http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
평방근 정보필터를 이용한 상관된 측정잡음을 갖는 기동표적의 추적을 위한 상호간섭다중모델 기법
권성숙,김경연 濟州大學校 産業技術硏究所 1998 산업기술연구소논문집 Vol.9 No.1
In tracking a maneuvering target by a radar system. the measurement noise is significantly correlated when the measurement frequency is high. In this paper. we describe an efficient interacting multiple model(IMM) approach for tracking a maneuvering target with correlated measurement noise based on the square root information filter(SR1F). The SRIF is employed instead of conventional Kalman filter since it exhibits more efficient features in handling the decorrelation process and improved numerical characteristics. The Monte Carlo simulations for the maneuvering target are provided to demonstrate the enhanced tracking performance of the proposed algorithm.
평방근 정보필터를 이용한 상관된 측정잡음을 갖는 기동표적의 추적을 위한 상호간섭다중모델 기법
권성숙,김경연 濟州大學校 工科大學 産業技術硏究所 1998 尖端技術硏究所論文集 Vol.9 No.1
In tracking a maneuvering target by a rader system, the measurement noise is significantly correlated when the measurement frequency is high. In this paper, we describe an efficient interacting multiple model(IMM) approach for tracking a maneuvering target with correlated measurement noise based on the square root information filter(SRIF). The SRIF is employed instead of conventional Kalman filter since it exhibits more efficient features in handling the decorrelation process and improved numerical characteristics. The Monte Carlo simulations for the maneuvering target are provided to demonstrate the enhanced tracking performance of the proposed algorithm.
평방근 정보필터를 이용한 미지의 측정 바이어스를 갖는 시스템에 대한 적응추정기의 설계
권성숙,김경연,김창일,김경식 濟州大學校工科大學産業技術硏究所 1996 尖端技術硏究所論文集 Vol.7 No.2
In this paper, we present an adaptive estimator for tracking of a maneuvering target containing unknown or randomly switching biased measurements using square root information filter(SRIF). The SRIF is employed instead of conventional Kalman filter since it exhibits more efficient features in handling the unknown measurements bias and improved numerical characteristics. Computer simulations for a system with unknown bias are carried out to show the adaptability and tracking performance of the proposed algorithm.