Sound source localization in environments characterized by high reverberation has garnered significant scholarly interest. Among the methods employed for this purpose, the Steered-Response Power Phase Transform (SRP-PHAT) is particularly noteworthy for its efficacious performance. However, the method is not without its limitations. While the phase transformation technique effectively mitigates multipath channel distortion, it concurrently accentuates irrelevant spectral components in scenarios of low signal-to-noise ratio (SNR), leading to potential inaccuracies in source localization. This issue is especially pronounced in environments marked by both low SNR and intense reverberation, where the efficacy of the phase transformation method markedly declines. Moreover, the SRP-PHAT algorithm's reliance on enumerating all potential sound sources and subsequently conducting a search for power peaks to localize the sound source results in significant computational demands. To address these shortcomings, this study introduces an enhanced weighting function aimed at refining the accuracy of sound source direction estimation within high-reverberation acoustic settings. Furthermore, this research incorporates the Beetle Swarm Optimization (BSO) algorithm in conjunction with the SRP-PHAT algorithm. This integration significantly diminishes the computational burden, thereby bolstering the algorithm's real-time operational capability.