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14 November 1989 Wide-Band Array Signal Processing Via Spectral Smoothing
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Many efficient signal subspace algorithms have been published on direction finding of narrow-band sources, e.g. MUSIC, ESPRIT. The difficulty of extending these methods to the wide-band cases lies in the fact that the signal vectors from each source doesn't span an one-dimensional subspace. Therefore, all the signal-subspace based algorithms will fail in case of wide-band sources. Recently, several approaches have been suggested to resolve this problem, e.g., the spectral-spatial approach, the coherent signal-subspace (CSS) method, the modal decomposition algorithm. Each of these algorithms has one or several of the following shortcomings: high computational cost, impractical signal model assumption, requirement of initial DOA estimate, complete knowledge of array manifold, etc. In this paper, we present a new and more efficient method for estimating DOA's of multiple wide-band sources via spectral smoothing. The proposed algorithm requires much less computational cost than the existing approaches and doesn't need initial DOA estimate, or specific signal model (ARMA, identical spectrum). If the array of sensors satisfies invariant displacement condition, ESPRIT can be used to eliminate the need of complete knowledge of array manifold and to reduce computational load and memory requirement. Under certain scenarios, the analytical analysis and computer simulation show the better performance of the proposed algorithm than that of the existing approaches mentioned above.
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Guanghan Xu and Thomas Kailath "Wide-Band Array Signal Processing Via Spectral Smoothing", Proc. SPIE 1152, Advanced Algorithms and Architectures for Signal Processing IV, (14 November 1989);

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