Deep-Sparse Array Cognitive Radar

Basit Öğe Kaydı
dc.authoridElbir, Ahmet M./0000-0003-4060-3781
dc.authorwosidElbir, Ahmet M./X-3731-2019
dc.contributor.authorElbir, Ahmet M.
dc.contributor.authorMulleti, Satish
dc.contributor.authorCohen, Regev
dc.contributor.authorFu, Rong
dc.contributor.authorEldar, Yonina C.
dc.date.accessioned2021-12-01T18:50:17Z
dc.date.available2021-12-01T18:50:17Z
dc.date.issued2019
dc.department[Belirlenecek]en_US
dc.description13th International Conference on Sampling Theory and Applications (SampTA) -- JUL 08-12, 2019 -- Bordeaux, FRANCEen_US
dc.description.abstractIn antenna array based radar applications, it is often desirable to choose an optimum subarray from a full array to achieve a balance between hardware cost and resolution. Moreover, in a cognitive radar system, the sparse subarrays are chosen based on the target scenario at that instant. Recently, a deep-learning based antenna selection technique was proposed for a single target scenario. In this paper, we extend this approach to multiple targets and assess the performance of state-of-the-art direction of arrival estimation techniques in conjunction with the proposed antenna selection method. To optimally choose the subarrays based on the target DOAs, we design a convolutional neural network which accepts the array covariance matrix as an input and selects the best sparse subarray that minimizes the error. Once the optimum sparse subarray is obtained, the signals from the selected antennas are used to estimate the DOAs. We provide numerical simulations to validate the performance of the proposed cognitive array selection strategy. We show that the proposed approach outperforms random sparse antenna selection and it leads to a higher DOA estimation accuracy by 6 dB.en_US
dc.description.sponsorshipAir Force Office of Scientific ResearchUnited States Department of DefenseAir Force Office of Scientific Research (AFOSR) [FA9550-18-1-0208]en_US
dc.description.sponsorshipThis project has received funding from the Air Force Office of Scientific Research under grant No. FA9550-18-1-0208.en_US
dc.identifier.isbn978-1-7281-3741-4
dc.identifier.urihttps://hdl.handle.net/20.500.12684/10854
dc.identifier.wosWOS:000558176800017en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherIeeeen_US
dc.relation.ispartof2019 13Th International Conference On Sampling Theory And Applications (Sampta)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSelectionen_US
dc.titleDeep-Sparse Array Cognitive Radaren_US
dc.typeConference Objecten_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
Ä°sim:
10854.pdf
Boyut:
602.56 KB
Biçim:
Adobe Portable Document Format
Açıklama:
Tam Metin / Full Text
Ä°ndir

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu