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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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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. |
format | Online Article Text |
id | pubmed-5949051 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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