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Ultrawideband Direction-of-Arrival Estimation Using Complex-Valued Spatiotemporal Neural Networks

机译:使用复值时空神经网络的超宽带到达方向估计

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摘要

We propose a direction of arrival (DoA) estimation method using a complex-valued neural network (CVNN) for ultrawideband (UWB) systems. We combine a complex-valued spatiotemporal neural network with power-inversion adaptive-array scheme for null-steering DoA estimation. Simulation and experiments demonstrate that the proposed method shows an estimation accuracy higher than that of conventional multiple signal classification method and a spectrum floor lower than that of real-valued neural network. These results suggest that the CVNN deals with signals more properly as wave information in the null synthesis in UWB systems.
机译:我们为超宽带(UWB)系统提出了一种使用复值神经网络(CVNN)的到达方向(DoA)估计方法。我们将复数值时空神经网络与幂反转自适应阵列方案相结合,以进行空转向DoA估计。仿真和实验表明,该方法的估计精度高于传统的多信号分类方法,频谱底限低于实值神经网络。这些结果表明,在超宽带系统的空综合中,CVNN作为波信息可以更正确地处理信号。

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