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Vibration-Robust Adaptive Attitude Reference System Using Sequential Measurement Noise Covariance

진동환경에 강인한 순차적 측정 오차 공분산값을 이용한 적응 자세 결정

  • Received : 2015.09.09
  • Accepted : 2016.03.17
  • Published : 2016.04.01

Abstract

A new technique for Attitude & Heading Reference System (AHRS) by using sequential measurement noise covariance (SMNC) is addressed in a vibration environments in this paper. In particular, a low-cost inertial measurement unit in general diverges in the acceleration phase or vibrating environments due to inherent properties of gravity and acceleration. In this paper, by considering current and prior measurements to estimate actual attitudes and headings in a local frame, the proposed technique overcomes these problems efficiently. Finally, the performance of the suggested approach is verified by numerical simulations.

본 논문은 관성 항법 시스템(Inertial Navigation System)을 활용한 자세 및 방향 결정시스템(Attitude & Heading Reference System)의 성능을 향상시키기 위한 새로운 기법인, 순차적 측정 오차 공분산(Sequential Measurement Noise Covariance) 기법을 제시하였다. 관성 센서는 시간이 지남에 따라 발생하는 적분오차와 진동이나 가속구간과 같은 외란이 가해 졌을 때 성능이 저하된다는 단점이 있다. 특히, 저가의 관성 센서의 경우 이러한 현상이 더욱 두드러지게 나타난다. 이를 극복하기 위한 알고리즘들은 많이 존재한다. 하지만 가장 일반적으로 사용되는 확장 칼만 필터의 경우 가속도계를 사용할 때 측정값(Measurement)이 일정 범위를 넘어가면 센서값을 배제하는 방법을 사용한다. 본 논문에서 제안하는 기법은 범위를 설정하지 않고 과거의 데이터를 순차적으로 활용하여 측정값의 가중치를 변화하는 기법이다. 최종적으로 제안된 기법을 수치 시뮬레이션을 통해 검증하였다.

Keywords

References

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