The propagator method for source bearing estimation
Signal Processing
Estimation of nominal direction of arrival and angular spread using an array of sensors
Signal Processing - Special issue on subspace methods, part I: array signal processing and subspace computations
Closed-form multiple invariance ESPRIT
Multidimensional Systems and Signal Processing
Source localization using a sparse representation framework to achieve superresolution
Multidimensional Systems and Signal Processing
Approximate maximum likelihood estimators for array processing inmultiplicative noise environments
IEEE Transactions on Signal Processing
Decoupled estimation of DOA and angular spread for a spatiallydistributed source
IEEE Transactions on Signal Processing
Bearing estimation for a distributed source: modeling, inherentaccuracy limitations and algorithms
IEEE Transactions on Signal Processing
Distributed source localization using ESPRIT algorithm
IEEE Transactions on Signal Processing
Parametric localization of distributed sources
IEEE Transactions on Signal Processing
A Simplified Estimator for Tridimensional Localization of Single Incoherently Distributed Source
Wireless Personal Communications: An International Journal
Derivative-constrained frequency-domain wideband DOA estimation
Multidimensional Systems and Signal Processing
Closed-form estimation of the speed of propagating waves from time measurements
Multidimensional Systems and Signal Processing
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A low-complexity algorithm is presented for the estimation of the nominal direction-of-arrivals (DOAs) of incoherently distributed (ID) sources. The presented algorithm estimates the nominal DOAs of ID sources by a novel propagator method which makes use of the approximate rotational invariance relationship between two closely spaced identical uniform linear arrays. Without any search and the eigendecomposition of the sample covariance matrix, our algorithm can provide lower computational complexity than other known methods. In addition, it can be applied to the multisource scenario with different angular distribution shapes. Simulation results prove the effectiveness of the presented algorithm.