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Enhanced array manifold matrices for L-shaped microphone array-based 2-D DOA estimation

This paper presents an alternative and efficient two-dimensional direction-of-arrival method to estimate multi-narrowband source directions from L-shaped microphone arrays. The problem of estimating direction-of-arrival method of multi-narrowband is considered and resolved by declaring new terms of source and central frequency in array manifold matrices. This new matrices are compatible with most classical subspace-based methods, such as, multiple signal classification and the other cross-correlation based two-dimensional direction-of-arrival estimation method. The performance is evaluated in terms of the root-mean-squared error over a range of the signal-to-noise ratio. Furthermore, simulation results demonstrate that proposed array manifold matrices with the classical subspace-based methods can efficiently handle with acceptable noise levels. In conclusion, the modified method provides a potential alternative to intelligent local positioning systems in voice control applications.