앙상블 칼만필터를 이용한 데이터 추적 필터 구현

• 영문명: Data Tracking Filter Using Ensemble Kalman Filter
• 발행기관: 한국산업기술융합학회(구. 산업기술교육훈련학회)
• 저자명: 하성재(Sung-Jae Ha) 김응조(Eung-Jo Kim) 김철현(Cheol-Hyun Kim)
• 간행물 정보: 『산업기술연구논문지』산업기술연구논문지 제25권 4호, 1~7쪽, 전체 7쪽
• 주제분류: 공학 > 공학일반
• 파일형태: PDF
• 발행일자: 2020.12.30

영문 초록

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.

목차

Ⅰ. 서 론

Ⅱ. 앙상블칼만필터

Ⅲ. 추적필터를 위한 레이다 시뮬레이터

Ⅳ. 앙상블칼만필터(EnKF) 처리 결과

Ⅴ. 결론 및 향후계획

참고문헌

키워드

파티클필서 탐지전추적 신호처리 레이더 오경보율 Ensemble Kalman Filter Track-Before-Detect Radar Signal Processing Radar CFAR