不确定海洋环境中基于主成分量的稳健检测器

发布时间：2018-03-19 15:15

本文选题：主成分　切入点：海洋环境　出处：《声学学报》2014年03期 　论文类型：期刊论文

【摘要】：传统的信号检测算法在不确定的海洋环境中性能出现下降。基于贝叶斯原理的最优检测算法可以实现对不确定海洋环境中信号的有效检测,但是其突出问题是计算量较大。本文提出了一种基于主成分量分析的稳健信号检测器,该检测器利用贝叶斯原理将环境先验信息引入到检测算法中,同时使用主成分量分析方法来降低运算量,实现了对信号的快速有效检测。分别使用标准失配海洋模型和海上实测数据进行了计算机仿真和实验验证,结果表明:(1)基于主成分量的稳健信号检测器检测性能达到最优贝叶斯检测器的效果。(2)本文方法在线运算速度是贝叶斯最优检测器的5~8倍。(3)环境先验信息失配的情况下,扩大海洋环境参数模型的不确定度范围有助于提高检测性能。
[Abstract]:The performance of traditional signal detection algorithm in uncertain marine environment is degraded, and the optimal detection algorithm based on Bayesian principle can effectively detect signals in uncertain marine environment. In this paper, a robust signal detector based on principal component analysis (PCA) is proposed, which uses Bayesian principle to introduce environmental prior information into the detection algorithm. At the same time, the principal component analysis method is used to reduce the computation cost and to realize the fast and effective detection of the signal. The computer simulation and experimental verification are carried out using the standard mismatched ocean model and the measured data at sea, respectively. The results show that: 1) the detection performance of robust signal detector based on principal component quantity reaches the effect of optimal Bayesian detector. Expanding the uncertainty range of the model is helpful to improve the detection performance.
【作者单位】：西北工业大学声学工程研究所;中国电子科技集团公司第十四研究所;
【基金】：国家自然科学基金(11274252)资助
【分类号】：TN911.23

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