MEMS/FOG 관성항법장치의 간접 교정 기법 개발

유해성(Yu Haesung),오주현(Ju-Hyun Oh),이인섭(Inseop Lee),김천중(Cheon-Joong Kim),박흥원(Heung-won Park) 한국항공우주학회 2020 한국항공우주학회 학술발표회 논문집 Vol.2020 No.7

큰 초기 자세 오차를 가진 관성항법장치의 운항중 정렬을 위한 비선형 필터 연구

유해성(Haesung Yu),최상욱(Sang Wook Choi),이상정(Sang Jeong Lee) 제어로봇시스템학회 2014 제어·로봇·시스템학회 논문지 Vol.20 No.4

This paper describes the in-flight alignment of SDINS (Strapdown Inertial Navigation Systems) using an EKF (Extended Kalman Filter) and a UKF (Unscented Kalam Filter), which allow large initial attitude error uncertainty. Regardless of the inertial sensors, there are nonlinear error dynamics of SDINS in cases of large initial attitude errors. A UKF that is one of the nonlinear filtering approaches for IFA (In-Flight Alignment) are used to estimate the attitude errors. Even though the EKF linearized model makes velocity errors when predicting incorrectly in case of large attitude errors, a UKF can represent correctly the velocity errors variations of attitude errors with nonlinear attitude error components. Simulation results and analyses show that a UKF works well to handle large initial attitude errors of SDINS and the alignment error attitude estimation performance are quite improved.

링레이저 자이로 기반 관성항법장치와 위성항법장치의 강결합 방식 시스템 구현

유해성(Haesung Yu),박상은(Sang Eun Park),정진섭(Jinseob Jeong),박흥원(Heung-Won Park) 한국항공우주학회 2013 韓國航空宇宙學會誌 Vol.41 No.2

항공기에 탑재되어 운용되는 링레이저 자이로 기반 스트랩다운 관성항법장치(SDINS)와 위성항법장치(GPS)의 결합 시스템의 실시간 구현에 있어서 설계시 고려해야할 문제에 대해서 살펴본다. SDINS/GPS 결합 시스템의 실시간 구현시, 레버암, 측정치 획득 및 오차 보상 외에, 링 레이저 자이로 기반의 SDINS의 특성을 고려해야만 한다. 뱅크턴을 반복적으로 수행하는 항공기에서 발생하는 누적 수직축 자세 오차를 추정하기 위해, 자이로의 비정렬이 모델링된 모델을 구현한다. 항공기 탑재 시험을 통해 수직축 자세 오차의 누적 문제 및 실시간 구현 상의 문제를 해결하고, 자세 오차 추정 성능 향상 결과를 살펴본다. This paper explores a real-time system implementation to couple tightly StrapDown Inertial Navigation System(SDINS) and Global Positioning System(GPS) mounted on the aircraft. When implementing the SDINS/GPS coupled system in real-time processor, we have to deliberate SDINS’s unique characteristics based on the ring laser gyro, and besides, lever-arm, measurements, and error compensation method. The novel modeling method is applied to system the misalignment error term of gyro to estimate the cumulative heading attitude errors while the aircraft banking to turn repeatedly. Captive Flight Test results show that the proposed modeling strategy has good performance.

뱅크턴하는 항체에 대한 GPS를 이용한 SDINS의 자세 오차 추정 향상

유해성(Haesung Yu),유기정(Ki-Jeong Yoo),김현석(Hyun-Seok Kim),이윤선(Youn Seon Lee),박흥원(Heung-Won Park) 한국항공우주학회 2011 韓國航空宇宙學會誌 Vol.39 No.2

뱅크턴을 수행하는 항공기에 운용되는 관성항법장치의 특정 자이로 비정렬 오차가 수직축 자세오차를 연속적으로 증가시키는 현상에 대해서 분석을 수행하고, 이 자아로 비정렬 오차를 제거하기 위해 GPS을 결합한 INS/GPS 시스템에 대해서 새로운 비정렬 모델링 방법을 제시하고, 그 성능 향상을 시뮬레이션을 통해 제시한다. An approach to improve the performance of SDINS and GPS integrated system for bank-to-turn flight vehicles is described. Then, it is shown through the simulation that a specific gyro misalignment error results in an increased heading error of SDINS. A new modelling method is presented herein for identifying of sensor and attitude error. The main advantage of the proposed method is that it not only estimates the gyro misalignment error of SDINS, but also improves estimate performance of heading error of SDINS in the presence of the gyro misalignments.

