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We present a gridless sparse iterative covariance-based estimation method based on alternating projections for direction-of-arrival (DOA) estimation. The gridless DOA estimation is formulated in the reconstruction of Toeplitz-structured low…

Signal Processing · Electrical Eng. & Systems 2023-02-06 Yongsung Park , Peter Gerstoft

In this paper, we study the spectral estimation problem of estimating the locations of a fixed number of point sources given multiple snapshots of Fourier measurements in a bounded domain. We aim to provide a mathematical foundation for…

Image and Video Processing · Electrical Eng. & Systems 2025-06-27 Ping Liu , Sanghyeon Yu , Ola Sabet , Lucas Pelkmans , Habib Ammari

This paper tackles the challenge of one-bit off-grid direction of arrival (DOA) estimation in a single snapshot scenario based on a learning-based Bayesian approach. Firstly, we formulate the off-grid DOA estimation model, utilizing the…

Signal Processing · Electrical Eng. & Systems 2024-12-17 Yunqiao Hu , Shunqiao Sun , Yimin D. Zhang

In this paper, a new signal processing framework is proposed, in which the array time samples are represented in DOA-frequency domain through a single stage problem. It is shown that concatenated array data is well represented in a…

Signal Processing · Electrical Eng. & Systems 2019-05-06 Shervin Amirsoleimani , Ali Olfat

This paper presents an efficient optimization technique for super-resolution two-dimensional (2D) direction of arrival (DOA) estimation by introducing a new formulation of atomic norm minimization (ANM). ANM allows gridless angle estimation…

Signal Processing · Electrical Eng. & Systems 2022-04-27 Zhi Tian , Zhe Zhang , Yue Wang

This paper focuses on the gridless direction-of-arrival (DoA) estimation for data acquired by non-uniform linear arrays (NLAs) in automotive applications. Atomic norm minimization (ANM) is a promising gridless sparse recovery algorithm…

Signal Processing · Electrical Eng. & Systems 2023-03-09 Silin Gao , Zhe Zhang , Muhan Wang , Yan Zhang , Jie Zhao , Bingchen Zhang , Yue Wang , Yirong Wu

Estimating the direction of arrival (DOA) of sources is an important problem in aerospace and vehicular communication, localization and radar. In this paper, we consider a challenging multi-source DOA estimation task, where the receiving…

Signal Processing · Electrical Eng. & Systems 2022-02-17 Tom Tirer , Oded Bialer

In this paper, the partial relaxation approach is introduced and applied to DOA estimation using spectral search. Unlike existing methods like Capon or MUSIC which can be considered as single source approximations of multi-source estimation…

Signal Processing · Electrical Eng. & Systems 2024-10-30 Minh Trinh-Hoang , Mats Viberg , Marius Pesavento

This paper proposes design techniques for partially-calibrated sparse linear subarrays and algorithms to perform direction-of-arrival (DOA) estimation. First, we introduce array architectures that incorporate two distinct array categories,…

Signal Processing · Electrical Eng. & Systems 2024-09-04 W. Leite , R. C. de Lamare , Y. Zakharov , W. Liu , M. Haardt

An approach to the estimation of the Direction of Arrival (DOA) of wide-band signals with a planar microphone array is presented. Our algorithm estimates an unambiguous DOA using a single planar array in which the microphones are placed…

Sound · Computer Science 2018-11-19 Rudolf Byker , Thomas Niesler

Sparse arrays have attracted a lot of interests recently for their capability of providing more degrees of freedom than traditional uniform linear arrays. For a mixture of circular and noncircular signals, most of the existing direction of…

Signal Processing · Electrical Eng. & Systems 2020-06-25 Jingjing Cai , Wei Liu , Ru Zong , Yangyang Dong

A simple scheme for joint direction of arrival (DOA) and array manifold estimation for a MIMO array system is proposed, where only two transmit antennas are calibrated initially. It first obtains a set of initial DOA results by employing a…

Information Theory · Computer Science 2013-10-14 Wei Zhang , Wei Liu , Siliang Wu , Ju Wang

Phase wrapping is a major problem in direction-of-arrival (DOA) estimation using phase-difference observations. For a sensor pair with an inter-sensor spacing greater than half of the wavelength ($\lambda/2$) of the signal, phase wrapping…

Signal Processing · Electrical Eng. & Systems 2021-10-22 Hui Chen , Tarig Ballal , Tareq Y. Al-Naffouri

In this paper, we propose a new method to design an annihilating filter (AF) for direction-of-arrival (DOA) estimation of multiple snapshots within an uniform linear array. To evaluate the proposed method, we firstly design a DOA estimation…

Sound · Computer Science 2021-10-14 Son Phan , Lam Pham

In this paper, we develop a new technique to obtain nearly optimal estimates of the computational resolution limits introduced in Appl. Comput. Harmon. Anal. 56 (2022) 402-446; IEEE Trans. Inf. Theory 67(7) (2021) 4812-4827; Inverse Probl.…

Image and Video Processing · Electrical Eng. & Systems 2022-05-17 Ping Liu , Habib Ammari

Direction of arrival (DOA) estimation is mostly performed using specialized arrays that have carefully designed receiver spacing and layouts to match the operating frequency range. In contrast, radio interferometric arrays are designed to…

Instrumentation and Methods for Astrophysics · Physics 2025-12-23 Sarod Yatawatta

The problem of gridless direction of arrival (DOA) estimation is addressed in the non-uniform array (NUA) case. Traditionally, gridless DOA estimation and root-MUSIC are only applicable for measurements from a uniform linear array (ULA).…

Signal Processing · Electrical Eng. & Systems 2021-05-05 Mark Wagner , Yongsung Park , Peter Gerstoft

The purpose of this research is to employ non-uniform arrays in different active and passive sensing applications for both narrowband and wideband operations, while providing a multitude of array processing methodologies that assist in…

Signal Processing · Electrical Eng. & Systems 2018-12-10 Elie Bou Daher

Standard Direction of Arrival (DOA) estimation methods are typically derived based on the Gaussian noise assumption, making them highly sensitive to outliers. Therefore, in the presence of impulsive noise, the performance of these methods…

Machine Learning · Computer Science 2024-05-28 Y. Li , W. Xiao , L. Zhao , Z. Huang , Q. Li , L. Li , R. C. de Lamare

We consider the problem of sparse signal recovery from noisy measurements. Many of frequently used recovery methods rely on some sort of tuning depending on either noise or signal parameters. If no estimates for either of them are…

Information Theory · Computer Science 2020-10-20 Hendrik Bernd Petersen , Peter Jung