A Denoising Method for Fiber Optic Gyroscope Based on Variational Mode Decomposition and Beetle Swarm Antenna Search Algorithm

Abstract

Fiber optic gyroscope (FOG) is one of the important components of Inertial Navigation Systems (INS). In order to improve the accuracy of the INS, it is necessary to suppress the random error of the FOG signal. In this paper, a variational mode decomposition (VMD) denoising method based on beetle swarm antenna search (BSAS) algorithm is proposed to reduce the noise in FOG signal. Firstly, the BSAS algorithm is introduced in detail. Then, the permutation entropy of the band-limited intrinsic mode functions (BLIMFs) is taken as the optimization index, and two key parameters of VMD algorithm, including decomposition mode number K and quadratic penalty factor α , are optimized by using the BSAS algorithm. Next, a new method based on Hausdorff distance (HD) between the probability density function (PDF) of all BLIMFs and that of the original signal is proposed in this paper to determine the relevant modes. Finally, the selected BLIMF components are reconstructed to get the denoised signal. In addition, the simulation results show that the proposed scheme is better than the existing schemes in terms of noise reduction performance. Two experiments further demonstrate the priority of the proposed scheme in the FOG noise reduction compared with other schemes.

Temperature Drift Compensation of Fiber Optic Gyroscopes Based on an Improved Method

“…where a i is the Lagrange multiplier, and the Lagrangian function is used to derive the derivation w, b, ξ i , a i , respectively. The optimality condition of the KKT point is expressed in Equations ( 15)- (18).…”

“…The experimental results demonstrated that the novel method is superior to both the EMD-HRD and EMD-SFT approaches with a higher SNR ratio. Song et al [18,19] proposed a hybrid algorithm of an optimized local mean decomposition-kernel principal component analysis (OLMD-KPCA) method. The Allan variance analysis results indicated that the Q, N, and B reduced from 12.915 to 2.429 × 10 −1 , 1.8 × 10 −2 to 5.061 × 10 −4 , and 3.01 × 10 −1 to 1 × 10 −2 based on the X axis; from 7.680 to 1.38 × 10 −1 , 1.2 × 10 −2 to 2.647 × 10 −4 , and 1.72 × 10 −1 to 6 × 10 −3 based on the Y axis; and from 7.093 to 1.25 × 10 −1 , 1 × 10 −2 to Micromachines 2023, 14, 1712 3 of 18 1.549 × 10 −4 , and 1.53 × 10 −1 to 7 × 10 −3 based on the X axis, respectively.…”

Research on the recognition model of exercise fatigue based on the fusion of sEMG and ECG signals

“…proposed an improved VMD method based on the Beetle Antennae Search algorithm, where the kurtosis of intrinsic mode functions was used as the fitness function during the search process. 8 Gai et al. optimized VMD parameters using a hybrid Gray Wolf algorithm, significantly improving the optimization speed.…”

Hybrid Strategy Improved Beetle Antennae Search Algorithm and Application

“…Recently, intelligent optimization algorithms, as a new evolutionary computational tool, have been widely used in engineering optimization problems [2][3][4]. As one of the heuristic search algorithms, the Beetle Antennae Search (BAS) algorithm enjoys the advantages of fast convergence, simple model, low computational complexity, and robust searching ability [5,6], and is widely employed in several engineering optimization problems with high research value [7][8][9][10].…”