Cyclostationarity-based DOA estimation algorithms for coherent signals in impulsive noise environments

Abstract

Estimating direction of arrival (DOA) is important in a variety of practical applications. Conventional cyclostationarity-based coherent DOA estimation algorithms are not robust to non-Gaussian α-stable impulsive noise. Additionally, fractional lower-order statistics (FLOS)-based algorithms are tolerant to impulsive noise; however, they experience performance degradation for coherent signals and interference. To overcome these drawbacks, two types of fractional lower-order cyclostationarity-based subspace DOA estimation methods are proposed for coherent signals in the presence of interference and α-stable impulsive noise. The new proposed algorithms exploit the fractional lower-order cyclostationarity properties of the signals and are immune to the impulsive noise and interference. Moreover, they can provide more accurate DOA estimates of coherent signals than conventional cyclostationarity-based and FLOS-based methods. The simulation results illustrate the robustness and effectiveness of the proposed methods for coherent signals based on a comparison with traditional methods. The new algorithms can be used in the presence of a wide range of interference, Gaussian noise, and α-stable distribution impulsive noise environments.

An effective spectrum sensing in cognitive radio networks using improved convolution neural network by glow worm swarm algorithm

“…21 For estimating the cyclic spectra, smoothing frequencies or time smoothing algorithms can be used. 22 However, time-smoothing algorithms have higher efficiency and reliability compared with algorithms for frequency smoothing. 23 The time-smooth cyclic phase diagram can be used as follows to determine the cyclic continuum if the measurement time is as t:…”

“…The period for Ts is indicated by the complex demodulate of w(k) and x(n) by X(Ts) (n, v + α/2), while w(k) represents the data tapering window of T w = Np Ts seconds. FAM is derived from (22). The CS is determined for each portion in the small parts of both frequency planes (v, α).…”

The DOA Estimation Method for Low-Altitude Targets under the Background of Impulse Noise

“…In the literature [24][25][26], the FLOM-MUSIC algorithm based on the fractional lower-order moment (FLOM) was proposed. In the literature [27][28][29], a fractional lower-order cyclic MUSIC (FLOC-MUSIC) algorithm using a fractional lower-order cyclic covariance matrix was proposed. However, these FLOS-based algorithms require prior knowledge of the characteristic exponent of stable distribution.…”

“…Compared with the algorithm in the literature [27][28][29][30][31], the algorithm in this paper does not require large sample sampling and loop iterations, so the computational complexity is low; 3.…”

Selection of the Informative Frequency Band in a Bearing Fault Diagnosis in the Presence of Non-Gaussian Noise—Comparison of Recently Developed Methods

“…In the classical approach of cyclostationary-based techniques the assumption of Gaussian noise is taken under consideration [7,9,[22][23][24][25][26]. However, one can find the papers where the algorithms for the signals with non-Gaussian noise are proposed [27][28][29][30][31][32][33][34][35][36][37][38]. We refer also to the recent paper, where the new definition of the cyclostationary non-Gaussian signal is given, see [27] for more details.…”