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作 者:贾凤勤 赵颖颖 JIA Fengqin;ZHAO Yingying(Zhengzhou University of Industrial Technology,Zhengzhou 451100,China)
出 处:《电声技术》2024年第8期35-37,共3页Audio Engineering
摘 要:研究一种基于卡尔曼滤波优化的自适应滤波方法,以提高水声信号的降噪性能。首先,探讨基于最小均方误差的自适应滤波方法。其次,引入卡尔曼滤波进一步优化滤波效果。最后,在MATLAB平台上使用DeepShip数据集进行方法测试。实验结果表明,所提方法在不同类型船舶信号的降噪处理上均显著优于传统方法,信噪比平均提升5.2 dB,验证了方法的有效性和优越性。This article studies an adaptive filtering method based on Kalman filter optimization to improve the denoising performance of underwater acoustic signals.Firstly,an adaptive filtering method based on minimum mean square error was explored.Then,Kalman filtering is introduced to further optimize the filtering effect.Finally,this experiment was conducted on the MATLAB platform using the DeepShip dataset for method testing.The experimental results show that the method proposed in this paper is significantly superior to traditional methods in noise reduction of signals from different types of ships,with an average improvement of 5.2 dB in signal-to-noise ratio,verifying the effectiveness and superiority of this method.
分 类 号:TN929.3[电子电信—通信与信息系统]
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