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改进小波变换的船舶射频信号降噪和识别
Noise reduction and recognition of ship radio frequency signal based on improved wavelet transform
- DOI:
- 作者:
- 周慧, 魏霖静, 李玥
ZHOU Hui, WEI Lin-jing, LI Yue
- 作者单位:
- 甘肃农业大学 信息科学技术学院, 甘肃 兰州 730070
College of Information Science and Technology, Gansu Agricultural University, Lanzhou 730070, China
- 关键词:
- 改进小波变换;神经网络;信号噪声降噪
improved wavelet transform; neural network; noise removal
- 摘要:
- 针对船舶射频信号受通信环境因素及硬件多源噪声的广泛复合因素影响而包含多种频段的噪声，在实时检测中造成有效信号检测率低、误差大的问题，本文设计一种船舶射频信号噪声降噪和识别的软硬件结合的仿真系统。将获取到的船舶射频信号经A/D转换电路转换后，在小波抑制模块分解得到小波系数，并采用改进阈值小波滤波后重构信号，送入信号识别模块利用概率神经网络进行识别。实验结果表明：本文提出的降噪识别方法能够有效地降低信噪比，提升船舶射频信号的识别率，可以应用到实际的船舶射频信号的检测系统中。
Aiming at the problem of low effective signal detection rate and large error in real-time detection due to the influence of communication environment factors and hardware multi-source noise, a simulation system combining software and hardware for noise reduction and recognition of ship radio frequency signal is designed in this paper. After the acquired ship RF signal is converted by A/D conversion circuit, the wavelet coefficients are decomposed in the wavelet suppression module, and the signal is reconstructed after the improved threshold wavelet filtering, and then sent to the signal recognition module for recognition using probabilistic neural network. The experimental results show that the noise reduction identification method proposed in this paper can effectively reduce the signal-to-noise ratio, improve the recognition rate of ship RF signals, and can be applied to the actual ship RF signal detection system.
2023,45(6): 162-165 收稿日期：2022-10-13
DOI：10.3404/j.issn.1672-7649.2023.06.031
分类号：TN911.T3
基金项目：兰州市人才创新创业项目（2021-RC-47）；教育部产学研项目（202102326021）；教育部产学研项目（202102326023）
作者简介：周慧(1982-)，女，硕士，讲师，研究方向为信号与信息处理