간접교정 방법을 이용한 관성센서의 장기 안정도 평가 방법 연구

유해성(Haesung Yu),이인섭(Inseop Lee),오주현(Juhyun Oh),김천중(Cheonjoong Kim) 대한전기학회 2023 대한전기학회 학술대회 논문집 Vol.2023 No.7

항공기 Run-up 진동 환경에서의 관성항법장치 초기 정렬 방법 설계 및 평가

유해성(Haesung Yu),이인섭(Inseop Lee),오주현(JuHyun Oh),김천중(CheonJoong Kim),박흥원(Heung-won Park) 제어로봇시스템학회 2015 제어·로봇·시스템학회 논문지 Vol.18 No.1

Inertial Navigation Systems (INS) are widely used as the main navigation device for aircraft. To get the initial attitude, the INS requires the initial alignment before navigation starts. An aircraft also needs an engine test procedure that cause some vibrations before flight. An INS can`t be aligned in a vibration environment so the initial alignment is performed before the aircraft engine test. Therefore, the initial alignment time of an INS has been a major factor in limiting an aircraft`s takeoff response time. In this paper, we designed an initial alignment algorithm that can be executed even in disturbances such as aircraft run-up. We demonstrated verification of the algorithm that is embedded on the real INS and testing methods to evaluate the alignment of the INS. We also analyzed the test results of the proposed initial alignment algorithm that is performed during a real aircraft run-up.

한국 조선 산업의 주도권 회복에 대한 탐색적 연구: 최근 고부가가치 선종 수주 성과를 중심으로

양해성(Haesung Yang),곽기호(Kiho Kwak),전유수(Yu Su Jeon) 한국혁신학회 2021 한국혁신학회지 Vol.16 No.1

기술적 기회의 창이 제한적인 조선산업에서 한국은 어떻게 주도권을 회복하였는가? 상기 연구문제에 천착하여 본 연구에서는 추격 사이클 이론의 관점에서 최근(2018년~2020년)나타난 한국과 중국 간 조선산업 주도권 이전 현상을 탐색적으로 고찰하였다. 그 결과, 조선⋅해운산업에 대한 글로벌 차원의 온실가스⋅대기오염물질 배출 규제 강화와 그에 따른 LNG 관련 선박 시장 창출은 우리나라 조선산업에 규제⋅수요적 기회의 창으로 작용하였음을 확인하였다. 특히 세계적인 천연가스 가격 하락과 국가별 탄소 배출량 감축 정책 추진은 LNG 수송(LNG Carrier) 뿐 아니라 소비 관점에서 LNG 추진엔진 기반 선박 수요를 촉발시켰다. 더불어 온실가스 배출 규제 강화와 결합된 해운업계의 원가 경쟁 심화는 초대형 유조선 및 컨테이너선에 대한 수요 확대도 견인하였다. 이와 같은 규제⋅수요적 기회의 창에 대해 우리나라 조선산업은 고부가가치선 중심의 수주전략 전개, 수주경쟁력 제고를 위한 보완 기술 개발, 그리고 대우조선해양과 현대중공업의 합병을 추진함으로써 주도권 회복에 성공하였다. 반면 중국 조선산업은 환경 변화에도 불구하고 과거의 성공 요인이었던 저가의 벌크선 중심 수주 지속과 함께 시스템 통합 역량의 열위 및 미흡한 기자재 산업 육성으로 인해 산업 주도권을 내어주었다. 본 연구는 조선산업과 같이 기술적 기회가 적은 중저기술 산업에서의 ‘선발주자의 주도권 회복’에는 규제⋅수요적 기회의 창이 중요함을 확인했다는 점에서 의의가 있다. 특히 조선산업이 주력 수출 산업이자 동남권 지역 경제와 고용의 핵심 산업이라는 점에서 기존에 축적한 기술 유산(Legacy Technology)의 가치를 재확인하고, 전통 제조업의 혁신 성장에 대한 정책적 시사점을 제시한데에 그 의의가 있다. How Korea resurged as the leader of the shipbuilding sector, characterized as mature and medium-low technology intensity? To answer the research questions, we investigated the very recent industrial leadership change between Korea and China from the catch-up cycle perspective. As a result, we found that the strengthening of greenhouse gas and emission regulation on vessels served as a favorable institution-led market window of opportunity for Korea (incumbent). More specifically, the decline of natural gas prices and the promotion of policies to reduce greenhouse gas created an institution-led market window for Korea in terms of LNG transport and consumption. Heavier cost competition in the demand sector (marine transport) combined with the emission regulation also acted as an exogenous window for the incumbent. To respond to the institutional and demand windows, the Korean shipbuilding sector developed a marketing strategy centered on value-added vessels, key enabling technologies development for enhancing market competitiveness, and proactive merge and acquisition between leading shipbuilders. In contrast, the Chinese sector still focused on a low-end bulk carrier contract and was negligent in nurturing system integration capability as well as equipment sector. Our findings contribute to the extension of the ‘Catch-up cycle’ theory by shedding new light on the role of institutional and demand windows in the resurgence of ‘Old incumbents’ at the medium-low technology sector, where technological discontinuity rarely occurs.

