Wideband acoustic source localization using multiple spherical arrays : anangular-spectrum smoothing approach

A novel algorithm using multiple spherical arrays based on spherical harmonic analysis is proposed to localize wideband acoustic sources. In the novel spherical harmonic algorithm, the re- ceived microphone signals are firstly used to do the spherical Fourier transformation. Then, the mul- tiple signal classification （MUSIC） algorithm is applied to the spherical components to obtain the an- gular-spectrum. Finally, the angular-spectrum smoothing technique is proposed to obtain the accu- rate localization of wideband sources. In contrast to the traditional single spherical array, the multi- pie spherical arrays used in this paper consist of several randomly distributed spheres in a given plane. The microphones are uniformly placed on each sphere, the same as the usual single spherical array. Simulation comparison of wideband sources localization between a single spherical array and multiple spherical arrays based on the novel algorithm is carried out to validate our proposed meth- od.

DOA estimation of wideband signals based on iterative spectral reconstruction

In order to solve the problem of coherent signal subspace method(CSSM) depending on the estimated accuracy of signal subspace, a new direction of arrival(DOA) estimation method of wideband source, which is based on iterative adaptive spectral reconstruction, is proposed. Firstly, the wideband signals are divided into several narrowband signals of different frequency bins by discrete Fourier transformation(DFT). Then, the signal matched power spectrum in referenced frequency bins is computed, which can form the initial covariance matrix. Finally, the linear restrained minimum variance spectral(Capon spectral) of signals in other frequency bins are reconstructed using sequential iterative means, so the DOA can be estimated by the locations of spectral peaks. Theoretical analysis and simulation results show the proposed method based on the iterative spectral reconstruction for the covariance matrices of all sub-bands can avoid the problem of determining the signal subspace accurately with the coherent signal subspace method under the conditions of small samples and low signal to noise ratio(SNR), and it can also realize full dimensional focusing of different sub-band data, which can be applied to coherent sources and can significantly improve the accuracy of DOA estimation.

Wideband direction-of-arrival estimation based on cubic spline function

A new direction-of-arrival （DOA） estimation algorithm for wideband sources is introduced, The new method obtains the output of the virtual arrays in the signal bandwidth using cubic spline function interpolation techniques. The narrowband high- resolution algorithm is then used to get the DOA estimation. This technique does not require any preliminary knowledge of DOA angles. Simulation results demonstrate the effectiveness of the method.