基于半正定约束的最差性能最优通用信号模型顽健波束成形算法OA北大核心CSCDCSTPCD
Robust beamforming based on the worst-case performance optimization with positive semi-definite constraints
针对通用信号模型下的顽健波束形成问题，提出了一种基于半正定约束的最差性能最优顽健自适应波束成形算法，通过对波束成形器进行建模和变换，得到了一种简单的顽健自适应波束成形器的表达式。对波束成形器进行求解，不仅得到了最优权矢量的近似闭式解，而且获得了一定的性能改善，并且该算法具有较低的计算复杂度。仿真结果表明了该算法的有效性和正确性。
For the robust adaptive beamforming problem of the general signal models, a robust beamforming algorithm based on the worst-case performance optimization with positive semi-definite constraints was proposed. A simple robust adaptive beamformer was derived by modeling and transforming. Not only an approximate closed-form solution to the optimal weight vector was derived with low complexity, but also the performance improvement could be obtained. The final s…查看全部>>
徐定杰;贺瑞;沈锋
哈尔滨工程大学 自动化学院，黑龙江 哈尔滨 150001哈尔滨工程大学 自动化学院，黑龙江 哈尔滨 150001哈尔滨工程大学 自动化学院，黑龙江 哈尔滨 150001
信息技术与安全科学
自适应波束成形最差性能最优通用信号模型半正定约束
adaptive beamformingworst-case performance optimizationgeneral signal modelspositive semi-definite constraints
《通信学报》 2013 (3)
混合Alpha稳定分布非高斯噪声模型及基于变分贝叶斯学习的参数估计方法
1-5,5
国家自然科学基金资助项目(61102107)
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