IMU-바로미터 기반의 수직변위 추정용 이단계 칼만/상보 필터
A Two-step Kalman/Complementary Filter for Estimation of Vertical Position Using an IMU-Barometer System
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초록
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 19.7cm while that of the raw barometer signal was 43.4cm.
Abstract
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 19.7cm while that of the raw barometer signal was 43.4cm.
참고문헌 (13)
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