A Signal Subspace Rotation Method for Localization of Multiple Wideband Sound Sources
This work addresses a domain-specific problem for audio signal processing by providing an incremental improvement in wideband sound source localization.
The paper tackles the problem of extending narrowband sound source localization algorithms to wideband signals by proposing a signal subspace rotation method, which reduces computational complexity without needing extra prior knowledge and demonstrates efficacy and robustness in experiments.
In this paper, the problem of extending narrowband multichannel sound source localization algorithms to the wideband case is addressed. The DOA estimation of narrowband algorithms is based on the estimate of inter-channel phase differences (IPD) between microphones of the sound sources. A new method for wideband sound source DOA estimation based on signal subspace rotation is present. The proposed algorithm normalizes the narrowband signal statistics by rotating the estimated signal subspace to the wideband counterpart in the eigenvector domain. Then the wideband DOA estimate can be obtained by estimating the normalized IPD from these wideband signal statistics. In addition to requiring less computational complexity compared to repeating the narrowband algorithms for all relevant frequencies of wideband signals, the proposed method also does not require any additional prior knowledge. The experimental results demonstrate the efficacy and the robustness of the proposed method.