Wideband DOA Estimation via Sparse Bayesian Learning over a Khatri-Rao Dictionary

Abstract

Abstract. This paper deals with the wideband directionof-arrival (DOA) estimation by exploiting the multiple measurement vectors (MMV) based sparse Bayesian learning (SBL) framework. First, the array covariance matrices at different frequency bins are focused to the reference frequency by the conventional focusing technique and then transformed into the vector form. Then a matrix called the Khatri-Rao dictionary is constructed by using the KhatriRao product and the multiple focused array covariance vectors are set as the new observations. DOA estimation is to find the sparsest representations of the new observations over the Khatri-Rao dictionary via SBL. The performance of the proposed method is compared with other wellknown focusing based wideband algorithms and the CramerRao lower bound (CRLB). The results show that it achieves higher resolution and accuracy and can reach the CRLB under relative demanding conditions. Moreover, the method imposes no restriction on the pattern of signal power spectral density and due to the increased number of rows of the dictionary, it can resolve more sources than sensors.

2-D DOA Estimation of LFM Signals Based on Dechirping Algorithm and Uniform Circle Array

“…Mode-space algorithm is a kind of spectral estimation algorithm for the UCA [38], [39] and its central idea is to equalize a UCA to a virtual uniform linear array (ULA) through matrix transformation so that the DOA estimation algorithm based on the ULA can be applied to a UCA. We ignore the details of the mode-space algorithm in the main body and show the results as (17). The details of UCA equalization to ULA are included in Appendix: The derivation of (17).…”

“…We ignore the details of the mode-space algorithm in the main body and show the results as (17). The details of UCA equalization to ULA are included in Appendix: The derivation of (17).…”

“…However, as the LFM signal belongs to a typical non-stationary signal, the traditional subspace algorithms which are based on the stationary signals cannot be applied to such condition. With the development of signal processing technology, people have developed a series of DOA estimation algorithms suitable for wideband signals [13][14][15][16][17][18][19]. In [13], the author uses a triangular array to realize DOA estimation of broadband LFM signals.…”

“…The algorithm shows a good ability to estimate a number of sources that exceed the number of sensors in the array. In [15][16][17][18][19], people use the sparse matrix theory to realize DOA estimation of wideband signals. Since Amin introduces the time-frequency analysis tool to DOA estimation field in 1999 [20], [21], people also have developed a series of DOA estimation algorithms based on the time-frequency analysis tool.…”

DOA Estimation of Multiple LFM Sources Using a STFT-based and FBSS-based MUSIC Algorithm

“…In recent years, the direction of arrival (DOA) estimation has received tremendous attention in different areas, such as radar, sonar and communication [1][2][3][4][5]. Many algorithms, such as multiple signal classification (MUSIC) [6], estimation of signal parameters via rotation invariance techniques (ESPRIT) [7], [8] and their variants based on the Eigen-structure techniques, have been developed over the years and provided satisfactory performance.…”