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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Main Authors: Zuo, Le, Pan, Jin, Ma, Boyuan
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2018
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Online Access:https://hdl.handle.net/10356/89039
http://hdl.handle.net/10220/44758
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-890392020-03-07T13:57:31Z Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors Zuo, Le Pan, Jin Ma, Boyuan School of Electrical and Electronic Engineering DOA Estimation Synthetic Array 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. Published version 2018-05-09T01:54:12Z 2019-12-06T17:16:32Z 2018-05-09T01:54:12Z 2019-12-06T17:16:32Z 2018 Journal Article Zuo, L., Pan, J., & Ma, B. (2018). Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors. Sensors, 18(4), 1088-. 1424-8220 https://hdl.handle.net/10356/89039 http://hdl.handle.net/10220/44758 10.3390/s18041088 en Sensors © 2018 by The Author(s). 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/). 15 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DOA Estimation
Synthetic Array
spellingShingle DOA Estimation
Synthetic Array
Zuo, Le
Pan, Jin
Ma, Boyuan
Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors
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.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Zuo, Le
Pan, Jin
Ma, Boyuan
format Article
author Zuo, Le
Pan, Jin
Ma, Boyuan
author_sort Zuo, Le
title Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors
title_short 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_sort parameter estimation of multiple frequency-hopping signals with two sensors
publishDate 2018
url https://hdl.handle.net/10356/89039
http://hdl.handle.net/10220/44758
_version_ 1681047718250676224