• 한국해양공학회지
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• 제37권1호
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• pp.38-48
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• 2023

To maintain the existing systems of ships and introduce autonomous operation technology, it is necessary to improve situational awareness through the sensor fusion of the automatic identification system (AIS) and automatic radar plotting aid (ARPA), which are installed sensors. This study proposes an algorithm for determining whether AIS and ARPA signals are sent to the same ship in real time. To minimize the number of errors caused by the time series and abnormal phenomena of heterogeneous signals, a tracking method based on the combination of the unscented Kalman filter and probabilistic data association filter is performed on ARPA radar signals, and a position prediction method is applied to AIS signals. Especially, the proposed algorithm determines whether the signal is for the same vessel by comparing motion-related components among data of heterogeneous signals to which the corresponding method is applied. Finally, a measurement test is conducted on a training ship. In this process, the proposed algorithm is validated using the AIS and ARPA signal data received by the voyage data recorder for the same ship. In addition, the proposed algorithm is verified by comparing the test results with those obtained from raw data. Therefore, it is recommended to use a sensor fusion algorithm that considers the characteristics of sensors to improve the situational awareness accuracy of existing ship systems.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 추계학술대회 논문집
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• pp.461-462
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• 2006

• 한국농림기상학회지
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• 제12권4호
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• pp.238-240
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• 2010

• 한국통신학회논문지
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• 제37권5C호
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• pp.355-364
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• 2012

협동교전능력을 위한 표적정보 수집, 실시간 정보융합, 공동 상황인식 기능 구현을 위하여 표적 처리기법 연구는 중요하다. 이러한 표적 처리 연구 중, 표적의 추적의 문제는 센서로부터 얻어진 측정값을 사용하여 표적의 상태를 예측하는 것으로부터 시작한다. 그러나 상태 예측에 사용되는 센서의 측정값들은 불확실성을 갖고 있기 때문에 측정된 정보에 어느 정도의 신뢰성을 부여할 수 있느냐가 중요한 문제가 된다. 따라서 이를 위해 다중 센서를 이용한 기법이 요구되고, 보편적으로 사용되는 확률적 데이터연관 기법으로부터 다중 센서를 이용한 표적 추적을 위해서는 이종 센서로부터 제공된 측정값들을 처리하기 위한 정보융합 기법이 필요하다. 본 논문에서는 레이더 및 ESM 센서에서 측정된 측정값 정보융합을 통하여 확률데이터연관 필터를 이용한 표적의 트랙 추정 성능을 향상시키기 위한 방법을 구체적으로 분석하여 정보를 결합하기 위한 새로운 실시간측정값 융합 기법을 제안하고 확률데이터연관을 통해 추적할 표적의 트랙을 추정하는 방법을 분석하였다. 모의실험을 통해 제안된 기법들이 선형 혹은 회전 운동하는 모델들에 대해 향상된 추정 결과를 보여준다.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제53권1호
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• pp.8-14
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• 2004

An O-mode Ultrashort Pulse Reflectometry (USPR) system has been designed and developed for the measurement of electron density profiles on the Sustained Spheromak Physics Experiment (SSPX) spheromak. In the original design of SSPX, peak densities were envisioned to be in the range of 0.5-3${\times}$10$^{14}$ cm$^{-3}$ . The total duration of formation and sustained discharges is typically ∼2 msec. Moreover, diagnostic access on SSPX is severely restricted. Such high density and short duration plasmas coupled with stringent diagnostic access are quite challenging for conventional reflectometer systems. In USPR, the SSPX diagnostic requirements have been successfully satisfied by employing up-converting mixers and monostatic horn/waveguide configuration. As a result, the USPR system has proven its applicability for the density measurement of a future fusion device. In the density profile measurements, the USPR system is capable of routinely generating density profiles with a temporal resolution of 57 $\mu$s. This paper presents details regarding the USPR fundamental principles, associated subsystems and laboratory tests as well as the experimental results obtained on SSPX

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제5B권3호
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• pp.289-295
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• 2005

Instrumentation and Control (I&C) of the Neutral Beam Test Stand (NB- TS) Facility at the Korea Atomic Energy Research Institute (KAERI) for the Korea Superconducting Tokamak Advanced Research (KSTAR) project has been underway since the start of the project to answer the diverse requests arising from the various facets of the development and construction phases of the project. Optical signal transmission constitutes a significant portion of I&C works and has been performed for the entirety of the project. During the NB- TS construction and related experiments, significant achievements to a more accurate as well as more refined optical signal transmissions have been made. Examples of those I&C works that utilized the optical signal transmission are the Langmuir probe signal transmission, gradient grid current signal transmission, gas flow control and signal transmission, ion source temperature measurement, beam line component temperature monitoring, and coolant flow signal transmission, etc. These optical signal transition provisions are now performing part of the indispensable functions for the proper operation of the NB- TS facility. Attained experience and expertise are expected to be well applied to the upcoming main neutral beam injection (NBI) system construction for the KSTAR project.

