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시간지연을 고려한 간접 되먹임 구조 칼만필터의 수치안정성 향상 기법
남성호,성창기,김태원,Nam, Seongho,Sung, Changky,Kim, Taewon 한국군사과학기술학회 2017 한국군사과학기술학회지 Vol.20 No.1
Most of weapon systems use aided navigation system which integrates inertial navigation and aiding sensors to compensate the INS errors increasing with the passage of time. Various aid sensors can be applied such as Global Navigation Satellite System (GNSS), radar, barometer, etc., but there might exist time delay caused by signal processing or transferring aid information. This time delay leads out-of-sequence measurements (OOSM) systems. Previously, optimal and suboptimal measurment update method for OOSM systems, where the time delay length are known, are proposed. However, previous algorithm does not guarantee the positive definite property of covariance matrix. In order to improve numerical stability for aided navigation using delayed-measurement, this paper proposes a new measurement covariance update algorithm be similar to Joseph-form in Kalman filter. Futhermore, we propose how to implement it in indirect feedback Kalman filter structure, which is commonly used in aided navigation systems, for time-delayed measurement systems. Simulation and vehicle test results show effectiveness of a proposed algorithm.
정보이론기반 지형 험준도 및 정보이득을 이용한 지형대조항법 성능 향상 기법
남성호,Nam, Seongho 한국군사과학기술학회 2017 한국군사과학기술학회지 Vol.20 No.3
Terrain referenced navigation(TRN) system is an attractive method for obtaining position based on terrain measurements and a terrain map. We focus on TRN systems based on the point mass filter(PMF) which is one of the recursive Bayesian method. In this paper, we propose two kinds of performance index for Bayesian filter. The proposed indices are based on entropy and mutual information from information theory. The first index measures roughness of terrain based on entropy of likelihood. The second index named by information gain, which is the mutual information between priori and posteriori distribution, is a quantity of information gained by updating measurement at each step. The proposed two indices are used to determine whether the solution from TRN is adequate for TRN/INS integration or not, and this scheme gives the performance improvement. Simulation result shows that the proposed indices are meaningful and the proposed algorithm performs better than normal TRN algorithm.
크레머-레어 바운드를 이용한 베이지안 필터 기반 지형대조항법 성능 검증
이정신(Jungshin Lee),성창기(Changki Sung),남성호(Seongho Nam),한경준(Kyungjun Han),오주현(Juhyun Oh),김천중(Cheonjoong Kim) 대한전자공학회 2017 대한전자공학회 학술대회 Vol.2017 No.6
By using Cramér-Rao Bound(CRB), Bayesian nonlinear filter based Terrain Referenced Navigation (TRN) algorithms can be evaluated. First, general CRB is derived from Fisher Information Matrix(FIM). In this study, the recursive posterior CRB is derived to evaluate the performance of TRN algorithms. Next, Point-Mass filter and various Particle filters are designed and evaluated through Monte Carlo simulation. Performance evaluation is inferred from the proximity to CRB.