Low-cost inertial estimation unit based on extended Kalman filtering

Martin Rezac; Zdenek Hurak

doi:10.1117/12.850030

29 September 2010 Low-cost inertial estimation unit based on extended Kalman filtering

Martin Rezac, Zdenek Hurak

Proceedings Volume 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI; 76961F (2010) https://doi.org/10.1117/12.850030
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

The paper describes some design and implementation aspects of a low-cost inertial estimation unit based on comercially available inertial sensors. The primary task for the unit described in this paper is to estimate the attitude (orientation, pose), but the extension to estimating the position and height is planned. The size of the unit is about the size of a handheld device. It includes a commercially available 3-axis rate gyro combined in a single package with a 3-axis accelerometer and a 3-axis magnetometer. In order to include position estimation capabilities a GPS receiver is attached and a barometric pressure sensor can be added. The primary limitation of the implementation described in this paper is that it assumes no long term acceleration of the carrier (neither along a linear nor along a curved path), which makes the result of less value in aerospace industry but may have some appeal to researcher engineers in other fields. The data measured by the three sensors are fused using the Extended Kalman filtering paradigm. No model of the dynamics of the carrier (aircraft, mobile robot or a patient) is relied upon, the only modeled dynamics is that of sensors, such as the bias and noise. The choice of extended Kalman filtering methodology was dictated by strong requirements on computational simplicity. Some experience with implementation of the proposed scheme on a digital hardware (ARM7 based microcontroller) is shared in the paper. Finally, functionality of the presented device is demonstrated in experiments. Besides simple indoor tests, fly experiments were conducted using a small UAV helicopter.

Citation Download Citation

Martin Rezac and Zdenek Hurak "Low-cost inertial estimation unit based on extended Kalman filtering", Proc. SPIE 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI, 76961F (29 September 2010); https://doi.org/10.1117/12.850030

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