Polarization-Angle-Frequency Estimation With Linear Nested Vector Sensors

This paper considers the problem of multiple dimensional parameter estimation of radar signals using a linear nested vector sensor array. We propose a computationally efficient polarizationangle-frequency estimation algorithm based on spatial-temporal nested sampling. Radar cross-sections diversity...

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Main Authors:	Xiaodong Han, Ting Shu, Jin He, Wenxian Yu
Format:	Article
Language:	English
Published:	IEEE 2018-01-01
Series:	IEEE Access
Subjects:	Angle and frequency estimation polarization estimation pulsed Doppler nested sampling nested array degree of freedom
Online Access:	https://ieeexplore.ieee.org/document/8401883/

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spelling	doaj-a957506823344bea9d42d3e94712f42c2021-03-29T20:56:51ZengIEEEIEEE Access2169-35362018-01-016369163692610.1109/ACCESS.2018.28509028401883Polarization-Angle-Frequency Estimation With Linear Nested Vector SensorsXiaodong Han0Ting Shu1https://orcid.org/0000-0003-0566-2890Jin He2Wenxian Yu3Shanghai Key Laboratory of Intelligent Sensing and Recognition, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, ChinaShanghai Key Laboratory of Intelligent Sensing and Recognition, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, ChinaShanghai Key Laboratory of Intelligent Sensing and Recognition, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, ChinaShanghai Key Laboratory of Intelligent Sensing and Recognition, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, ChinaThis paper considers the problem of multiple dimensional parameter estimation of radar signals using a linear nested vector sensor array. We propose a computationally efficient polarizationangle-frequency estimation algorithm based on spatial-temporal nested sampling. Radar cross-sections diversity in multiple coherent processing intervals is exploited to construct a virtual polarization-spatialtemporal manifold with extended degrees of freedom. Then, a computational efficient method without eigen-decomposition is derived to estimate Khatri-Rao signal subspace. Automatically paired polarization, azimuth-elevation angles, and doppler frequency estimates are finally obtained by exploiting the idea of the estimation of signal parameters via rotational invariance techniques algorithm. The effectiveness of the proposed method is verified through numerical examples.https://ieeexplore.ieee.org/document/8401883/Angle and frequency estimationpolarization estimationpulsed Dopplernested samplingnested arraydegree of freedom
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Xiaodong Han Ting Shu Jin He Wenxian Yu
spellingShingle	Xiaodong Han Ting Shu Jin He Wenxian Yu Polarization-Angle-Frequency Estimation With Linear Nested Vector Sensors IEEE Access Angle and frequency estimation polarization estimation pulsed Doppler nested sampling nested array degree of freedom
author_facet	Xiaodong Han Ting Shu Jin He Wenxian Yu
author_sort	Xiaodong Han
title	Polarization-Angle-Frequency Estimation With Linear Nested Vector Sensors
title_short	Polarization-Angle-Frequency Estimation With Linear Nested Vector Sensors
title_full	Polarization-Angle-Frequency Estimation With Linear Nested Vector Sensors
title_fullStr	Polarization-Angle-Frequency Estimation With Linear Nested Vector Sensors
title_full_unstemmed	Polarization-Angle-Frequency Estimation With Linear Nested Vector Sensors
title_sort	polarization-angle-frequency estimation with linear nested vector sensors
publisher	IEEE
series	IEEE Access
issn	2169-3536
publishDate	2018-01-01
description	This paper considers the problem of multiple dimensional parameter estimation of radar signals using a linear nested vector sensor array. We propose a computationally efficient polarizationangle-frequency estimation algorithm based on spatial-temporal nested sampling. Radar cross-sections diversity in multiple coherent processing intervals is exploited to construct a virtual polarization-spatialtemporal manifold with extended degrees of freedom. Then, a computational efficient method without eigen-decomposition is derived to estimate Khatri-Rao signal subspace. Automatically paired polarization, azimuth-elevation angles, and doppler frequency estimates are finally obtained by exploiting the idea of the estimation of signal parameters via rotational invariance techniques algorithm. The effectiveness of the proposed method is verified through numerical examples.
topic	Angle and frequency estimation polarization estimation pulsed Doppler nested sampling nested array degree of freedom
url	https://ieeexplore.ieee.org/document/8401883/
work_keys_str_mv	AT xiaodonghan polarizationanglefrequencyestimationwithlinearnestedvectorsensors AT tingshu polarizationanglefrequencyestimationwithlinearnestedvectorsensors AT jinhe polarizationanglefrequencyestimationwithlinearnestedvectorsensors AT wenxianyu polarizationanglefrequencyestimationwithlinearnestedvectorsensors
_version_	1724193861666865152

Polarization-Angle-Frequency Estimation With Linear Nested Vector Sensors

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