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향상된 표적 추적 기법을 이용한무유도 대전차 로켓의 조준 오차 제거 방법
송진모,김태완,박태선,도주철,배종수 한국군사과학기술학회 2018 한국군사과학기술학회지 Vol.21 No.1
In this paper, we proposed a method for eliminating aiming error of unguided anti-tank rocket using improved target tracking. Since predicted fire is necessary to hit moving targets with unguided rockets, a method was proposed to estimate the position and velocity of target using fire control system. However, such a method has a problem that the hit rate may be lowered due to the aiming error of the shooter. In order to solve this problem, we used an image-based target tracking method to correct error caused by the shooter. We also proposed a robust tracking method based on TLD(Tracking Learning Detection) considering characteristics of the FCS(Fire Control System) devices. To verify the performance of our proposed algorithm, we measured the target velocity using GPS and compared it with our estimation. It is proved that our method is robust to shooter’s aiming error.
무유도 로켓의 조준 장치를 이용한 영상 기반 이동 표적 정보 추정 기법 연구
송진모,이상훈,도주철,박태선,배종수,Song, Jin-Mo,Lee, Sang-Hoon,Do, Joo-Cheol,Park, Tai-Sun,Bae, Jong-Sue 한국군사과학기술학회 2017 한국군사과학기술학회지 Vol.20 No.3
In this paper, we present a method for estimating of position and velocity of a moving target by using the range and the bearing measurements from multiple sensors of aiming unit. In many cases, conventional low cost gyro sensor and a portable laser range finder(LRF) degrade the accuracy of estimation. To enhance these problems, we propose two methods. The first is background image tracking and the other is principal component analysis (PCA). The background tracking is used to assist the low cost gyro censor. And the PCA is used to cope with the problems of a portable LRF. In this paper, we prove that our method is robust with respect to low-frequency, biased and noisy inputs. We also present a comparison between our method and the extended Kalman filter(EKF).
A Finite Memory Filter for Discrete-Time Stochastic Linear Delay Systems
송일영,송진모,정웅지,공명술 한국센서학회 2019 센서학회지 Vol.28 No.4
In this paper, we propose a finite memory filter (estimator) for discrete-time stochastic linear systems with delays in state and mea- surement. A novel filtering algorithm is designed based on finite memory strategies, to achieve high estimation accuracy and stabilityunder parametric uncertainties. The new finite memory filter uses a set of recent observations with appropriately chosen initial horizonconditions. The key contribution is the derivation of Lyapunov-like equations for finite memory mean and covariance of system state with an arbitrary number of time delays. A numerical example demonstrates that the proposed algorithm is more robust and accurate than the Kalman filter against dynamic model uncertainties
이상훈,송진모,배종수,Lee, Sang-Hoon,Song, Jin-Mo,Bae, Jong-Sue 한국군사과학기술학회 2015 한국군사과학기술학회지 Vol.18 No.3
Pose estimation is an important operation for many vision tasks. This paper presents a method of estimating the camera pose, using a known landmark for the purpose of autonomous vertical takeoff and landing(VTOL) unmanned aerial vehicle(UAV) landing. The proposed method uses a distinctive methodology to solve the pose estimation problem. We propose to combine extrinsic parameters from known and unknown 3-D(three-dimensional) feature points, and inertial estimation of camera 6-DOF(Degree Of Freedom) into one linear inhomogeneous equation. This allows us to use singular value decomposition(SVD) to neatly solve the given optimization problem. We present experimental results that demonstrate the ability of the proposed method to estimate camera 6DOF with the ease of implementation.