Science Alert
Journal of Applied Sciences
  Year: 2010 | Volume: 10 | Issue: 19 | Page No.: 2217-2230
DOI: 10.3923/jas.2010.2217.2230
Wavelet-based Pre-filtering for Low Cost Inertial Sensors
A.M. Hasan, K. Samsudin, A.R. Ramli and R.S. Azmir

This study proposed to de-noise the IMU signal by effectively band-limiting the signal at the output of each inertial measurement sensor prior to its mechanization and further processing by the Strapdown INS (SDINS) algorithm. Wavelet Multi-Resolution Algorithm (WMRA) is utilized to improve the performance of the inertial sensors by removing their short term noise. The aim of this study is to reveal how WMRA is utilized to improve the performance of the inertial measurement unit systems and investigate how wavelet analysis can be used to analyse and de-noise output of the low-cost inertial sensors. The proposed multi-level decomposition was applied to real accelerometer and gyroscopes data obtained from MEMS IMU (MotionPak II). Different level of decomposition and thresholding filter was evaluated to obtain optimal results. Analysis of the results demonstrate reducing the INS position and velocity error for the specific IMU.
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04 February, 2014
Xavier Piao:
This article seems very intuitive to understand the main points. Thank you for your effort. But I am poor in this area... so actually to implement this Wavelet Denoising in real time system like MEMS IMU processing, I should know its real-time scheme and should know how long delay from it according to its decomposition level. Output delay seems somewhat long if this denoising is proceeded I think. In a word, could you kindly let me know what is the real-time implementing algorithm step by step? Or any detailed literature for it in IMU sensor output processing. I am so eager to hear from you. Thank you in advance. I hope your reply soon. With Best Regards, Xavier Piao, China.