| 不确定海洋环境中基于蒙特卡罗优化的稳健检测方法 |
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| 引用本文： | 刘宗伟,孙超,吕连港.不确定海洋环境中基于蒙特卡罗优化的稳健检测方法[J].声学学报,2015,40(5):665-674. |
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| 作者姓名： | 刘宗伟 孙超 吕连港 |
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| 作者单位： | 1 国家海洋局第一海洋研究所 青岛 266061; |
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| 基金项目： | 国家自然科学基金(11274252,51479169)、海洋哺乳动物发声×研究国家专项和东南大学水声信号处理教育部重点实验室开放研究基金(UASP1205)资助× |
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| 摘 要： | 常规的检测算法在实际不确定海洋环境中会遇到环境失配的问题,进而导致检测性能下降。本文结合贝叶斯原理和广义似然比方法,基于蒙特卡罗优化技术,提出了一种不确定海洋环境中信号检测方法。该检测器将环境先验信息应用到广义似然比检验中,在保证有效检测的基础上,降低了计算复杂度。同时给出了精确模型匹配检测器、最优贝叶斯信号检测器、平均模型匹配检测器和能量检测器作为对比的检测算法。计算机仿真和SWellEx-96海上实测数据处理结果表明,本文提出的信号检测器检测取得了优于平均模型匹配检测器和能量检测器的性能,其计算效率也有明显提高。
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| 收稿时间： | 2014-03-18 |
A robust signal detection method based on Monte Carlo optimization in uncertain ocean environment |
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| Affiliation: | 1 The First Institute of Oceanography, State Oceanic Administration Qingdao 266061;2 Institute of marine science and tecnolgy, Northwestern Polytechnical University Xi'an 710072;3 Key lab of marine science and numerical modeling, State Oceanic Administration Qingdao 266061 |
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| Abstract: | Existing detection methods will have mismatch problem when apply to the real uncertain ocean and this will lead to the performance degradation. Based on the Monte Carlo optimization this paper proposed a robust signal detector using the Bayesian theory and generalized likelihood ratio test (GLRT). The detector uses a priori knowledge of the environment in the GLRT to avoid the nonlinear optimization process. This guarantees the detection performance and reduces the computational complexity at the same time. Matched-ocean detector, mean-ocean detector and energy detector were also present as a comparison. Results from simulations and SWellEx-96 experiment data show that the proposed detector has leading performance over mean-ocean detector and energy detector. The computational consumption is also reduced. |
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