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刘增宏 , 吴晓芬 , 许建平 , 等 . 中国Argo海洋观测十五年 [J ] . 地球科学进展 , 2016 , 31 ( 5 ): 445 - 460 . DOI: 10.11867/j.issn.1001-8166.2016.05.0445. http://doi.org/10.11867/j.issn.1001-8166.2016.05.0445. 中国Argo计划组织实施15年以来,在太平洋和印度洋等海域布放了350多个剖面浮标,建成了我国Argo大洋观测网,并建立了针对Argo剖面浮标的资料接收、处理和分发系统,利用Argo资料开发了多个数据产品,在一定程度上推动了国内海洋数据的共享进程。海量的Argo资料已成为我国海洋和大气科学领域基础研究及业务化应用的主要数据源,特别是在热带气旋(台风)、海洋环流、中尺度涡、湍流、海水热盐储量与输送、大洋水团以及海洋、天气/气候业务化预测预报等方面取得了一批重要的研究和应用成果。随着国际Argo计划由“核心Argo”向“全球Argo”拓展,我国Argo大洋观测网的长期维护和持续发展面临巨大挑战,应紧紧抓住这一难得的机遇,利用国产北斗剖面浮标在南海及邻近我国的西北太平洋和印度洋海域建成Argo区域海洋观测网,为应对全球气候变化及防御自然灾害,更多地承担一个海洋大国的责任和义务。

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赵文春 , 姜润翔 , 喻鹏 , 等 . 基于轴频电场线谱特征的目标检测及识别 [J ] . 兵工学报 , 2020 , 41 ( 6 ): 1165 - 1171 . DOI: 10.3969/j.issn.1000-1093.2020.06.013 http://doi.org/10.3969/j.issn.1000-1093.2020.06.013 为有效地从海洋环境电场信号中检测出舰船轴频电场信号，在对大量实测数据分析的基础上，提出一种基于轴频电场线谱特征的目标检测与识别方法。对接收信号进行傅里叶变换计算频谱图，并对其进行归一化处理以提高其动态范围；采用浮动门限与固定门限相结合的方法对疑似线谱信号进行检测；采用积分累计的方法对疑似线谱特征进行目标确认，并利用长时间积分特征均值实现对目标信号的识别；通过海上实测数据对方法的有效性进行检验。结果表明，该方法能够有效检测到目标信号，并可实现对目标信号的识别分类。

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喻鹏 , 程锦房 , 张伽伟 , 等 . 基于Rao检测器的舰船轴频电场滑动门限检测方法 [J ] . 兵工学报 , 2021 , 42 ( 4 ): 827 - 834 . DOI: 10.3969/j.issn.1000-1093.2021.04.016 http://doi.org/10.3969/j.issn.1000-1093.2021.04.016 为实现非高斯背景噪声和低信噪比情况下的舰船轴频电场检测，提出一种基于Rao检测器的滑动门限检测方法。基于信号源特征建立信号模型，在对水面浮动平台测量背景下环境噪声非高斯特性分析基础上，采用混合高斯模型对噪声进行建模；在检测过程中，实时估计混合高斯噪声模型参数和Rao检测统计量，并将前一段时间的平均Rao检测统计量作为门限，实现滑动门限检测。为验证所提方法的有效性，采用仿真计算的方式，证明Rao检测方法相比于能量检测方法的优势；根据实测数据，对比滑动门限Rao检测方法与滑动功率谱检测方法的性能差异。结果表明，滑动门限Rao检测方法能够有效抑制环境非高斯噪声影响，相比滑动功率谱检测方法具有更好的检测效果。

YU P , CHENG J F , ZHANG J W , et al. Ship shaft-rate electric field sliding threshold detection method based on Rao detector [J ] . Acta Armamentarii , 2021 , 42 ( 4 ): 827 - 834 . (in Chinese) DOI: 10.3969/j.issn.1000-1093.2021.04.016 http://doi.org/10.3969/j.issn.1000-1093.2021.04.016 A sliding threshold detection method based on Rao detector is proposed to detect the ship's shaft-rate electric field at a low SNR in non-Gaussian noise environment. A signal model is established based on the characteristics of signal source, and a noise model is established based on Gaussian mixture model (GMM) after analyzing its non-Gaussian characteristics measured by a floating platform. In the detection process, the parameters of GMM and the Rao detection value are computed in real time; the mean value of previous Rao detection values is regarded as the sliding threshold. The simulation method is first used to verify the proposed method. The results show that the detection performance of Rao detector is better than that of energy detector. Then the measured ship data is used to compare the Rao sliding threshold method and the sliding power spectrum method. The results show that the proposed method is better in decreasing the non-Gaussian environment noise and has a better detection performance than the sliding power spectrum method.

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