The propagator method for source bearing estimation
Signal Processing
Fast communication: a fast algorithm for 2-D direction-of-arrival estimation
Signal Processing - Special section: Hans Wilhelm Schüßler celebrates his 75th birthday
Maximum likelihood array processing in spatially correlated noisefields using parameterized signals
IEEE Transactions on Signal Processing
Maximum-likelihood direction-of-arrival estimation in the presenceof unknown nonuniform noise
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Direction estimation in partially unknown noise fields
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Array processing in correlated noise fields based on instrumentalvariables and subspace fitting
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
ESPRIT-based 2-D direction finding with a sparse uniform array ofelectromagnetic vector sensors
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Direction finding using noise covariance modeling
IEEE Transactions on Signal Processing
Source localization using vector sensor array in a multipath environment
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Maximum likelihood DOA estimation and asymptotic Cramer-Rao boundsfor additive unknown colored noise
IEEE Transactions on Signal Processing
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This paper considers a new azimuth-elevation DOA estimation algorithm for multiple signals using electromagnetic vector sensor array. We firstly exploit the planar-plus-an-isolated sensor array geometry (Li et al. in IEE Proc Radar Sonar Navig 143(5):295---299, 1996) to define a full rank cross-covariance matrix. Then we develop an efficient ESPRIT-like algorithm using the so-called propagator to estimate the steering vectors of electromagnetic vector sensor, without performing eigen-decomposition into signal subspaces. Finally, we compute the vector cross product to obtain the closed-form azimuth-elevation angle estimates. The new algorithm does not require 2D iterative searching, and is applicable to coherent (fully correlated) signals and spatially correlated noise. In addition, the proposed algorithm offers enhanced estimation precision by sparse array aperture extension, but suffers no DOA cyclical ambiguity. Monte-Carlo simulations are presented to verify the effectiveness of the proposed algorithm.