Abstract
We consider an antenna placement optimization problem for distributed multi-input multi-output (MIMO) radar systems in this paper. We aim to enhance the system surveillance and localization performance in different subareas by optimizing antenna positions, with metrics being formulated to evaluate the surveillance and localization performance of distributed MIMO radar systems. However, the proposed optimization problem is high-dimensional, nonlinear, and especially multi-objective due to two objective functions conflicting with each other. To solve this problem, we further propose an enhanced multi-objective particle swarm optimization (MOPSO) algorithm, which differs from the traditional MOPSO in that its particle can properly consider the differences between the elements within the particle. Finally, simulation results are provided to verify the effectiveness of the proposed algorithm.
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