Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Performance analysis of multi-dimensional ESPRIT-type algorithms for
  arbitrary and strictly non-circular sources with spatial smoothing   Spatial smoothing is a widely used preprocessing scheme to improve the
performance of high-resolution parameter estimation algorithms in case of
coherent signals or if only a small number of snapshots is available. In this
paper, we present a first-order performance analysis of the spatially smoothed
versions of R-D Standard ESPRIT and R-D Unitary ESPRIT for sources with
arbitrary signal constellations as well as R-D NC Standard ESPRIT and R-D NC
Unitary ESPRIT for strictly second-order (SO) non-circular (NC) sources. The
derived expressions are asymptotic in the effective signal-to-noise ratio
(SNR), i.e., the approximations become exact for either high SNRs or a large
sample size. Moreover, no assumptions on the noise statistics are required
apart from a zero-mean and finite SO moments. We show that both R-D NC
ESPRIT-type algorithms with spatial smoothing perform asymptotically identical
in the high effective SNR regime. Generally, the performance of spatial
smoothing based algorithms depends on the number of subarrays, which is a
design parameter and needs to be chosen beforehand. In order to gain more
insights into the optimal choice of the number of subarrays, we simplify the
derived analytical R-D mean square error (MSE) expressions for the special case
of a single source. The obtained MSE expression explicitly depends on the
number of subarrays in each dimension, which allows us to analytically find the
optimal number of subarrays for spatial smoothing. Based on this result, we
additionally derive the maximum asymptotic gain from spatial smoothing and
explicitly compute the asymptotic efficiency for this special case. All the
analytical results are verified by simulations.

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The categories of this paper are: cmp-lg
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The categories of this paper are: plasm-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: math-ph
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The categories of this paper are: eess
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The categories of this paper are: patt-sol
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The categories of this paper are: atom-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: hep-ex
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The categories of this paper are: cond-mat
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The categories of this paper are: hep-lat
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The categories of this paper are: stat
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The categories of this paper are: astro-ph
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The categories of this paper are: q-fin
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The categories of this paper are: alg-geom
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The categories of this paper are: adap-org