Please use this identifier to cite or link to this item: http://hdl.handle.net/2248/7336
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dc.contributor.authorNirmal, K-
dc.contributor.authorSreejith, A. G-
dc.contributor.authorMathew, J-
dc.contributor.authorMayuresh, Sarpotdar-
dc.contributor.authorAmbily, S-
dc.contributor.authorPrakash, A-
dc.contributor.authorSafonova, M-
dc.date.accessioned2020-11-20T13:28:49Z-
dc.date.available2020-11-20T13:28:49Z-
dc.date.issued2016-07-
dc.identifier.citationProceedings of the SPIE, Vol. 9912, pp. 99126W-1 - 99126W-10en_US
dc.identifier.issn0277-786X-
dc.identifier.urihttp://prints.iiap.res.in/handle/2248/7336-
dc.descriptionRestricted Access © SPIE--The International Society for Optical Engineering http://dx.doi.org/10.1117/12.2234255en_US
dc.description.abstractWe describe the characterization and removal of noises present in the Inertial Measurement Unit (IMU) MPU- 6050, which was initially used in an attitude sensor, and later used in the development of a pointing system for small balloon-borne astronomical payloads. We found that the performance of the IMU degraded with time because of the accumulation of different errors. Using Allan variance analysis method, we identified the different components of noise present in the IMU, and verified the results by the power spectral density analysis (PSD). We tried to remove the high-frequency noise using smooth filters such as moving average filter and then Savitzky Golay (SG) filter. Even though we managed to filter some high-frequency noise, these filters performance wasn't satisfactory for our application. We found the distribution of the random noise present in IMU using probability density analysis and identified that the noise in our IMU was white Gaussian in nature. Hence, we used a Kalman filter to remove the noise and which gave us good performance real time.en_US
dc.language.isoenen_US
dc.publisherSPIE-The International Society for Optical Engineeringen_US
dc.subjectBalloon experimenten_US
dc.subjectAttitude sensoren_US
dc.subjectPointing systemen_US
dc.subjectMEMS sensorsen_US
dc.titleNoise modeling and analysis of an IMU-based attitude sensor: improvement of performance by filtering and sensor fusionen_US
dc.typeArticleen_US
Appears in Collections:IIAP Publications



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