{"title":"基于MEMS的低成本IMU自适应振动滤波器的设计与实现","authors":"Ufuk Guner, H. Canbolat, A. Unluturk","doi":"10.1109/ELECO.2015.7394499","DOIUrl":null,"url":null,"abstract":"In this work, an adaptive vibration filter was designed for Micro Electro - Mechanical System (MEMS) based on low cost Inertial Measurement Unit (IMU). Designed IMU has ten degree freedom. It consists of three axis accelerometer, three axis gyroscope, three axis magnetometer and one axis barometric pressure sensor. All sensors are connected to Cortex M3 based microcontroller. Kalman Filter was used as sensor fusion algorithm. Although Kalman filter could overcome many noise sources, it could give undesirable output signal when sensors, which are combined with Kalman filter, were affected by simultaneously same noise like as vibration noise. So in order to overcome the vibration affection of IMU, an Adaptive Noise Canceller (ANC) was designed and implemented for the IMU. In addition, an experimental setup was built to compare the IMU output with and without ANC.","PeriodicalId":369687,"journal":{"name":"2015 9th International Conference on Electrical and Electronics Engineering (ELECO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Design and implementation of adaptive vibration filter for MEMS based low cost IMU\",\"authors\":\"Ufuk Guner, H. Canbolat, A. Unluturk\",\"doi\":\"10.1109/ELECO.2015.7394499\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, an adaptive vibration filter was designed for Micro Electro - Mechanical System (MEMS) based on low cost Inertial Measurement Unit (IMU). Designed IMU has ten degree freedom. It consists of three axis accelerometer, three axis gyroscope, three axis magnetometer and one axis barometric pressure sensor. All sensors are connected to Cortex M3 based microcontroller. Kalman Filter was used as sensor fusion algorithm. Although Kalman filter could overcome many noise sources, it could give undesirable output signal when sensors, which are combined with Kalman filter, were affected by simultaneously same noise like as vibration noise. So in order to overcome the vibration affection of IMU, an Adaptive Noise Canceller (ANC) was designed and implemented for the IMU. In addition, an experimental setup was built to compare the IMU output with and without ANC.\",\"PeriodicalId\":369687,\"journal\":{\"name\":\"2015 9th International Conference on Electrical and Electronics Engineering (ELECO)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 9th International Conference on Electrical and Electronics Engineering (ELECO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ELECO.2015.7394499\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 9th International Conference on Electrical and Electronics Engineering (ELECO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELECO.2015.7394499","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design and implementation of adaptive vibration filter for MEMS based low cost IMU
In this work, an adaptive vibration filter was designed for Micro Electro - Mechanical System (MEMS) based on low cost Inertial Measurement Unit (IMU). Designed IMU has ten degree freedom. It consists of three axis accelerometer, three axis gyroscope, three axis magnetometer and one axis barometric pressure sensor. All sensors are connected to Cortex M3 based microcontroller. Kalman Filter was used as sensor fusion algorithm. Although Kalman filter could overcome many noise sources, it could give undesirable output signal when sensors, which are combined with Kalman filter, were affected by simultaneously same noise like as vibration noise. So in order to overcome the vibration affection of IMU, an Adaptive Noise Canceller (ANC) was designed and implemented for the IMU. In addition, an experimental setup was built to compare the IMU output with and without ANC.