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GPS 비가용 환경을 고려한 점검 무인비행체의 보조 측위센서 설계 개념
서의석(Ui-Suk Suh),이찬석(Chan-Seok Lee),김태완(Tae-Wan Kim),나원상(Won-Sang Ra) 대한전기학회 2021 전기학회논문지 Vol.70 No.3
This paper suggests a novel localization sensor for substation inspection UAVs carrying out their missions under a GPS-denied environment. The proposed sensor consists of a transmitter located at the known position and a cruciform receiver array which enables the UAV to measure the time difference of arrivals. For such case, the UAV localization problem can be cast into a passive nonlinear state estimation using the range difference (RD) information expressed by a nonlinear function of the UAV position of interest. To avoid the performance degradation due to the inherent nonlinearity of the problem, we reformulate the localization problem in the setting of a linear robust state estimation. Ensuring the robustness against imperfect RD measurement noise statistics which is cruicial for determining filter design parameters, a modified robust weighted least squares estimator is designed by considering the geometric constraint between the state variables as an additional information. Experimental results show that the proposed design concept of a UAV localization sensor is applicable in practice.
재진입 표적추적을 위한 복수 레이더 2단계 정보융합 기법
정보영(Boyoung Jung),이찬석(Chan-Seok Lee),서의석(Ui-Suk Suh),나원상(Won-Sang Ra) 대한전기학회 2021 전기학회논문지 Vol.70 No.9
This paper proposes a two-stage track-to-track fusion algorithm for re-entry target tracking using multiple radars. The existing track-to-track fusion strategy relying only on the kinematic information shows unreliable target tracking performance when the target of interest is adjacent with other objects. To prevent tracking performance degradation due to false track fusion, the track paring hypothesis is evaluated using both the feature data and the kinematic data provided by radars. A recursive Bernoulli filter is desinged to discriminate the target identity by fusing binary decision data which correspond to the most probable track pairing hypothesis. Since our approach exploits the statistical property of the available decision data, it can enhance the target tracking and identification performance. Through the computer simulations for a typical re-entry target tracking scenario, the effectiveness of the suggested data fusion scheme is demonstrated.