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KCI등재 학술저널

앙상블 칼만필터를 이용한 데이터 추적 필터 구현

Data Tracking Filter Using Ensemble Kalman Filter

DOI : 10.29279/kostet.2020.25.4.1
  • 95

In this study, we developed an ensemble Kalman filter (EnKF) for a track-before-detect (TBD) radar-tracking algorithm. The TBD algorithm is used in environments where target detection is difficult, owing to heavy clutter environments, small radar cross-section targets, and stealth targets. Generally, reducing the threshold for the TBD algorithm increases nonlinearity and false alarms. Under these conditions, it is difficult to achieve desirable estimated accuracy of the tracking filter if conventional Kalman filter methods are used. In this study, it was found that the estimated accuracy of the tracking filter effectively improved the EnKF and extended Kalman filter root-mean-square error rates by 40% and 20%, respectively, when an EnKF was applied in TBD processing.

Ⅰ. 서 론

Ⅱ. 앙상블칼만필터

Ⅲ. 추적필터를 위한 레이다 시뮬레이터

Ⅳ. 앙상블칼만필터(EnKF) 처리 결과

Ⅴ. 결론 및 향후계획

참고문헌

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