在沿海环境中，低频大功率高分辨主动声呐产生较高的虚警。高虚警不仅增加了声呐员的工作量，而且降低了自动反潜系统（如无人反潜平台）的应用场景。随着主动声呐日益增加自主探测技术的需求，以及人工智能不断的市场化成功应用，特征分类降低主动声呐虚警率的方法受到越来越多关注。本文通过特征分类的方法二分类样本数据为目标与杂波，在一定主动声呐检测性能的基础上，降低其虚警概率。
It is well to known that low frequency and high power active sonar has high false alarm rate in the coast. High false alarm rate not only improves the sonar operator workload, but also reduce the use of automatic anti-submarine systems (such as unmanned anti-submarine platform). With the increasing demand for autonomous detection technology of active sonar and the continuous successful application of artificial intelligence in market, the method of feature classification to reduce the false alarm rate of active sonar has attracted more and more researchers' interest and attention. In this paper,the feature classification method is used to classify the sample data as target and clutter, and on the basis of certain active sonar detection performance, the false alarm probability is reduced.
2022,44(2): 156-160 收稿日期：2021-05-06
DOI：10.3404/j.issn.1672-7649.2022.02.028
分类号：TB56
作者简介：冯金鹿(1987-)，男，工程师，研究方向为主动声呐信号及信息处理
参考文献：
[1] HJELMERVIK K T, BERG H, SEKSE D H, et al. A hybrid recorded-synthetic sonar data set for validation of ASW classification algorithms[J]. Oceans, 2015: 1–5
[2] BUß M, BENEN S, STILLER D, et al. Feature selection and classification for false alarm reduction on active diver detection sonar data[C]//4th International Conference on Underwater Acoustics, 2017, 9.
[3] HJELMERVIK K T, BERG H. Automatic target classification for low-frequency anti-submarine warfare sonars[J]. Oceans, 2013: 1–3
[4] BERG H, HJELMERVIK K T, SEKSE D H, et al. A comparison of different machine learning algorithms for automatic classification of sonar targets[C]//Oceans 2016 MTS/IEEE Monterey, 2016, 9: 746−753.
[5] COLIN M E G D, BEERENS S P. False-alarm reduction for low-frequency active sonar with BPSK pulse: experimental results[J]. IEEE Journal of Oceanic Engineering, 2011, 36(1): 52–59
[6] AURÉLIEN GÉRON. 机器学习实战: 基于Scikit-Learn和Tensorflow[M]. 北京: 机械工业出版社, 2018.
[7] 周志华. 机器学习[M]. 北京: 清华大学出版社, 2016.
[8] 李航. 统计学习方法[M]. 北京: 清华大学出版社, 2012.
