Noise modeling and analysis of an IMU-based attitude sensor: improvement of performance by filtering and sensor fusion

摘要

We describe the characterization and removal of noise present in the InertialMeasurement Unit (IMU) MPU-6050. This IMU was initially used in an attitudesensor (AS) developed in-house, and subsequently implemented in a pointing andstabilization platform developed for small balloon-borne astronomical payloads.We found that the performance of the IMU degrades with time due to theaccumulation of different errors. Using the Allan variance analysis method, weidentified the different components of noise present in the IMU and verifiedthe results using a power spectral density analysis (PSD). We tried to removethe high-frequency noise using smoothing filters, such as moving average filterand Savitzky-Golay filter. Although we did manage to filter some of thehigh-frequency noise, the performance of these filters was not satisfactory forour application. We found the distribution of the random noise present in theIMU using a probability density analysis, and identified the noise to be whiteGaussian in nature which we successfully removed by a Kalman filter in realtime.