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中文摘要：
提出了一种基于多目标遗传算法的星载天线干扰抑制算法，该算法在射频端通过调节权系数进行输出功率判决从而实现波束形成。文中引入多目标优化问题Pareto最优解的概念，采用了无支配性排序遗传算法（NSGA-Ⅱ）来搜索干扰调零权值的Pareto最优解集，充分发挥这种先进多目标遗传算法的高内在并行性、强鲁棒性以及能够不断优化最优解集的优势，较好地兼顾了星载天线干扰抑制时干扰抑制深度与主波束保形这一对矛盾问题。最后提出了归一化双目标函数加权选择最优调零权的方法从Pareto最优解集中选择一组符合决策者偏好的最优调零权。计算机仿真实验证明，文中所提出的算法具有较好的干扰抑制能力和主波束保形效果。
英文摘要：
In this paper, a novel space-borne antenna nulling method based on multi-objective genetic algorithm is presented for rejecting strong jamming. The presented beamforming algorithm is a feedback method judged by power. The paper introduces the concept of Pareto optimum front and adopts the non-dominated sorting genetic algorithm（NSGA-Ⅱ） to search the Pareto optimum front of the nulling weights. NSGA-Ⅱ has high inner parallel ability, strong robustness and the advantage of unceasingly optimizing the set of optimum solutions. All advantages of the advanced multi-objective GA are taken to solve the problems of both nulling depth and main-lobe shape keeping. At last, to select the best weights catering to the decision maker＇s need from the Pareto optimization front, a method of selecting the optimum anti-jamming weights by weighting two unitary objective functions is presented. Simulation results and performance analysis proves that the algorithm is effective and efficient in rejecting strong jamming and keeping main-lobe shape simultaneously.
同期刊论文项目
同项目期刊论文
Multitarget identification and localization using bistatic MIMO radar systems (vol 2008, art no 2834
Joint frequency ambiguity resolution and accurate timing estimation in OFDM systems with multipath f
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