Advanced SearchSearch Tips
A Two-step Kalman/Complementary Filter for Estimation of Vertical Position Using an IMU-Barometer System
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A Two-step Kalman/Complementary Filter for Estimation of Vertical Position Using an IMU-Barometer System
Lee, Jung Keun;
  PDF(new window)
Estimation of vertical position is critical in applications of sports science and fall detection and also controls of unmanned aerial vehicles and motor boats. Due to low accuracy of GPS(global positioning system) in the vertical direction, the integration of IMU(inertial measurement unit) with the GPS is not suitable for the vertical position estimation. This paper investigates an IMU-barometer integration for estimation of vertical position (as well as vertical velocity). In particular, a new two-step Kalman/complementary filter is proposed for accurate and efficient estimation using 6-axis IMU and barometer signals. The two-step filter is composed of (i) a Kalman filter that estimates vertical acceleration via tilt orientation of the sensor using the IMU signals and (ii) a complementary filter that estimates vertical position using the barometer signal and the vertical acceleration from the first step. The estimation performance was evaluated against a reference optical motion capture system. In the experimental results, the averaged estimation error of the proposed method was 19.7 cm while that of the raw barometer signal was 43.4 cm.
Vertical position;Vertical acceleration;Kalman filter;Complementary filter;IMU(inertial measurement unit);Barometer;
 Cited by
Gyroscopic drift compensation by using low cost sensors for improved attitude determination, Measurement, 2018, 116, 199  crossref(new windwow)
P. Gasior, S. Gardecki, J. Goslinski, and W. Giernacki, "Estimation of altitude and vertical velocity for multirotor aerial vehicle using Kalman filter," in Recent Advances in Automation, Robotics and Measuring Techniques, Vol. 267, R. Szewczyk, C. Zielinski, and M. Kaliczynska, Eds. Heidelberg, Germany: Springer International Publishing, 2014, pp. 377-385.

S. Zihajehzadeh, T. J. Lee, J. K. Lee, R. Hoskinson, and E. J. Park, "Integration of MEMS inertial and pressure sensors for vertical trajectory determination," IEEE Trans. Instrum. Meas., Vol. 64, No. 3, pp. 804-814, 2015. crossref(new window)

O. Svabensky, J. Weigel, and R. Machotka, "On GPS heighting in local networks," Acta Geodyn. Geomater., Vol. 3, No. 143, pp. 39-43,Jun. 2006.

Y. B. Son, and S. Y. Oh, "A barometer-IMU fusion method for vertical velocity and height estimation," IEEE Proc. of Sensors, pp. 1-4, Busan, Korea, 2015.

A. M. Sabatini and V. Genovese, "A sensor fusion method for tracking vertical velocity and height based on inertial and barometric altimeter measurements," Sensors, Vol. 14, No. 8, pp. 13324-13347, 2014. crossref(new window)

P. Pierleoni, A. Belli, L. Palma, L. Pernini, and S. Valenti, "An accurate device for real-time altitude estimaion using data fusion algorithms," Proc. of 2014 IEEE/ASME 10th Int'l Conf. on MESA., pp.1-5, Senigallia, Italy, 2014.

M. Tanigawa, H. Luinge, L. Schipper, P. Slycke, "Drift-free dynamic height sensor using MEMS IMU aided by MEMS pressure sensor," Proc. 5th Workshop on Positioning, Navigation and Communication, pp. 191-196, Hannover, Germany, 2008.

Y. Kim, Y. Hwang, S. Choi and J. Lee, "Height estimation scheme of low-cost pedestrian dead-reckoning system using Kalman filter and walk condition estimation algorithm," Proc. of IEEE/ASME International Conf. on AIM., pp.1492-1497, Wollongong, Australia, 2013.

F. Bianchi, S. J. Redmond, M. R. Narayanan, S. Cerutti, and N. H. Lovell, "Barometric pressure and triaxial accelerometry-based falls event detection," IEEE Trans. Neural Sys. Rehab. Eng., Vol. 18, No. 6, pp. 619-627, 2010. crossref(new window)

J. K. Lee, E. J. Park, and S. N. Robinovitch, "Estimation of attitude and external acceleration using inertial sensor measurement during various dynamic conditions", IEEE Trans. Instrum. Meas., Vol. 61, No. 8, pp. 2262-2273, 2012. crossref(new window)

T. Walter, and J. R, Higgins, "A comparison of complementary and Kalman filtering," IEEE Trans. Aerosp. Electron. Syst., Vol. AES-11, No. 3, pp. 321-325, 1975. crossref(new window)

A. M. Sabatini and V. Genovese, "A stochastic approach to noise modeling for barometric altimeters," Sensors, Vol. 13, No. 11, pp. 15692-15707, 2013. crossref(new window)

T. Degen, H. Jaeckel, M. Rufer, and S. Wyss, "SPEEDY: a fall detector in a wrist watch", in Proc. 7th IEEE Int. Symposium on Wearable Computing, pp. 184-187, 2003.