• 한국진공학회지
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• 제20권4호
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• pp.243-251
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• 2011

국내에서 개발 중인 맥동관형 냉동기 및 일반적인 GM 냉동기 성능평가를 위해 냉각용량 측정 장치를 제작한 후, 측정절차 검토 및 장치 성능확인의 일환으로 상용 냉동기의 냉각용량을 측정했다. 측정된 2차원 냉각용량 차트는 실험에 사용한 냉동기 모델이 가지는 고유 특성을 잘 나타냈다. 이 논문에서는 제작된 냉각용량 평가 장치의 설계사항 및 시운전 결과를 소개한다.

• 한국해양공학회지
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• 제11권3호
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• pp.170-179
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• 1997

This paper presents a hybrid navigation system for AUV to locate its position precisely in rough sea. The tracking system is composed of various sensors such as an inclinometer, a tri-axis magnetometer, a flow meter, and a super short baseline(SSBL) acoustic position tracking system. Due to the inaccuracy of the attitude sensors, the heading sensor and the flowmeter, the predicted position slowly drifts and the estimation error of position becomes larger. On the other hand, the measured position is liable to change abruptly due to the corrupted data of the SSBL system in the case of low signal to noise ratio or large ship motions. By introducing a sensor fusion technique with the position data of the SSBL system and those of the attitude heading flowmeter reference system (AHFRS), the hybrid navigation system updates the three-dimensional position robustly. A Kalman filter algorithm is derived on the basis of the error models for the flowmeter dynamics with the use of the external measurement from the SSBL. A failure detection algorithm decides the confidence degree of external measurement signals by using a fuzzy inference. Simulation is included to demonstrate the validity of the hybrid navigation system.

• Journal of Positioning, Navigation, and Timing
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• 제12권2호
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• pp.129-140
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• 2023

Autonomous driving systems are likely to be operated in various complex environments. However, the well-known integrated Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS), which is currently the major source for absolute position information, still has difficulties in accurate positioning in harsh signal environments such as urban canyons. To overcome these difficulties, integrated Visual/Inertial/GNSS (VIG) navigation systems have been extensively studied in various areas. Recently, a Compressed-State Constraint Kalman Filter (CSCKF)-based VIG navigation system (CSCKF-VIG) using a monocular camera, an Inertial Measurement Unit (IMU), and GNSS receivers has been studied with the aim of providing robust and accurate position information in urban areas. For this new filter-based navigation system, on the basis of time-propagation measurement fusion theory, unnecessary camera states are not required in the system state. This paper presents a performance evaluation of the CSCKF-VIG system compared to other conventional navigation systems. First, the CSCKF-VIG is introduced in detail compared to the well-known Multi-State Constraint Kalman Filter (MSCKF). The CSCKF-VIG system is then evaluated by a field experiment in different GNSS availability situations. The results show that accuracy is improved in the GNSS-degraded environment compared to that of the conventional systems.

• 제어로봇시스템학회논문지
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• 제13권7호
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• pp.637-648
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• 2007

This paper presents a sensor fusion method based on indirect Kalman filter(IKF) for error compensation of low-cost inertial sensors and its application to the determination of attitude and position of small flying robots. First, the analysis of the measurement error characteristics to zero input is performed, focusing on the bias due to the temperature variation, to derive a simple nonlinear bias model of low-cost inertial sensors. Moreover, from the experimental results that the coefficients of this bias model possess non-deterministic (stochastic) uncertainties, the bias of low-cost inertial sensors is characterized as consisting of both deterministic and stochastic bias terms. Then, IKF is derived to improve long term stability dominated by the stochastic bias error, fusing low-cost inertial sensor measurements compensated by the deterministic bias model with non-inertial sensor measurement. In addition, in case of using intermittent non-inertial sensor measurements due to the unreliable data link, the upper and lower bounds of the state estimation error covariance matrix of discrete-time IKF are analyzed by solving stochastic algebraic Riccati equation and it is shown that they are dependant on the throughput of the data link and sampling period. To evaluate the performance of proposed method, experimental results of IKF for the attitude determination of a small flying robot are presented in comparison with that of extended Kaman filter which compensates only deterministic bias error model.