基于PVDF的类蝙蝠声纳回波信号神经网络处理

A. Fiorillo, G. D'Angelo
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引用次数: 7

摘要

蝙蝠复杂的声纳系统能够提取一套完整的信息,以便定位和描述猎物。弯曲的压电聚合物换能器已经在相同的频率范围内用于在空气中产生超声波。在本文中,我们研究了利用神经网络处理回声信号的可能性,类似于生物模型。我们分析了调频信号,这只是最复杂的蝙蝠回波信号的一部分,以便通过飞行时间评估来测量目标距离。啁啾首先用低噪声CMOS放大器放大,然后进行适当的滤波和整流,以获得脉冲时间序列。最后,对脉冲信号进行一级神经网络处理,识别出正确的脉冲时间序列,计算出飞行时间。利用Matlab和Spice程序进行的仿真结果将为压电聚合物换能器的应用提供参考。
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Echo signals processing with neural network in bat-like sonars based on PVDF
The sophisticated sonar system of bats is capable of extracting a complete set of information in order to locate and characterize the prey. Curved piezopolymer transducers were already used in the same frequency range to generate ultrasonic waves in air. In this article we investigate the possibility to process echo-signals by using a neural network, similarly to the biological model. We analyse frequency modulated signals, which are only a part of the most complex bat echo signal, in order to measure the target distance through the time of flight evaluation. Chirps are first amplified with a low noise CMOS amplifier, than are properly filtered and rectified in order to obtain a pulse time sequence. Finally the pulse signal is processed by the first level of a neural network to recognize the right pulse time sequence and evaluate the time of flight. Simulated results carried out by using both Matlab and Spice programs, will be presented with reference to piezo-polymer transducers application.
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