
Proceedings Paper
Target position localization in a passive radar system through convex optimizationFormat | Member Price | Non-Member Price |
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Paper 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 array
locations is subject to random errors. Since maximum likelihood (ML) formulation of this target localization
problem is a non-convex optimization problem, semi-definite relaxation (SDR)-based optimization methods in
general do not provide satisfactory performance. As a result, approximated ML optimization problems are
proposed and solved with SDR plus bisection methods. For the case without position errors, it is shown that the
relaxation guarantees a rank-one solution. The optimization problem for the case with position errors involves
only a relaxation of a scalar quadratic term. Simulation results show that the proposed algorithms outperform
existing methods and provide mean square position error performance very close to the Cramer-Rao lower bound
even for larger values of noise and position estimation errors.
Paper Details
Date Published: 28 May 2013
PDF: 10 pages
Proc. SPIE 8753, Wireless Sensing, Localization, and Processing VIII, 87530I (28 May 2013); doi: 10.1117/12.2018148
Published in SPIE Proceedings Vol. 8753:
Wireless Sensing, Localization, and Processing VIII
Sohail A. Dianat; Michael David Zoltowski, Editor(s)
PDF: 10 pages
Proc. SPIE 8753, Wireless Sensing, Localization, and Processing VIII, 87530I (28 May 2013); doi: 10.1117/12.2018148
Show Author Affiliations
Moeness G. Amin, Villanova Univ. (United States)
Braham Himed, Air Force Research Lab. (United States)
Braham Himed, Air Force Research Lab. (United States)
Published in SPIE Proceedings Vol. 8753:
Wireless Sensing, Localization, and Processing VIII
Sohail A. Dianat; Michael David Zoltowski, Editor(s)
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