From the co-array perspective, sparse spatial sampling can significantly increase the
degrees-of-freedom (DOFs), enabling us to perform underdetermined direction-of-arrival …

Parameter estimation from multiple measurement vectors (MMVs) is a fundamental problem
in many signal processing applications, eg, spectral analysis and direction-of-arrival …

针对采用1 l 范数优化的稀疏表示DOA 估计算法正则化参数选取困难, 计算复杂度高的问题,
该文提出一种基于稀疏贝叶斯学习的高效算法. 该算法首先利用均匀线阵的结构特性, 将DOA …

This paper introduces a subspace method for the estimation of an array covariance matrix.
When the received signals are uncorrelated, it is shown that the array covariance matrices …

This thesis addresses several challenges in Bayesian target tracking, particularly for array
signal processing applications, and for multiple targets. The optimal method for multiple …

Abstract The Khatri-Rao (KR) subspace method is a high resolution method for direction-of-
arrival (DOA) estimation. Combined with 2 q level nested array, the KR subspace method …

A common assumption in many speech and acoustic processing methods is that the noise is
white and Gaussian (WGN). Although making this assumption results in simple and …

The traditional super-resolution direction finding methods based on sparse recovery need to
divide the estimation space into several discrete angle grids, which will bring the final result …

We propose a new direction of arrival estimation method for wideband uncorrelated signals.
The wideband signals are first decomposed into narrowband signals. A group sparse Lasso …

Estimation of azimuth and elevation angles of both Angle of Arrival and Angle of Departure
is a challenging research topic in 5G smart antenna technology. The key contributions of this …