서지주요정보
(A) study on suboptimal nonlinear filtering methods = 준최적화 비선형 필터링 방법들에 관한 연구
서명 / 저자 (A) study on suboptimal nonlinear filtering methods = 준최적화 비선형 필터링 방법들에 관한 연구 / Myoung-Ho Oh.
저자명 Oh, Myoung-Ho ; 오명호
발행사항 [대전 : 한국과학기술원, 1996].
Online Access 원문보기 원문인쇄

소장정보

등록번호

8006648

소장위치/청구기호

학술문화관(문화관) 보존서고

DMA 96004

SMS전송

도서상태

이용가능

대출가능

반납예정일

초록정보

Three new suboptimal nonlinear filtering methods are proposed. The damped modified iterated Kalman filter for nonlinear discrete time systems is presented. The modified iterated Kalman filter, which will be called MIKF for brevity, is derived from the modified Newton method to approximate a maximum likelihood estimate. The MIKF is also obtained by an iteration scheme for the extended Kalman filter equations. A convergence analysis of the MIKF is given. By the damping method, we can reduce the total CPU time needed to estimate the state variables or may even obtain a convergent scheme when the MIKF diverges. The modified quasilinear filtering method for estimation of processes in multidimensional nonlinear stochastic systems has been proposed. This method produces more accurate filter coefficients than the standard quasilinear filtering method. To compute these coefficients, it suffices to know the distribution of the state vector of stochastic system. It can be determined by using the software for statistical analysis of multidimensional nonlinear stochastic systems. All computations connected with the determination of coefficients of the modified quasilinear filters do not use the results of observations. Therefore they can be computed in advance in the process of designing the filter. The lower-order suboptimal filtering method for estimating the state vector for a special class of discrete nonlinear systems is proposed. The dimension of state in this filter is less than that in the extended Kalman filter. The comparative less computation time required for calculation of the filter gains and implementation of the estimation process make it possible to apply this method to multidimensional dynamic systems in real time. Numerical examples show the effective convergence behavior of the proposed filters. Depending on several factors, which are required to the particular problem, such as convergence and computational efficiency, one can choose an appropriate method.

서지기타정보

서지기타정보
청구기호 {DMA 96004
형태사항 [ii], 52 p. : 삽도 ; 26 cm
언어 영어
일반주기 저자명의 한글표기 : 오명호
지도교수의 영문표기 : U-Jin Choi
지도교수의 한글표기 : 최우진
학위논문 학위논문(박사) - 한국과학기술원 : 수학과,
서지주기 Reference : p. 50-52
주제 Suboptimal Nonlinear Filtering
Damped Modified Iterated Kalman Filter
Modified Quasilinear Filter
Low-Order Suboptimal Filter
준최적화 비선형 필터링
김폭형 수정 반복형 Kalman 필터 수정 준선형 필터
저수위 준최적화 필터
QR CODE qr code