<p>Spherical Harmonic Domain Beamforming (SHB) has become a key technology for indoor sound source localization, widely applied in fields such as modern communications, smart homes, and virtual reality. However, traditional SHB suffers from limitations such as low spatial resolution and severe sidelobe contamination, with its performance significantly degrading when indoor reverberation increases. In this paper, the CLEAN deconvolution beamforming method is introduced to improve the localization performance of the traditional SHB algorithm, resulting in the SHD-CLEAN algorithm. This algorithm utilizes a beamformer that is independent of distance, eliminating the need to pre-determine the distance between the sound source and the array. At the same time, by exploiting the advantage of decoupling frequency and angular components in the spherical harmonic domain, frequency smoothing techniques are introduced, enabling SHD-CLEAN to be applied for indoor reverberant sound source localization without significant computational overhead. Experimental results show that the proposed algorithm achieves excellent localization accuracy in low signal-to-noise ratio, high reverberation, and multi-source scenarios. It does not require prior information about the actual sound sources and offers lower computational complexity with higher spatial resolution.</p>