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• W1975977450 abstract "This paper proposes efficient target localization methods for a passive radar system using bistatic time-of-arrival(TOA) information measured at multiple synthetic array locations, where the position of these synthetic arraylocations is subject to random errors. Since maximum likelihood (ML) formulation of this target localizationproblem is a non-convex optimization problem, semi-definite relaxation (SDR)-based optimization methods ingeneral do not provide satisfactory performance. As a result, approximated ML optimization problems areproposed and solved with SDR plus bisection methods. For the case without position errors, it is shown that therelaxation guarantees a rank-one solution. The optimization problem for the case with position errors involvesonly a relaxation of a scalar quadratic term. Simulation results show that the proposed algorithms outperformexisting methods and provide mean square position error performance very close to the Cramer-Rao lower boundeven for larger values of noise and position estimation errors." @default.
• W1975977450 created "2016-06-24" @default.
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• W1975977450 date "2013-05-28" @default.
• W1975977450 modified "2023-09-27" @default.
• W1975977450 title "Target position localization in a passive radar system through convex optimization" @default.
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• W1975977450 doi "https://doi.org/10.1117/12.2018148" @default.
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