Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Super-Resolution DOA Estimation for Arbitrary Array Geometries Using a
  Single Noisy Snapshot   We address the problem of search-free DOA estimation from a single noisy
snapshot for sensor arrays of arbitrary geometry, by extending a method of
gridless super-resolution beamforming to arbitrary arrays with noisy
measurements. The primal atomic norm minimization problem is converted to a
dual problem in which the periodic dual function is represented with a
trigonometric polynomial using truncated Fourier series. The number of terms
required for accurate representation depends linearly on the distance of the
farthest sensor from a reference. The dual problem is then expressed as a
semidefinite program and solved in polynomial time. DOA estimates are obtained
via polynomial rooting followed by a LASSO based approach to remove extraneous
roots arising in root finding from noisy data, and then source amplitudes are
recovered by least squares. Simulations using circular and random planar arrays
show high resolution DOA estimation in white and colored noise scenarios.

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The categories of this paper are: hep-lat
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The categories of this paper are: nucl-th
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The categories of this paper are: hep-ph
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The categories of this paper are: q-bio
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The categories of this paper are: supr-con
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The categories of this paper are: gr-qc
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The categories of this paper are: patt-sol
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The categories of this paper are: cond-mat
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The categories of this paper are: adap-org
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The categories of this paper are: math-ph
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The categories of this paper are: physics
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The categories of this paper are: nucl-ex
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The categories of this paper are: plasm-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: econ
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The categories of this paper are: chao-dyn