An EMD threshold de-noising method for inertial sensors

作者：Gan Yu^*; Sui Lifen; Wu Jiangfei; Wang Bing; Zhang Qinghua; Xiao Guorui

来源：Measurement, 2014, 49: 34-41.

DOI：10.1016/j.measurement.2013.11.030

• Inertial sensors
• Empirical Mode Decomposition (EMD)
• Colored noise
• Threshold de-noising
• Fractional Gaussian noise

Random errors of inertial sensors are key factors in influencing the performance of Inertial Navigation System (INS). Based on underlying white noise model, classical wavelet threshold de-noising method is incapable of eliminating colored noise. Since time-correlated colored noise is predominant, fractional Gaussian noise (fGn) is utilized to model sensor errors and the Hurst parameter of fGn is estimated by the periodogram method. Variances of the noise in Intrinsic Mode Functions (IMFs) decomposed by Empirical Mode Decomposition (EMD) are analyzed. The standard deviations of noise in the first tow IMFs are estimated by a robust estimator, and then the noise variances in other IMFs can be obtained after the variance relation among the IMFs decomposed from fGn is derived. Noise thresholds of IMFs are estimated through the obtained variances and an EMD threshold de-noising method using order-dependent thresholds is established. The method is firstly verified by a simulation example and then applied in INS and compared with wavelet de-noising method. Results show that wavelet threshold de-noising is poor at suppressing colored noise while EMD threshold de-noising is effective on reducing sensor errors due to its close association with proper noise model.

• 出版日期2014-3
• 单位中国人民解放军信息工程大学