  Wideband direction of arrival (DOA) estimation techniques for sensors array
have been studied extensively in the literature. Nevertheless, needing prior
information on the number and directions of sources or demanding heavy
computational load makes most of these techniques less useful in practice. In
this paper, a low complexity subspace-based framework for DOA estimation of
broadband signals, named as wideband modal orthogonality (WIMO), is proposed
and accordingly two DOA estimators are developed. First, a closed-form
approximation of spatial-temporal covariance matrix (STCM) in the uniform
spectrum case is presented. The eigenvectors of STCM associated with non-zero
eigenvalues are modal components of the wideband source in a given bandwidth
and direction. WIMO idea is to extract these eigenvectors at desired DOAs from
the approximated STCM and test their orthogonality to estimated noise subspace.
In the non-uniform spectrum case, WIMO idea can be applied by approximating
STCM through numerical integration. Fortunately, STCM approximation and modal
extraction can be performed offline. WIMO provides DOA estimation without the
conventional prerequisites, such as spectral decomposition, focusing procedure
and, a priori information on the number of sources and their DOAs. Several
numerical examples are conducted to compare the WIMO performance with the
state-of-the-art methods. Simulations demonstrate that the two proposed DOA
estimators achieve superior performance in terms of probability of resolution
and estimation error along with orders of magnitude runtime speedup.
