基于扭曲域压缩感知重构的多径色散构型飞行时间估计

A. Digulescu, I. Candel, C. Ioana
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引用次数: 0

摘要

本文提出了一种基于扭曲域压缩感知(CS)重构的宽带信号飞行时间估计方法。在实际情况下,与信号发送/接收相关的约束(如换能器配置或实验设置)会影响信号的信息内容。因此,在进行参数估计之前,需要对接收到的信号进行内容重构(一般基于匹配滤波)。在目前的研究中,我们有兴趣改善由于初始实验设置或操作条件下的振动而不完全对齐的两个换能器(发射器和接收器)之间的波TOF估计。由于接收信号的传播环境会有几个传播色散路径,因此收发换能器的失调会引入干扰。这种多径传播环境会导致干扰,进而导致部分采样损失。为了恢复丢失的样本,本文提出的信号重建方法首先对信号进行时间轴(翘曲)变换。时间轴变换的目的是将任意非线性调频信号在扭曲域中转化为平稳信号。在变换后的域中,利用CS概念恢复缺失的频谱分量。然后,解包裹函数可以将恢复的信号表示到原始时域中。我们证明了基于匹配滤波器的重构信号的声波TOF估计比使用原始接收信号更准确。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time of flight estimation in multi-path dispersive configuration using compressive sensing reconstruction in the warped domain
In this paper, we present a new approach of time of flight (TOF) estimation using wide band signals, based on compressive sensing (CS) reconstruction in warped domain. In real conditions, constraints related to signal's transmitting/receiving (such as the transducers configuration or the experimental setup) can affect the informational content of the signal. Thus, the received signals need content reconstruction before the parameters estimation (generally based on matched filtering). In the current study, we are interested to improve such waves TOF estimation between two transducers (a transmitter and a receiver) that are not perfectly aligned, due either to the initial experimental setup or to the vibrations in operational conditions. The misalignments of transmitter-receiver transducers introduce interferences since the propagation environment will have several propagation dispersive paths in terms of the received signals. This multipath propagation environment will conduct to interferences and, then, to the partial samples loss. In order to recover the missing samples, the proposed signal reconstruction method uses firstly a time axis (warping) transformation of the signal. The aim of time axis transformation is to turn any non-linear frequency modulation into a stationary signal in the warped domain. In this transformed domain, the CS concept is used to recover the missing spectral components. Then, an unwrapping function enables to express the recovered signal into the original time domain. We prove that the matched filter-based acoustic wave TOF estimation from the reconstructed signal is more accurate than using the original received signal.
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