高斯-指数混合噪声中的弱信号检测及其渐近相对效率

Keman Liu, Xiushan Liu, Jinglin Xiang
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引用次数: 0

摘要

传统的水下目标信号检测器是基于高斯模型的。根据最近的研究,该模型与实际的海洋环境噪声不一致,基于该模型的最优检测器存在意想不到的性能差的风险。通过对水下噪声样本的分析,提出了一种描述接收噪声的高斯-指数混合模型,从而推导出最优的信号检测器。我们首先将海洋环境噪声模型重建为高斯-指数混合模型。接下来,我们推导出在这种噪声中已知信号的最优非线性检测器结构。最后,为了评价最优检测器的性能,将其与传统的能量检测器进行了比较。比较是基于比较假设检验程序的渐近相对效率(ARE)的概念。仿真结果表明,该探测器的性能比传统的能量探测器高4 ~ 8dB。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Weak signal detection and asymptotic relative efficiency in Gaussian-Exponential mixture noise
Traditional signal detectors for underwater targets are based on Gaussian model. Such model, according to recent research, does not agree with actual ocean ambient noise, and the optimal detector based on this model risks unexpectedly poor performance. We present a Gaussian- Exponential mixture model to describe the received noise by analysis of underwater noise samples for deriving an optimal signal detector. We first rebuild the ocean ambient noise model as a Gaussian-Exponential mixture model. Next, we derive an optimal nonlinear detector structure for known signals in such noise. Finally, in order to evaluate the performance of the optimal detector, it is compared to the conventional energy detector. The comparison is based on the concept of asymptotic relative efficiency (ARE) for comparing hypothesis testing procedures. The simulation results show that the performance of the proposed detector is better than that of the conventional energy detector by 4∼8dB.
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