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• W2912581924 abstract "To facilitate the ability of phased array radar to manage both its search and track (SAT) tasks simultaneously within a predetermined illumination time budget, a resource allocation (RA) scheme for integrated SAT application is built in this paper. We formulate the RA scheme as a bi-objective constrained optimization framework, and use Pareto's theory to determine its multiple Pareto optimal solutions. With these Pareto solutions, one can find a suitable tradeoff between SAT tasks, and correspondingly choose an illumination scheme, for an arbitrary application demand. By exploiting the unique structure of the bi-objective optimization problem, we strictly prove that the multiple Pareto solutions with cardinality M can be obtained by parallelly solving M + 1 convex minimax problems. These problems are shown to correlate with the SAT tasks independently, and are correspondingly solved by the well-known linear programming methods and a proposed minimax solving algorithm, respectively. Finally, some numerical results are provided to illustrate the effectiveness and reveal the intrinsic mechanism of the Pareto theory based bi-objective RA strategy." @default.
• W2912581924 created "2019-02-21" @default.
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• W2912581924 date "2019-04-01" @default.
• W2912581924 modified "2023-09-30" @default.
• W2912581924 title "Resource Allocation for Search and Track Application in Phased Array Radar Based on Pareto Bi-Objective Optimization" @default.
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• W2912581924 doi "https://doi.org/10.1109/tvt.2019.2894960" @default.
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