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Low-cost IMU Data Denoising using Savitzky-Golay Filters | IEEE Conference Publication | IEEE Xplore

Low-cost IMU Data Denoising using Savitzky-Golay Filters

Publisher: IEEE

Abstract:

MEMS sensors have been used in many applications including navigation systems. However, these sensors suffer from highly noisy measurements. If left untreated, these erro...View more

Abstract:

MEMS sensors have been used in many applications including navigation systems. However, these sensors suffer from highly noisy measurements. If left untreated, these errors will significantly degrade the ultimate navigational solution. Hence, applying a pre-filtering technique becomes a necessity to de-noise these sensor signals to improve the overall system performance. While wavelet denoising is the most common technique for sensor data pre-filtering, it may not be suitable for real-time implementations. This paper explores another method; namely, Savitzky-Golay filters, which can provide competitive denoising performance with a less computationally demanding algorithm. The purpose of the paper is to examine the performance of the new method against wavelet de-noising with respect to both positioning and attitude accuracy and computations time. We applied the filter to denoise MEMS-based inertial sensors data in a tightly coupled integrated INS/GPS system. Our results showed that the new method outperformed the wavelet denoising approach. Moreover, the new method demands much less computations time, which makes it more suitable for embedded systems and real-time applications.
Date of Conference: 19-21 March 2019
Date Added to IEEE Xplore: 16 May 2019
ISBN Information:
Publisher: IEEE
Conference Location: Sharjah, United Arab Emirates

References

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