Underdetermined direction of arrival (DOA) estimation with coprime array is discussed in the framework of multiple measurement sparse Bayesian learning (MSBL). Exploiting the extended difference coarray, a large
Sparse arrayHierarchical priorMaximum a posteriori (MAP)Variational inferenceThis paper reformulates the problem of direction-of-arrival (DOA) estimation for sparse array from a variational Bayesian perspective. In this context, we propose a hierarchical prior for the signal coefficients that amounts ...
Direction estimation using compressive sampling array processing[ C] 椅 The 15th Workshop on Statistical Signal Processing, IEEE. Cardiff: IEEE, 2009: 625 - 628. [6] 摇 Gretsistas A, Plumbley M D. A multichannel spatial compressed sensing approach for direction of errival estimation[ C] 椅...
In this paper, a sparse array design problem for non-Gaussian signal direction of arrival (DOA) estimation is investigated. Compared with conventional second-order cumulant- (SOC-) based methods, fourth-order cumulant- (FOC-) based methods achieve improved DOA estimation performance by utilizing all...
We propose the STCR method for DOA estimation of coherent signals using MRAs. This is performed by imposing a Toeplitz structure to the array output covariance matrix and defining an underdetermined problem which is solved based on a sparse representation method. We show that this approach achieves...
Shen, X., Tang, J. DOA Estimation of Coherent Sources Using Coprime Array via Reweighted Atomic Norm Minimization.44, 2762–2778 (2025). https://doi.org/10.1007/s00034-024-02938-1 Download citation Received13 June 2024 Revised27 November 2024 ...
LI He,LIU Zhihong,YI Chuijie.Sound source location estimation based on compressed sensing and random linear array[J].Journal of Shandong University of Science and Technology(Natural Science),2020,39(5):122-130. [10]窦慧晶,高立菁,朱子云.基于加权...
3. Partial Dictionary Based Off-Grid DOA Estimation Method 3.1. Sparse Representation Using Partial Dictionary Combine the outputs of subarray 1 and subarray 3 to form the first nested array , whose covariance matrix is (3) where is the combined direction matrix and is a diagonal matrix contain...
Direction-of-arrival (DOA) estimation problem is one of the most important tasks for array signal processing. Conventional methods are limited by either the computational complexity or the resolution. In this paper, a novel deep learning (DL) framework for super-resolution DOA estimation is develope...
In this paper, a sparse array design problem for non-Gaussian signal direction of arrival (DOA) estimation is investigated. Compared with conventional second-order cumulant- (SOC-) based methods, fourth-order cumulant- (FOC-) based methods achieve improved DOA estimation performance by utilizing all...