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Proceedings ArticleDOI

Joint DoA and bandwidth estimation of unknown signals through single snapshot data and MT-BCS approach

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TLDR
A novel strategy for the estimation of the direction-of-arrivals (DoAs) and the bandwidth of multiple signals impinging on a linear array and the spectral correlation allows to improve the accuracy of the DoAs recovery, although the single instant data acquisition, and to have the signals bandwidth.
Abstract
A novel strategy for the estimation of the direction-of-arrivals (DoAs) and the bandwidth of multiple signals impinging on a linear array is introduced. Starting from the voltages measured at the output of the array elements at a single time instant, the retrieval of the DoAs is addressed by means of a customized strategy based on the Multi-Tasks Bayesian Compressive Sensing (MT-BCS) in order to correlate the solutions obtained over different frequency samples. The spectral correlation allows to improve the accuracy of the DoAs recovery, although the single instant data acquisition, and to have an estimation of the signals bandwidth. A preliminary numerical result is reported to shown the behavior of the proposed method.

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Proceedings ArticleDOI

Robust BCS-based Direction-of-Arrival and Bandwidth Estimation of Unknown Signals for Cognitive Radar

TL;DR: A novel strategy based on a customized implementation of the Multi- Tasks Bayesian Compressive Sensing (MT -BCS) is proposed to increase the robustness of the joint DoA-and-BW estimation, thanks to the statistical correlation of multiple frequency data samples acquired at consecutive time instants.
Journal ArticleDOI

MT-BCS-Based DoA and Bandwidth Estimation of Unknown Signals through Multiple Snapshots Data

TL;DR: A preliminary numerical result is reported to show the behavior of the proposed approach to Direction-of-Arrival estimation in multiple snapshots data.
Proceedings ArticleDOI

DoA and Bandwidth Estimation of Unknown Signals Based on MT-BCS through Multiple Snapshots Data

TL;DR: A preliminary numerical result is reported to show the behavior of the proposed approach in different snapshots and noise, and also using RMSE to present numerical results more clearly.
Proceedings ArticleDOI

Joint DoA and BW Estimation of Time-Modulated Linear Array Based on MT-BCS

TL;DR: A customized strategy using Multi-Tasks Bayesian Compressive Sensing (MT-BCS) based on Laplace prior is proposed to improve the accuracy of the joint DoA and BW estimation, thanks to the statistical correlation of multiple frequency data samples acquired at consecutive time instants.
References
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Multiple emitter location and signal parameter estimation

TL;DR: In this article, a description of the multiple signal classification (MUSIC) algorithm, which provides asymptotically unbiased estimates of 1) number of incident wavefronts present; 2) directions of arrival (DOA) (or emitter locations); 3) strengths and cross correlations among the incident waveforms; 4) noise/interference strength.
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ESPRIT-estimation of signal parameters via rotational invariance techniques

TL;DR: Although discussed in the context of direction-of-arrival estimation, ESPRIT can be applied to a wide variety of problems including accurate detection and estimation of sinusoids in noise.
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Two decades of array signal processing research: the parametric approach

TL;DR: The article consists of background material and of the basic problem formulation, and introduces spectral-based algorithmic solutions to the signal parameter estimation problem and contrast these suboptimal solutions to parametric methods.
Journal ArticleDOI

Maximum likelihood localization of multiple sources by alternating projection

TL;DR: An algorithm, referred to as APM, for computing the maximum-likelihood estimator of the locations of simple sources in passive sensor arrays is presented and the convergence of the algorithm to the global maximum is demonstrated for a variety of scenarios.
Journal ArticleDOI

Compressive Sensing in Electromagnetics - A Review

TL;DR: A review of the state-of-the-art and most recent advances of compressive sensing and related methods as applied to electromagnetics can be found in this article, where a wide set of applicative scenarios comprising the diagnosis and synthesis of antenna arrays, the estimation of directions of arrival, and the solution of inverse scattering and radar imaging problems are reviewed.
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