Abstract
Direction of arrival (DOA) estimation has emerged as a promising technology for many military and civilian applications, such as radio astronomy and wireless communications. However, it remains very challenging to estimate DOA for distributed sources within impulsive noise environments. As is widely known, the utilization of the subspace technology in array signal processing can enable high-resolution DOA estimation. In many instances, most of these algorithms assume that the noise is Gaussian. Considering the impulsive noise environments, the derivative of the error function is derived as the iteratively weighted factor in the objective function of low-rank decomposition. Two iterative algorithms are proposed to compute the signal subspace to implement DOA estimation for coherently distributed sources. To further improve the DOA estimation accuracy and increase the number of estimated sources, the virtual data samples are reconstructed from the extended co-prime array. Simulation results confirm that the two proposed impulsive noise suppression algorithms provide better performance than the existing algorithms. The virtual data samples that are reconstructed from the extended co-prime array can be utilized as the effective inputs for subspace-like algorithms.
Highlights
Direction of arrival (DOA) estimation is a fundamental step in wireless location systems, and it has gained widespread attention due to its wide applications in many military and civilian fields including sonar, radar, radio astronomy, and electronic reconnaissance [1]â[4]
We concentrate on improving the performance of DOA estimation for coherently distributed (CD) sources in the symmetric alpha-stable (SÎąS) impulsive noise
For subspace-based algorithms, the signal subspace and noise subspace can be obtained by performing singular value decomposition (SVD) to the weighted matrix W X; because the iteratively weighted factor W depends on the residual matrix Îľ that contains the unknown matrices Y and Z, we must adopt an iterative method
Summary
Direction of arrival (DOA) estimation is a fundamental step in wireless location systems, and it has gained widespread attention due to its wide applications in many military and civilian fields including sonar, radar, radio astronomy, and electronic reconnaissance [1]â[4]. [27] proposes a novel ESPRIT-based 2D localization approach for ID sources in massive or large-scale multiple-input multiple-output (MIMO) systems This method constructs the signal subspace for estimating the nominal azimuth and elevation DOAs and the angular spreads. We concentrate on improving the performance of DOA estimation for CD sources in the symmetric alpha-stable (SÎąS) impulsive noise. To improve the performance of DOA estimates and increase estimated sources through a limited number of array sensors, we apply the extended co-prime array and derive a reconstruction method of virtual data samples, which can be employed as inputs for arbitrary DOA estimation algorithms. The virtual consecutive ULA corresponding to {â17,â16, ¡ ¡ ¡ , â1, 0, 1, ¡ ¡ ¡ , 16, 17}d can be obtained
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