Underwater Parallel Bistable Stochastic Resonance Network: A Physical Layer Perspective

Wei Li, Hanzhi Lu, Y. Zuo
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Abstract

Underwater acoustic signals can suffer performance loss at low signal-to-noise ratios (SNR). An array is usually used to enhance processing performance. However, some of the underwater sensors may be floating. In such cases, inaccurate phase calibration can lead conventional array processing to fail. In this paper, we design an underwater bistable network. Bistable systems have the Stochastic Resonance(SR) property, and a bistable network can enhance the SR property, which can improve system performance in low SNR. And in such systems we do not need to calibrate the phase. We give the output SNR in theory and simulation to show its performance. Illustrative results show the performance of the proposed bistable network.
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水下平行双稳随机共振网络:物理层视角
在低信噪比(SNR)条件下,水声信号会遭受性能损失。数组通常用于增强处理性能。然而,一些水下传感器可能是漂浮的。在这种情况下,不准确的相位校准可能导致传统的阵列处理失败。本文设计了一种水下双稳网络。双稳系统具有随机共振特性,双稳网络可以增强系统的随机共振特性,从而提高系统在低信噪比下的性能。在这样的系统中,我们不需要校准相位。通过理论和仿真给出了输出信噪比。示例结果表明了所提出的双稳态网络的性能。
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