A Sliding Window Data Compression Method for Spatial-Time DOA Estimation

This paper presents a sliding window data compression method for spatial-time direction-of-arrival (DOA) estimation using coprime array. The signal model is firstly formulated by jointly using the temporal and spatial information of the impinging sources. Then, a sliding window data compression proc...

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Autores principales:	Pin-Jiao Zhao, Guo-Bing Hu, Li-Wei Wang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Electrical engineering. Electronics. Nuclear engineering TK1-9971 Cellular telephone services industry. Wireless telephone industry HE9713-9715
Acceso en línea:	https://doaj.org/article/64f91c8c873242528ea4e1ad34d9a735
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id	oai:doaj.org-article:64f91c8c873242528ea4e1ad34d9a735
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spelling	oai:doaj.org-article:64f91c8c873242528ea4e1ad34d9a7352021-11-08T02:36:27ZA Sliding Window Data Compression Method for Spatial-Time DOA Estimation1687-587710.1155/2021/9705617https://doaj.org/article/64f91c8c873242528ea4e1ad34d9a7352021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/9705617https://doaj.org/toc/1687-5877This paper presents a sliding window data compression method for spatial-time direction-of-arrival (DOA) estimation using coprime array. The signal model is firstly formulated by jointly using the temporal and spatial information of the impinging sources. Then, a sliding window data compression processing is performed on the array output matrix to realize fast calculation of time average function, and the computational burden has been reduced accordingly. Based on the concept of sum and difference co-array (SDCA), the vectorized conjugate augmented MUSIC is adopted, with which more sources than twice of the physical sensors can be resolved. Additionally, the sparse array robustness to sensor failure has been evaluated by introducing the concept of essential sensors. The theoretical analysis and numerical simulations are provided to confirm the effectiveness performance of the proposed method.Pin-Jiao ZhaoGuo-Bing HuLi-Wei WangHindawi LimitedarticleElectrical engineering. Electronics. Nuclear engineeringTK1-9971Cellular telephone services industry. Wireless telephone industryHE9713-9715ENInternational Journal of Antennas and Propagation, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Electrical engineering. Electronics. Nuclear engineering TK1-9971 Cellular telephone services industry. Wireless telephone industry HE9713-9715
spellingShingle	Electrical engineering. Electronics. Nuclear engineering TK1-9971 Cellular telephone services industry. Wireless telephone industry HE9713-9715 Pin-Jiao Zhao Guo-Bing Hu Li-Wei Wang A Sliding Window Data Compression Method for Spatial-Time DOA Estimation
description	This paper presents a sliding window data compression method for spatial-time direction-of-arrival (DOA) estimation using coprime array. The signal model is firstly formulated by jointly using the temporal and spatial information of the impinging sources. Then, a sliding window data compression processing is performed on the array output matrix to realize fast calculation of time average function, and the computational burden has been reduced accordingly. Based on the concept of sum and difference co-array (SDCA), the vectorized conjugate augmented MUSIC is adopted, with which more sources than twice of the physical sensors can be resolved. Additionally, the sparse array robustness to sensor failure has been evaluated by introducing the concept of essential sensors. The theoretical analysis and numerical simulations are provided to confirm the effectiveness performance of the proposed method.
format	article
author	Pin-Jiao Zhao Guo-Bing Hu Li-Wei Wang
author_facet	Pin-Jiao Zhao Guo-Bing Hu Li-Wei Wang
author_sort	Pin-Jiao Zhao
title	A Sliding Window Data Compression Method for Spatial-Time DOA Estimation
title_short	A Sliding Window Data Compression Method for Spatial-Time DOA Estimation
title_full	A Sliding Window Data Compression Method for Spatial-Time DOA Estimation
title_fullStr	A Sliding Window Data Compression Method for Spatial-Time DOA Estimation
title_full_unstemmed	A Sliding Window Data Compression Method for Spatial-Time DOA Estimation
title_sort	sliding window data compression method for spatial-time doa estimation
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/64f91c8c873242528ea4e1ad34d9a735
work_keys_str_mv	AT pinjiaozhao aslidingwindowdatacompressionmethodforspatialtimedoaestimation AT guobinghu aslidingwindowdatacompressionmethodforspatialtimedoaestimation AT liweiwang aslidingwindowdatacompressionmethodforspatialtimedoaestimation AT pinjiaozhao slidingwindowdatacompressionmethodforspatialtimedoaestimation AT guobinghu slidingwindowdatacompressionmethodforspatialtimedoaestimation AT liweiwang slidingwindowdatacompressionmethodforspatialtimedoaestimation
_version_	1718443101037527040

A Sliding Window Data Compression Method for Spatial-Time DOA Estimation

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