结合卡尔曼滤波和自适应FxNLMS的水声降噪方案

Md. Mostafizur Rahman, Sumonto Sarker
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引用次数: 0

摘要

水下环境比陆地环境更具挑战性。控制器或增强系统的整体性能取决于实际测量数据,因此数据读数中的噪声可能是致命的。为了有效地自适应控制低频和高频噪声,提出了主动噪声消除技术。设计一种改进的FxLMS系统和参数来降低噪声和传感器数据的干扰是本文的重点。所需要的方程将被简单地分析和讨论。在MATLAB中对该系统进行仿真,并对滤波结果进行分析。根据仿真结果,所提出的模型可以滤除带有噪声的信号,特别是当数据中存在显著变化且不知道可能影响传感器读数的噪声频率时。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Underwater Acoustic Noise Cancellation Scheme Combining Kalman Filter With Adaptive FxNLMS
Underwater environments are more challenging than that of terrestrial. The performance of a controller or the augmented system as a whole depends on the real measured data, so noise on data readings can be fatal. To effectively and adaptively control lower and higher frequency noise, the Active Noise Cancellation (ANC) was developed. Designing a system and the parameter of modified FxLMS for reducing noise, and disturbance of sensor data is the primary focus of this paper. The required equation will be analyzed and discussed briefly. Moreover, the system will be simulated in MATLAB and then the filtered result will be analyzed. Based on the simulation results, the proposed model can filter out signals with noise, particularly when there is a significant variation in the data and no knowledge of the noise frequency that might affect sensor readings.
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