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Adaptive-beamforming-based multiple targets signal separation

机译:基于自适应波束形成的多目标信号分离

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摘要

In practical array signal processing systems, how to separate the required target signal from the received mixed signals effectively is an important research work. Firstly, for the conventional diagonal loading approaches, it is difficult to choose the DL level reliably. To solve this problem, by using the shrinkage method we present a General-Linear-Combination-Based robust adaptive beamformer (GLC) in this paper. Secondly, different from the traditional time-domain and frequency-domain separation methods, we innovatively apply the adaptive beamforming technique into the research of multiple targets signal separation in this paper, and give the specifications quantitatively to measure the separation effects: spatial separation angle and similarity coefficient. Simulation results show that compared with traditional methods, the GLC-based method has smaller spatial separation angle and greater similarity coefficient, which could separate the required target signal more accurately.
机译:在实际的阵列信号处理系统中,如何有效地从接收到的混合信号中分离出所需的目标信号是一项重要的研究工作。首先,对于常规的对角加载方法,难以可靠地选择DL电平。为了解决这个问题,通过使用收缩方法,我们在本文中提出了一种基于通用线性组合的鲁棒自适应波束形成器(GLC)。其次,与传统的时域和频域分离方法不同,本文将自适应波束形成技术创新地应用于多目标信号分离的研究中,并定量给出了测量分离效果的指标:空间分​​离角和相似系数。仿真结果表明,与传统方法相比,基于GLC的方法具有较小的空间分离角和较大的相似系数,可以更准确地分离出所需的目标信号。

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