<p>As the depth of coal mining increases, the risk of rockbursts escalates, necessitating advancements in microseismic monitoring technologies. This study aims to develop a localization method for microseismic events, particularly in low signal-to-noise ratio (SNR) environments prevalent in coal mining operations. The method leverages the Enhanced Dynamic Disturbance Index (EDDI) to improve noise suppression and location accuracy without the necessity of onset time picking. The research introduces a cross-correlation stacking method incorporating EDDI, which enhances the signal's dynamic disturbance attributes for better identification and localization of seismic events. This method contrasts traditional Kirchhoff migration and semblance stacking techniques, which often suffer from noise issues and velocity model inaccuracies. Numerical simulations in a homogenous velocity model were conducted to evaluate the method's performance under varying noise levels and velocity perturbations. The EDDI-based cross-correlation stacking method demonstrated superior resistance to noise and velocity model errors compared to conventional methods. It consistently achieved high localization accuracy, particularly in scenarios with up to 70% noise level, significantly outperforming other tested methods in terms of focusing energy and minimizing localization errors across multiple seismic stations. The EDDI-enhanced cross-correlation stacking method offers a promising solution for high-precision microseismic event localization, especially suitable for low-SNR conditions. While it requires more computational resources, its high accuracy and robustness against noise and velocity errors make it an excellent choice for complex underground environments.</p>