The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Vehicular Pitch Estimation Algorithm with ACF/IMMKF Based on GPS/IMU/OBD Data Fusion

GPS/IMU/OBD 융합기반 ACF/IMMKF를 이용한 차량 Pitch 추정 알고리즘

  • Kim, Ju-won (Hanyang University Department of Electronics and Computer Engineering) ;
  • Lee, Myung-su (Department of Electronics and Computer Engineering, Hanyang University) ;
  • Lee, Sang-sun (Department of Electronics and Computer Engineering, Hanyang University)
  • Received : 2015.07.13
  • Accepted : 2015.09.09
  • Published : 2015.09.30
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Abstract

The longitudinal velocity is necessary for accurate vehicular positioning in urban environment. The pitch angle, which is a road slope, should be calculated to acquire the longitudinal velocity. However, it is impossible to consider very accurate pitch, when using a sensor and an algorithm. That's why process noise and positioning stimation error of IMU should be adjusted to the driving environment and fuse GPS, OBD data with ACF which consist of AKF, CF in this paper. Then, final pitch angle which is appropriate for driving environment is estimated by IMMKF in order to optimize the system model according to road slope models.

도심지환경에서 정확한 차량 위치를 추정하기 위해서는 종방향 속도가 필요하다. 이러한 종방향 속도는 노면경사, 즉 차량의 피치각(Pitch) 산출을 통해서 가능하다. 하지만 단일 센서와 알고리즘을 이용한 피치각 추정에는 정확한 값을 기대할 수 없다. 본 논문에서는 정확한 피치각 추정을 위해 AKF(Adaptive Kalman Filter)와 CF(Complementary Filter)로 구성된 ACF(Adaptive Complementary Filter)를 이용하여 IMU(Inertial Measurement Unit)의 프로세스 노이즈와 측정에러를 주행환경에 맞게 조절하고, 이에 GPS(Global Positioning System)와 OBD(Onboard Equipment) 데이터를 융합한다. 그리고 노면 경사 모델에 따른 필터에 시스템 모델 최적화를 위해 IMMKF(Interactive Multiple Model Kalman Filter)를 사용하여 주행환경에 적합한 최종 피치각을 추정한다.

Keywords

References

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