光电工程, 2020, 47 (6): 190137, 网络出版: 2020-10-27  

基于MEEMD与FLP的光纤陀螺去噪

De-noising algorithm for FOG based on MEEMD and FLP algorithm
作者单位
1 海军航空大学, 山东 烟台 264000
2 海军92728部队, 上海 200040
3 海军92214部队, 浙江宁波 315000
摘要
为了降低噪声对光纤陀螺输出的影响, 提出了一种基于改进经验模态分解 (MEEMD)和前向线性预测 (FLP)结合的光纤陀螺去噪算法。首先, 引入排列熵概念, 利用改进经验模态分解对光纤陀螺信号进行分解与重构; 然后针对分解后混合噪声的低阶 IMF项, 通过 FLP算法进行滤波去噪; 最后将经过 MEEMD-FLP处理后的信号进行重构以得到结果。对某干涉型 FOG进行静态测试, 通过实测数据计算结果表明: 与原始 FOG信号相比, 降噪后的 RMSE降低了 76.77%, 标准差降低了 76.76%。该算法可有效降低噪声对 FOG输出信号的影响, 具有更高的去噪精度。
Abstract
In order to reduce the influence of noise on the output signal of FOG, a de-noising algorithm of FOG based on modified ensemble empirical mode decomposition (MEEMD) and forward linear prediction (FLP) is proposed. Firstly, the concept of permutation entropy is introduced, and the FOG signal is decomposed and reconstructed by using MEEMD. Secondly, the low-order IMF terms of the mixed noise after decomposition is filtered and de-noised by the FLP algorithm. Finally, the signal processed by the MEEMD-FLP is reconstructed to get the result. The static test of a FOG is carried out. The experimental results show that compared with the original FOG signal, the RMSE after de-noising is reduced by 76.77%, and the standard deviation is reduced by 76.76%. It can effectively reduce the influence of noise on the FOG output signal and has higher de-noising accuracy.

戴邵武, 陈强强, 刘志豪, 戴洪德. 基于MEEMD与FLP的光纤陀螺去噪[J]. 光电工程, 2020, 47(6): 190137. Dai Shaowu, Chen Qiangqiang, Liu Zhihao, Dai Hongde. De-noising algorithm for FOG based on MEEMD and FLP algorithm[J]. Opto-Electronic Engineering, 2020, 47(6): 190137.

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