Calibration Method for INS Based on Multiple Actuator Function

Yeong-Bin Seo,Haesung Yu,Myeong-Jong Yu 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.1

This paper presents a calibration method based on a multiple actuator function (MAF) to improve the navigation performance of the inertial navigation system (INS). The navigation performance of the INS can be improved by utilizing a compensation function. Existing calibration methods model the compensation function based on calibration coefficients obtained by indirect calibration. In indirect calibration, the calibration coefficients are calculated using acceleration errors. However, errors such as random walks, white noise, and bias instability can affect the precision of the calculated calibration coefficients. These errors can degrade the accuracy of the calibration coefficients and the compensation function. To overcome these limitations, the proposed method models a compensation function based on the MAF. The accuracy of the compensation function is improved by the accurate actuator angle and actuator position of the MAF. Unlike indirect calibration, the precision of the MAF is improved exclusively by navigation performance. The accurate actuator angle is calculated by adopting gradient descent and Q-learning, and the accurate actuator position is calculated by adopting the Bhattacharyya coefficient. The accuracy and precision of the proposed calibration method is evaluated by static-state tests and vehicle tests. The results show that the proposed calibration method is a valid approach to improve the navigation performance of the INS.

High-degree Cubature Kalman Filtering Approach for GPS Aided In-Flight Alignment of SDINS

Shin, Hyun-choel,Yu, Haesung,Park, Heung-won The Institute of Positioning 2015 Journal of Positioning, Navigation, and Timing Vol.4 No.4

A High-degree Cubature Kalman Filter (CKF) is proposed to deal with the Strapdown Inertial Navigation System (SDINS) alignment problem. In-flight Alignment (IFA) is an effective method to compensate for attitude errors of the navigation system. While providing precise attitude error compensation, however, the external source aided alignment often creates a nonlinear filtering problem caused by a large misalignment angle. Introduced recently, Cubature Kalman Filter is a suitable technique for various nonlinear problems. In this paper, a higher degree CKF is applied to this accuracy-is-everything SDINS IFA problem. The simulation results show that the proposed technique outperformed a traditional nonlinear filter in terms of precision and alignment time.

Compensation Method of Gyroscope Bias Hysteresis Error with Temperature and Rate of Temperature using Deep Neural Networks

Yeong-Bin Seo,Haesung Yu,Myeong-Jong, Yu,Sang Jeong Lee 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10

In this paper, a new compensation method for hysteresis bias error of the ring laser gyroscope (RLG) is proposed. Deep neural networks using temperature and rate of temperature is applied to obtain the RLG bias. In the process of entering the deep neural networks, temperature and rate of temperature are split into several factors for higher accuracy. Through entering these factors to the deep neural networks, more accurate estimation performance is achieved than simply entering the temperature and rate of temperature. The RLG bias estimating performance of deep neural network is evaluated through comparing with various methods – 3rd order function, classic rate of temperature method, and radial basis function network (RBFN). The experimental results show that the proposed compensation method has more precise calibration performance than others.