Multi-target elliptic positioning via difference of convex functions programming

Multi-target localization in a distributed multiple-input multiple-output radar is quite challenging as the correct measurement-target associations in each transmitter–receiver pair are unknown. In this paper, we address this difficult problem from a joint optimization perspective. The measurement-t...

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Vydané v:	Signal processing Ročník 234; s. 109996
Hlavní autori:	Dang, Xudong, Liu, Hongwei, Yan, Junkun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.09.2025
Predmet:	Convex optimization Data association Difference of convex functions Distributed MIMO radar Multi-target localization Difference of convex functions Multi-target localization Convex optimization Distributed MIMO radar Data association
ISSN:	0165-1684
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Shrnutí:	Multi-target localization in a distributed multiple-input multiple-output radar is quite challenging as the correct measurement-target associations in each transmitter–receiver pair are unknown. In this paper, we address this difficult problem from a joint optimization perspective. The measurement-target association and multi-target localization are jointly formulated as an intractable mixed-integer optimization problem, which contains both discrete and continuous variables. We first develop an equivalent Difference of Convex functions (DC) representation for the non-convex Boolean constraint imposed on the association variables, making the problem tractable. Then, a DC algorithm is derived to efficiently solve the resulting optimization problem. Simulation results demonstrate that the proposed DC method is numerically accurate when compared to state-of-the-art methods.
ISSN:	0165-1684
DOI:	10.1016/j.sigpro.2025.109996