Enhanced DOA estimation with co-prime array in the scenario of impulsive noise: a pseudo snapshot augmentation perspective
Résumé
Co-prime array configuration is popular in the
recent development of array signal processing. However, the
assumption of Gaussian noise in most co-prime array process-
ing research leads to model mismatch in practical scenarios
of impulsive noise, therefore has an adverse impact on the
estimation of direction of arrival (DOA) of the incoming sources.
Moreover, co-prime array builds an enlarged virtual array by
vectorizing the covariance matrix of the received signals, where
the equivalent received signals of the virtual array have only a
single snapshot. In this paper, we propose an enhanced fractional
low-order method (EFLOM) for co-prime array configuration
in the scenarios of impulsive noise, from the perspective of
pseudo snapshot augmentation. Since impulsive noise does not
have finite second-order statistics or high-order cumulant, we
construct a series of equivalent covariance matrices by using
phased fractional low-order moments with different orders of the
received signals. Then, the vectorization of the multiple equivalent
covariance matrices can be considered as the equivalent received
signals of virtual array with multiple pseudo snapshots. Since
multiple pseudo snapshots are constructed from the same sources,
additional spatial smoothing preprocessing operations are still
needed for enforced decorrelation. In this paper, we propose an
improved spatial smoothing (ISS) technique by applying the in-
formation of both autocorrelation and cross subarray correlation
in the covariance matrix. Afterwards, the classical multiple signal
classification (MUSIC) is applied for the estimation of DOAs.
In addition, the proposed method can also be extended to the
other sparse array geometrics. The performance of the proposed
method is theoretically verified and simulations are provided
to show its effectiveness in terms of the generalized signal to
noise ratio (GSNR), parameter of impulsive noise, and angle
separation. Simulation results show that the proposed method can
greatly improve the resolution, accuracy, and degrees of freedom
(DOFs) in DOA estimation in presence of impulsive noise.