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

• Item type: Journal(1)
• 公開日: 2019-01-15
• タイトル: Vehicle Vibration Error Compensation on IMU-accelerometer Sensor Using Adaptive Filter and Low-pass Filter Approaches
• タイトル / 言語: en
• タイトル: Vehicle Vibration Error Compensation on IMU-accelerometer Sensor Using Adaptive Filter and Low-pass Filter Approaches
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [特集：未来の暮らしを支えるパーベイシブシステムと高度交通システム] adaptive LMS filter, low-pass FIR filter, vehicular accelerometer, IMU sensor, on board diagnostic (OBD-II), digital signal processing
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Computer Science and Electrical Engineering, Kumamoto University／Center of Electronics Technology, Agency for Assessment and Application of Technology (BPPT)
• 著者所属: Faculty of Engineering, Hiroshima University
• 著者所属: Big Data Science and Technology, Faculty of Advanced Science and Technology, Kumamoto University
• 著者所属(英): en
• 著者所属(英): Computer Science and Electrical Engineering, Kumamoto University / Center of Electronics Technology, Agency for Assessment and Application of Technology (BPPT)
• 著者所属(英): en
• 著者所属(英): Faculty of Engineering, Hiroshima University
• 著者所属(英): en
• 著者所属(英): Big Data Science and Technology, Faculty of Advanced Science and Technology, Kumamoto University
• 著者名: Bondan, Suwandi; Teruaki, Kitasuka; Masayoshi, Aritsugi
• 著者名(英): Bondan, Suwandi; Teruaki, Kitasuka; Masayoshi, Aritsugi
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: 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 of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.27(2019) (online); DOI http://dx.doi.org/10.2197/ipsjjip.27.33; ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: 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 of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.27(2019) (online); DOI http://dx.doi.org/10.2197/ipsjjip.27.33; ------------------------------
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 60, 号 1, 発行日 2019-01-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764