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引用次数: 3

摘要

被动估计两个(或多个)传感器处共同信号的到达时间差(TDOA)是信号处理中的一个基本问题,主要应用于发射器定位。TDOA估计的一种常用方法是使接收信号之间的样本互相关最大化。由于各种原因,这种相关性有时是通过频域计算的,在信号的离散傅立叶变换(DFT)之后——在这种情况下,线性相关性本质上被循环相关性所取代。尽管这两种计算方法的不同之处仅仅是一些相对较短的“边缘效应”,但这些边缘效应所带来的影响可能比它们相对(通常可以忽略不计)有效持续时间通常预测的要大。在这项工作中,我们分析了使用循环而不是线性相关导致的均方TDOA估计误差,表明对于某些信号,损失可能比通过简单的线性依赖于延迟值预测的损失更严重。
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Analysis of the edge-effects in frequency-domain TDOA estimation
Passive estimation of the Time-Difference of Arrival (TDOA) of a common signal at two (or more) sensors is a fundamental problem in signal processing, with applications mainly in emitter localization. A common approach to TDOA estimation is the maximization of the sample cross-correlation between the received signals. For various reasons, this correlation is sometimes computed via the frequency-domain, following a Discrete Fourier Transform (DFT) of the signals - in which case the linear correlation is essentially replaced with a cyclic correlation. Although the two computations differ merely by some relatively short “edge-effects”, these edge-effects can entail more impact than commonly predicted by their relative (usually negligible) effective durations. In this work we analyze the mean square TDOA estimation error resulting from the use of cyclic instead of linear correlations, showing that for some signals the loss can be more severe than what would be predicted by a simple linear dependence on the delay value.
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