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: 『한국산업기술융합학회 학술대회 논문집』2021년 전반기 학술대회 논문집, 19~25쪽, 전체 7쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2021.05.27

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.

키워드

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