{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T18:45:53Z","timestamp":1772477153787,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2014,7,24]],"date-time":"2014-07-24T00:00:00Z","timestamp":1406160000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04\u20130.24 m\/s; height RMSE was in the range 5\u201368 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions.<\/jats:p>","DOI":"10.3390\/s140813324","type":"journal-article","created":{"date-parts":[[2014,7,24]],"date-time":"2014-07-24T11:00:50Z","timestamp":1406199650000},"page":"13324-13347","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":57,"title":["A Sensor Fusion Method for Tracking Vertical  Velocity and Height Based on Inertial and Barometric  Altimeter Measurements"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3306-6498","authenticated-orcid":false,"given":"Angelo","family":"Sabatini","sequence":"first","affiliation":[{"name":"The BioRobotics Institute, Scuola Superiore Sant'Anna, Viale Rinaldo Piaggio, Pontedera 34 56025, Pisa, Italy"}]},{"given":"Vincenzo","family":"Genovese","sequence":"additional","affiliation":[{"name":"The BioRobotics Institute, Scuola Superiore Sant'Anna, Viale Rinaldo Piaggio, Pontedera 34 56025, Pisa, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2014,7,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1109\/MCG.2002.1046626","article-title":"Motion tracking: No silver bullet, but a respectable arsenal","volume":"22","author":"Welch","year":"2002","journal-title":"IEEE Comput. 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