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A method minimizing the correlation properties of a noise field and improving detection of signals embedded in anisotropic noise

机译:一种使噪声场的相关特性最小化并改善对各向异性噪声中嵌入信号的检测的方法

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摘要

This paper deals with the development of a processing technique that improves the signal-to-noise ratio (SNR) at the single sensor for a received signal that is embedded in a partially correlated noise field. The approach of this study is unique in that the noise is treated as being non-white and partially correlated. The concept of the proposed development is based on the time interval over which the temporal coherence or correlation properties of a noise field are defined. For narrowband signals, the associated temporal coherence period is much longer than the correlation time interval of the anisotropic noise field. Thus, a coherent integration of discontinuous segments of received signals will enhance the SNR at the single sensor by lowering the correlation properties of the associated non-white noise. Reconstruction of the narrow-band signal time series, with improved SNR at the sensor will allow the use of the existing high resolution techniques to be utilized more effectively by lowering their threshold values in order to detect very weak signals. The intention here is to integrate the characteristics of the real anisotropic noise field during the preliminary processing stages of the received signals by an array of sensors. Simulations show that the proposed method can be integrated in the signal processing functionality of sonar and radar systems.
机译:本文研究了一种处理技术的发展,该处理技术针对嵌入部分相关噪声场中的接收信号提高了单个传感器的信噪比(SNR)。这项研究的独特之处在于,噪声被视为非白色且部分相关。所提出的开发的概念基于时间间隔,在该时间间隔上定义了噪声场的时间相干性或相关性。对于窄带信号,相关的时间相干周期比各向异性噪声场的相关时间间隔长得多。因此,接收信号的不连续段的相干积分将通过降低相关的非白噪声的相关特性来增强单个传感器的SNR。重建窄带信号时间序列,并在传感器处改善SNR,将通过降低阈值来检测非常微弱的信号,从而更有效地利用现有的高分辨率技术。这里的意图是在传感器阵列的接收信号的初步处理阶段期间,整合真实各向异性噪声场的特性。仿真表明,该方法可以集成在声纳和雷达系统的信号处理功能中。

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