基于冗余第二代小波变换的光纤陀螺实时降噪算法研究

Research on Real-Time Denoising Algorithm for Fiber Optic Gyroscope Based on Redundant Second-Generation Wavelet Transform

摘要:

提出了一种基于冗余第二代小波变换的光纤陀螺实时降噪算法,该算法直接利用插值补零后的预测器和更新器对信号进行分解和重构,确保逼近信号和细节信号的长度与原始信号相同,避免重构后信号失真。模拟信号和光纤陀螺输出信号的仿真实验结果表明,该算法能够较好地保留信号的时域特征,保证信号的完整性和准确性,不受降噪过程的影响,同时量化噪声降低了约50.23%,角度随机游走降低了约19.14%,零偏不稳定性降低了约53.02%,为光纤陀螺信号处理提供了一种有效的方法。

Abstract:

This paper proposes a real-time denoising algorithm for fiber optic gyroscopes based on redundant second-generation wavelet transforms. The algorithm directly utilizes predictors and updaters with zero-padding interpolation to decompose and reconstruct signals. This approach ensures that the lengths of the approximation and detail signals are the same as that of the original signal, thus preventing signal distortion after reconstruction. The results of experiments on both simulated and actual output signals from fiber optic gyroscopes demonstrated that the algorithm effectively preserved the temporal characteristics of the signals, ensuring that their integrity and accuracy were not compromised by the denoising process. Moreover, it decreased the quantization noise by approximately 50.23%, decreased angular random walking by approximately 19.14%, and mitigated bias instability by approximately 53.02%. Thus, it provides an effective method for signal processing in fiber optic gyroscopes.