In this paper, we have studied the sources of error of a low-cost 3-axis MEMS accelerometer by means of Power Spectral Density and Allan Variance techniques. These techniques were applied to the signals acquired from ten identical devices to characterize the variability of the sensor produced by the same manufacturer. Our analysis showed as identically produced accelerometer have somehow variable behavior in particular at low frequency. It is therefore of paramount importance before their use in Inertial Navigation or Earthquakes Monitoring System, a complete characterization of each single sensors.
D'Alessandro, A., Vitale, G., Scudero, S., D'Anna, R., Costanza, A., Fagiolini, A., et al. (2017). Characterization of MEMS accelerometer self-noise by means of PSD and Allan Variance analysis. In Proceedings of the 7th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI) [10.1109/IWASI.2017.7974238].
Characterization of MEMS accelerometer self-noise by means of PSD and Allan Variance analysis
Fagiolini, A.
;Greco, L.
2017-01-01
Abstract
In this paper, we have studied the sources of error of a low-cost 3-axis MEMS accelerometer by means of Power Spectral Density and Allan Variance techniques. These techniques were applied to the signals acquired from ten identical devices to characterize the variability of the sensor produced by the same manufacturer. Our analysis showed as identically produced accelerometer have somehow variable behavior in particular at low frequency. It is therefore of paramount importance before their use in Inertial Navigation or Earthquakes Monitoring System, a complete characterization of each single sensors.
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