threshold. The study highlights the potential of IRS in enhancing stealth performance by intelligently controlling the reflection coefficients to reduce or eliminate the reflected signal power towards the radar.