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首页> 外文期刊>Journal of VLSI signal processing systems >Improved Direction-of-Arrival Estimation Using Wavelet Based Denoising Techniques
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Improved Direction-of-Arrival Estimation Using Wavelet Based Denoising Techniques

机译:基于小波降噪技术的改进航向估计

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In this paper, we explore the use of wavelet based denoising techniques to improve the Direction-of-Arrival (DOA) estimation performance of array processors at low SNR. Traditional single sensor wavelet denoising techniques are not suitable for this application since they fail to preserve the intersensor signal correlation. We propose two correlation preserving techniques for denoising multi-sensor signals: (1) the Temporal Wavelet Array Denoising (TWAD) technique developed by Rao and Jones [IEEE Trans. Signal Processing, vol. 48, pp. 1225-1234, 2000], and (2) a new Spatial Wavelet Array Denoising (SWAD) technique. It is shown that SWAD offers the advantage of a significant reduction in computational complexity at the cost of a slight reduction in SNR gain. The denoised array data is used for DOA estimation by the MUSIC algorithm. Simulation results are presented for MUSIC (without denoising), TWAD-MUSIC, and SWAD-MUSIC, to illustrate the improvement in DOA estimation performance brought about by denoising.
机译:在本文中,我们探索使用基于小波的降噪技术来改善低SNR时阵列处理器的到达方向(DOA)估计性能。传统的单传感器小波去噪技术不适用于此应用,因为它们无法保留传感器间信号的相关性。我们提出了两种用于对多传感器信号进行降噪的相关性保留技术:(1)Rao和Jones [IEEE Trans。信号处理,第一卷48,第1225-1234页,2000],以及(2)一种新的空间小波阵列去噪(SWAD)技术。结果表明,SWAD具有显着降低计算复杂度的优势,但以略微降低SNR增益为代价。经去噪的阵列数据通过MUSIC算法用于DOA估计。给出了MUSIC(无降噪),TWAD-MUSIC和SWAD-MUSIC的仿真结果,以说明降噪带来的DOA估计性能的提高。

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