Combining U-Net Auto-encoder and MUSIC Algorithm for Improving DOA Estimation Accuracy under Defects of Antenna Array

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F25547526%3A_____%2F22%3AN0000001" target="_blank" >RIV/25547526:_____/22:N0000001 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9943003" target="_blank" >https://ieeexplore.ieee.org/document/9943003</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ATC55345.2022.9943003" target="_blank" >10.1109/ATC55345.2022.9943003</a>

Result language
angličtina
Original language name
Combining U-Net Auto-encoder and MUSIC Algorithm for Improving DOA Estimation Accuracy under Defects of Antenna Array
Original language description
Direction of arrival (DOA) estimation plays a crucial role in radio signal surveillance and reconnaissance systems because it provides spatial information to localize radiated signal sources. Conventional DOA estimation algorithms, such as multiple signal classification (MUSIC) and estimation of signal parameters via rotational invariant technique (ESPRIT), are very sensitive to defects of antenna arrays that reduce the accuracy of estimated DOA in real applications. To mitigate this issue, an auto-encoder based on U-Net is proposed to transfer the imperfect covariance matrix to a new one; then, the MUSIC algorithm is applied to the new covariance matrix to estimate the DOAs of incoming signals. The proposed approach is investigated through simulation for a uniform linear array of eight elements with an inter-element space of half-wavelength. The simulation results indicate that our proposed method achieves a good performance in terms of DOA estimation accuracy. In comparison, the proposed model has outperformed the other models, such as conventional MUSIC, ESPRIT, and two other deep neural networks.
Czech name
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Czech description
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Project
<a href="/en/project/TM02000035" target="_blank" >TM02000035: NEO classification of signals (NEOCLASSIG) for radio surveillance systems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
C - Předmět řešení projektu podléhá obchodnímu tajemství (§ 504 Občanského zákoníku), ale název projektu, cíle projektu a u ukončeného nebo zastaveného projektu zhodnocení výsledku řešení projektu (údaje P03, P04, P15, P19, P29, PN8) dodané do CEP, jsou upraveny tak, aby byly zveřejnitelné.

Article name in the collection
Combining U-Net Auto-encoder and MUSIC Algorithm for Improving DOA Estimation Accuracy under Defects of Antenna Array
ISBN
978-1-6654-5188-8
ISSN
2162-1039
e-ISSN
2162-1020
Number of pages
5
Pages from-to
413-417
Publisher name
IEEE
Place of publication
Ha Noi, Vietnam
Event location
Ha Noi, Vietnam
Event date
Jan 1, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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