Vehicle Vibration Error Compensation on IMU-accelerometer Sensor Using Adaptive Filter and Low-pass Filter Approaches

In vehicle dead reckoning or vehicle positioning systems, an inertial measurement unit (IMU) sensor has an important role to provide acceleration and orientation of the vehicle. The acceleration from the IMU accelerometer is used to calculate the velocity of the vehicle, and then it estimates the vehicle's distance traveled to time. However, the accelerometer suffers from external noises such as vehicle vibrations (generated from the engine, alternator, compressor, etc) and road noises. This paper delivers deep analysis and focuses on how to handle the error from vehicle vibrations. A filter method is proposed by using a combination of adaptive least mean squares (LMS) and low-pass finite impulse response (FIR) filters. The adaptive LMS filter is used to cancel the vehicle vibration error frequencies and adapts those frequency changes in several engine rotation conditions. It is then finalized with the low-pass FIR filter which is used to filter high-frequency vibration noises. Several experiments were made and the results show that the proposed filtering method is able to give better signal to noise ratio (SNR dB) and noise attenuation ratio (ATT dB) in comparison with regular low-pass FIR filter and independent adaptive LMS filter in a particular condition.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.27(2019) (online)DOI　http://dx.doi.org/10.2197/ipsjjip.27.33------------------------------

In vehicle dead reckoning or vehicle positioning systems, an inertial measurement unit (IMU) sensor has an important role to provide acceleration and orientation of the vehicle. The acceleration from the IMU accelerometer is used to calculate the velocity of the vehicle, and then it estimates the vehicle's distance traveled to time. However, the accelerometer suffers from external noises such as vehicle vibrations (generated from the engine, alternator, compressor, etc) and road noises. This paper delivers deep analysis and focuses on how to handle the error from vehicle vibrations. A filter method is proposed by using a combination of adaptive least mean squares (LMS) and low-pass finite impulse response (FIR) filters. The adaptive LMS filter is used to cancel the vehicle vibration error frequencies and adapts those frequency changes in several engine rotation conditions. It is then finalized with the low-pass FIR filter which is used to filter high-frequency vibration noises. Several experiments were made and the results show that the proposed filtering method is able to give better signal to noise ratio (SNR dB) and noise attenuation ratio (ATT dB) in comparison with regular low-pass FIR filter and independent adaptive LMS filter in a particular condition.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.27(2019) (online)DOI　http://dx.doi.org/10.2197/ipsjjip.27.33------------------------------