DTCWT-ICA based Improved DOA Estimation of Closely Spaced and Coherent Signals with Uniform Linear Array

Abstract

Direction of Arrival (DOA) estimation is the important stage in a smart antenna that estimates the direction of impinging signals on an antenna array, and the most high-resolution DOA estimation subspace algorithm is Multiple Signal Classification (MUSIC). MUSIC algorithm is best suited for estimating the non-coherent signals due to its accuracy and a high degree of resolution. However, its performance degrades in presence of multipath propagation that has coherent and closely spaced signals and at low Signal to Noise Ratio. Many researchers proposed modifications to the MUSIC algorithm to improve its performance even under multipath, coherent and closely spaced signal environment. This paper focuses on investigating a proposed preprocessing technique, referred to as CW-ICA MUSIC that improves the performance of the MUSIC algorithm under above scenario even at low SNR. Simulation results confirm that the proposed preprocessing technique based on Dual Tree Complex Wavelet Transform (DTCWT) and Independent Component Analysis (ICA) outperforms the reported modified MUSIC algorithms such as Wavelet-MUSIC, and SS-MUSIC.

A Novel DOA Estimation of Closely Spaced Sources Using Attention Mechanism With Conformal Arrays

“…To improve the resolution for DOA estimation in the presence of closely spaced sources, several approaches have been proposed in recent years, but these works are limited to uniform linear arrays (ULAs) [15], [16], [17], [18], [19], [20], [21]. Directional domain filtering was proposed by improving the SNR and rebuilding the covariance matrix [15].…”

ICA based DoA estimation with minimum input data

“…These classical methods can detect the DoA of signals in most general applications 1 and by using additional algorithms overcome some problems, such as estimating the DoA when sources are closely spaced 5 . However, their performance is reduced in some special cases such as overlapping sources, that is, no spatial separation between sources.…”