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물리적 구속조건을 고려한 공대지 대전차 유도탄의 유도기법 연구
박봉균(Bong-Gyun Park),엄태윤(Tae-Yoon Um) 대한전기학회 2019 전기학회논문지 Vol.68 No.1
A composite guidance scheme is proposed for air-to-ground anti-tank missiles launched from an airborne platform. Long-range anti-tank missiles usually use a fiber optic line (FOL) for the datalink between an operator and the missile to obtain real-time target information and to command the missile. Also, impact angle control is used to maximize the warhead effectiveness, but it should be carefully implemented due to interference between the launch platform and the FOL. Thus, the proposed guidance scheme takes into account both impact angle and FOL constraints. Under system lag and acceleration limits, a selection method of guidance gains and calculation logic of the maximum achievable impact angle are proposed for a guideline of practical implementation. The performance of the proposed guidance scheme is investigated by nonlinear simulations with various engagement conditions.
미사일 및 표적 운동을 고려한 시선지령유도에서의 코리올리 가속도 보상
류동영(Dong-Young Rew),탁민제(Min-Jea Tahk),엄태윤(Um-Tae Yoon),송택렬(Taek-Lyul Song) 대한전자공학회 1992 대한전자공학회 학술대회 Vol.1992 No.10
In CLOS guidance, feedback compensation of the Coriolis acceleration is used to reduce miss distance. This paper presents the effects of the bandwidth of target and missile on the optimal Coriolis acceleration compensation. A state space formulation of CLOS guidance is used to implement CLOS guidance in feedback form. And the LQR control method is applied to find the optimal feedback gain. From the analysis of the Riccati equations of the optimal control, the following facts are observed: When the target is agile, the optimal gain is reduced, since the compensation becomes ineffective. The missile bandwidth also affects the Coriolis acceleration compensation. Narrower missile requires more compensation for the Coriolis acceleration.
Noise Covariances Estimation for Systems with Bias States
Um, Tae-Yoon,Lee, Jang-Gyu,Park, Seong-Taek,Park, Chan-Gook 서울대학교 항공우주신기술연구소 2000 항공우주신기술연구소 연구보고 Vol.1 No.2
This paper presents a new approach to noise covariances estimation for a linear, time-invariant, stochastic system with constant but unknown bias states. The system is supposed to satisfy controllable/observable conditions without bias states. Based on a restructured data representation, the covariance of a new variable that consists of measurement vectors is expressed as a linear combination of unknown parameters. Noise covariances are then estimated by employing a recursive least-squares algorithm. The proposed method requires no a priori estimates of noise covariances, provides consistent estimates, and can also be applied when the relationship between bias states and other states is unknown. The method has been applied to SDINS initial alignment. Simulation results indicate a satisfactory performance of the proposed method.