摘要
This paper proposes a novel task-driven flexible array beampattern synthesis model for self-organized drone swarms according to their task requirements so that they can adjust their positions appropriately and point in a specific direction. First, we formulate the novel beampattern synthesis model using the drone-swarm antenna position and weight vector as the optimization variables and the maximum driving distance as the constraint. Then, the Lawson criterion is used to simplify the objective function, and the two kinds of optimization variables of antenna position and weight vector are reduced to a single kind of variable optimization problem of antenna position, alleviating the optimization difficulty caused by the usage of coupled variables. Simultaneously, auxiliary variables are introduced to separate the constraints from the complex objective function, and the Alternating Direction Method of Multipliers (ADMM)is used to slove the problem, which reduces the difficulty of solving a highly nonlinear optimization problem with constraints,. In addition, we extend this method to a scenario in which the provided Direction Of Arrival (DOA)of interest is imprecise. Simulation results show that the proposed method can obtain lower sidelobe levels than previous methods.
投稿的翻译标题 | Task-driven Flexible Array Beampattern Synthesis for Self-organized Drone Swarm |
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源语言 | 繁体中文 |
页(从-至) | 517-529 |
页数 | 13 |
期刊 | Journal of Radars |
卷 | 11 |
期 | 4 |
DOI | |
出版状态 | 已出版 - 8月 2022 |
关键词
- Beampattern synthesis
- Flexible array
- Nonconvex optimization
- Radar signal processing
- Self-organized drone swarm