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Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors

This paper essentially focuses on parameter estimation of multiple wideband emitting sources with time-varying frequencies, such as two-dimensional (2-D) direction of arrival (DOA) and signal sorting, with a low-cost circular synthetic array (CSA) consisting of only two rotating sensors. Our basic i...

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Detalles Bibliográficos
Autores principales: Zuo, Le, Pan, Jin, Ma, Boyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5949051/
https://www.ncbi.nlm.nih.gov/pubmed/29617323
http://dx.doi.org/10.3390/s18041088
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author Zuo, Le
Pan, Jin
Ma, Boyuan
author_facet Zuo, Le
Pan, Jin
Ma, Boyuan
author_sort Zuo, Le
collection PubMed
description This paper essentially focuses on parameter estimation of multiple wideband emitting sources with time-varying frequencies, such as two-dimensional (2-D) direction of arrival (DOA) and signal sorting, with a low-cost circular synthetic array (CSA) consisting of only two rotating sensors. Our basic idea is to decompose the received data, which is a superimposition of phase measurements from multiple sources into separated groups and separately estimate the DOA associated with each source. Motivated by joint parameter estimation, we propose to adopt the expectation maximization (EM) algorithm in this paper; our method involves two steps, namely, the expectation-step (E-step) and the maximization (M-step). In the E-step, the correspondence of each signal with its emitting source is found. Then, in the M-step, the maximum-likelihood (ML) estimates of the DOA parameters are obtained. These two steps are iteratively and alternatively executed to jointly determine the DOAs and sort multiple signals. Closed-form DOA estimation formulae are developed by ML estimation based on phase data, which also realize an optimal estimation. Directional ambiguity is also addressed by another ML estimation method based on received complex responses. The Cramer-Rao lower bound is derived for understanding the estimation accuracy and performance comparison. The verification of the proposed method is demonstrated with simulations.
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spelling pubmed-59490512018-05-17 Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors Zuo, Le Pan, Jin Ma, Boyuan Sensors (Basel) Article This paper essentially focuses on parameter estimation of multiple wideband emitting sources with time-varying frequencies, such as two-dimensional (2-D) direction of arrival (DOA) and signal sorting, with a low-cost circular synthetic array (CSA) consisting of only two rotating sensors. Our basic idea is to decompose the received data, which is a superimposition of phase measurements from multiple sources into separated groups and separately estimate the DOA associated with each source. Motivated by joint parameter estimation, we propose to adopt the expectation maximization (EM) algorithm in this paper; our method involves two steps, namely, the expectation-step (E-step) and the maximization (M-step). In the E-step, the correspondence of each signal with its emitting source is found. Then, in the M-step, the maximum-likelihood (ML) estimates of the DOA parameters are obtained. These two steps are iteratively and alternatively executed to jointly determine the DOAs and sort multiple signals. Closed-form DOA estimation formulae are developed by ML estimation based on phase data, which also realize an optimal estimation. Directional ambiguity is also addressed by another ML estimation method based on received complex responses. The Cramer-Rao lower bound is derived for understanding the estimation accuracy and performance comparison. The verification of the proposed method is demonstrated with simulations. MDPI 2018-04-04 /pmc/articles/PMC5949051/ /pubmed/29617323 http://dx.doi.org/10.3390/s18041088 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zuo, Le
Pan, Jin
Ma, Boyuan
Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors
title Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors
title_full Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors
title_fullStr Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors
title_full_unstemmed Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors
title_short Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors
title_sort parameter estimation of multiple frequency-hopping signals with two sensors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5949051/
https://www.ncbi.nlm.nih.gov/pubmed/29617323
http://dx.doi.org/10.3390/s18041088
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