Space Time MUSIC: Consistent Signal Subspace Estimation for Wide-band Sensor Arrays
Elio D. Di Claudio, Raffaele Parisi, Giovanni Jacovitti

TL;DR
This paper introduces a space-time MUSIC method for wide-band DOA estimation that overcomes spectral leakage issues and achieves consistent signal subspace recovery using a finite impulse response array model.
Contribution
It develops a novel ST-MUSIC estimator based on maximum likelihood that ensures consistency in wide-band DOA estimation under realistic array models.
Findings
Outperforms existing binning methods at high SNR
Provides consistent subspace estimation under realistic array assumptions
Effective in scenarios with model mismatches
Abstract
Wide-band Direction of Arrival (DOA) estimation with sensor arrays is an essential task in sonar, radar, acoustics, biomedical and multimedia applications. Many state of the art wide-band DOA estimators coherently process frequency binned array outputs by approximate Maximum Likelihood, Weighted Subspace Fitting or focusing techniques. This paper shows that bin signals obtained by filter-bank approaches do not obey the finite rank narrow-band array model, because spectral leakage and the change of the array response with frequency within the bin create \emph{ghost sources} dependent on the particular realization of the source process. Therefore, existing DOA estimators based on binning cannot claim consistency even with the perfect knowledge of the array response. In this work, a more realistic array model with a finite length of the sensor impulse responses is assumed, which still has…
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