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Adaptive detection for unknown noise power spectral densities

机译:未知噪声功率谱密度的自适应检测

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摘要

The detection of a known broadband signal in colored noise of unknown power spectral density is addressed. Motivated by the consistency of the integrated periodogram, a new detector is proposed. Its asymptotic performance is proven to be only slightly poorer than the optimal but unrealizable Neyman-Pearson detector. It also possesses the CFAR property asymptotically and should therefore be quite valuable in practice. For finite data records, it is shown by computer simulation to significantly outperform the conventional matched filter (without prewhitening) under realistic conditions encountered in practice.
机译:解决了在未知功率谱密度的有色噪声中检测已知宽带信号的问题。基于积分周期图的一致性,提出了一种新的检测器。事实证明,其渐近性能仅比最佳但无法实现的Neyman-Pearson检测器稍差。它也具有渐近的CFAR属性,因此在实践中应该非常有价值。对于有限的数据记录,计算机模拟显示,在实际遇到的实际条件下,该性能明显优于传统的匹配滤波器(不进行预白化)。

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