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Demixing sines and spikes using multiple measurement vectors
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
EURECOM- Communication Systems.
School of Electrical Engineering, Iran University of Science & Technology.
2023 (engelsk)Inngår i: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 203, artikkel-id 108786Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

We address the line spectral estimation problem with multiple measurement corrupted vectors. Such scenarios appear in many practical applications such as radar, optics, and seismic imaging in which the measurements can be modeled as the sum of a spectrally sparse and a block-sparse signal known as outlier. Our aim is to demix the two components and for this purpose, we design a convex problem whose objective function promotes both of the structures. Using the Positive Trigonometric Polynomials (PTP) theory, we reformulate the dual problem as a Semidefinite Program (SDP). Our theoretical results state that for a fixed number of measurements N and constant number of outliers, up to O(N) spectral lines can be recovered using our SDP problem as long as a minimum frequency separation condition is satisfied. Our simulation results also show that increasing the number of samples per measurement vectors reduces the minimum required frequency separation for successful recovery.

sted, utgiver, år, opplag, sider
Elsevier, 2023. Vol. 203, artikkel-id 108786
Emneord [en]
Atomic norm, Convex optimization, Demixing, Multiple measurement vector, Spectral super resolution
HSV kategori
Identifikatorer
URN: urn:nbn:se:umu:diva-200382DOI: 10.1016/j.sigpro.2022.108786ISI: 000872558500013Scopus ID: 2-s2.0-85139348869OAI: oai:DiVA.org:umu-200382DiVA, id: diva2:1709194
Tilgjengelig fra: 2022-11-08 Laget: 2022-11-08 Sist oppdatert: 2023-09-05bibliografisk kontrollert

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Maskan, Hoomaan

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