Data Association for Multi-Target Elliptic Localization in Distributed MIMO Radars

Autor:	Fereidoon Behnia, Seyed Amir Reza Kazemi, Rouhollah Amiri
Rok vydání:	2021
Předmět:	Optimization problem Noise measurement Computer science Carry (arithmetic) MIMO Location awareness computer.software_genre Computer Science Applications Data association Modeling and Simulation Convergence (routing) Convex optimization Electrical and Electronic Engineering computer Algorithm
Zdroj:	IEEE Communications Letters. 25:2904-2907
ISSN:	2373-7891 1089-7798
DOI:	10.1109/lcomm.2021.3087009
Popis:	In this letter, an efficient method for solving the multi-target localization problem in distributed MIMO radars is proposed. The proposed method attempts to simultaneously carry out the localization and data association tasks by formulating a mixed-integer optimization problem, which is approximated as a convex problem that can be efficiently solved with a polynomial complexity. Numerical simulations substantiate the efficacy of the proposed method.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::dfc8dfc8fde64c829f01cf5c49d37bd1 https://doi.org/10.1109/lcomm.2021.3087009 Zobrazit plný text záznamu