• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2009년도 제40회 하계학술대회
• /
• pp.1923_1924
• /
• 2009

최근 들어 소프트웨어의 테스트에 대한 필요성이 증가함에 따라 소프트웨어 테스트 방법에 대한 연구가 활발해지고 있으며 이를 적용한 제품들도 다양한 분야에서 개발되고 있다. 또한 UML과 같은 모델 기반의 언어가 등장함에 따라 소프트웨어의 재사용성 등을 높일 수있는 설계가 가능하다. 본 논문에서는 테스트가 가능한 SDINS/GPS 통합 항법 소프트웨어 구조를 UML 모델로 제시하며, 제시한 모델에 대한 테스트 절차를 기술한다. 본 논문의 결과를 이용하여 SDINS/GPS 통합 항법 소프트웨어를 설계하면 소프트웨어를 다른 하드웨어로 이식하는 것과 다른 센서 측정치를 처리하기 위한 소프트웨어 확장이 용이하다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
• /
• pp.519-521
• /
• 1987

Among the gyroscopes used for SDINS, the dynamically turned gyroscope (DTG) covers a wide dynamic range while it is simple and small. In addition, it is a two-degree-of freedom gyro; it can detect two-axis input simultaneously. DTG, since its development in 1970's, is widely accepted for strapdown inertial systems. In the first year, we have concentrated on developing a two degree-of-freedom DIG. An interdisciplinary research team has been formed to accomplish the first year objective. Five departments in the College of Engineering, Seoul National University are involved. They are; 1) Department of Control and Instrumentation, 2) Department of Mechanical Design and Production, 3) Department of Electrical Engineering, 4) Department of Electronic Engineering, and 5) Department of Metallurgical Engineering. In addition, the Department of Precision Mechanical Engineering of Pusan National University is subcontracted to develop a test procedure for gyroscope and SDINS. Gyroscope is a key sensor for SDINS. Furthermore gyroscope itself is used as a. independent sensor for vehicle guidance and control and fire control system. Gyroscope and SDINS are an important for defense, aeronautical, and space industries that Korea is and will be actively involved. Upon the success of the project, they are expected to be manufactured in Korea under a cooperative effort between university and industry.

• 제어로봇시스템학회논문지
• /
• 제20권4호
• /
• pp.468-473
• /
• 2014

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.

• 제어로봇시스템학회논문지
• /
• 제8권3호
• /
• pp.249-255
• /
• 2002

Since the stationary alignment process of the SDINS is not completely observable, some furls of the aided alignment have been applied. The purpose of this paper is to propose a new initial alignment algorithm, which utilizes the attitude output from the AGPS(Attitude Determination GPS) receiver and to demonstrate the feasibility of the proposed algorithm with several experimental results. A Kalman filter is designed for utilizing the attitude output as well as the zero velocity information. Also analyzed is the observability of the SDINS error model. To show the feasibility of the proposed scheme, we implement an alignment system where HG1700AE IMU (Inertial Measurement Unit) from Honeywell and an AGPS receiver designed at Chungnam National University are used. Test trials are done to evaluate the performance of the proposed alignment scheme. The proposed algorithm provides as good initial alignment performance as a high accurate navigation system, MAPS(Modular Azimuth Positioning System) INS.

• 한국군사과학기술학회지
• /
• 제9권3호
• /
• pp.132-140
• /
• 2006

In this paper, a new fault detection method for the extended Kalman filter, which uses a N-step predictor, is proposed. The N-step predictor performs the only time propagations for N-step intervals without measurement updates and its output is used as a monitoring signal for the fault detection. A consistency between the extended Kalman filter and the N-step predictor is tested to detect a fault. A test statistic is defined by the difference between the extended Kalman filter and the N-step predictor. The proposed method is applied to strapdown inertial navigation system (SDINS). By computer simulation, it is shown that the proposed method detects a fault effectively.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.56.1-56
• /
• 2001

Initial attitude error is one of the large error sources in the navigation errors of SDINS. And it is important to decide the initial attitude of SDINS. The method, like a self-alignment or a transfer alignment method, is required to a precise INS. If we do not have a precise INS, we should get large attitude error. After performing the initial alignment, a vehicle has the initial attitude error. Therefore, it results in navigation error due to the initial attitude error. But, if we use position information during flight, we could estimate and compensate a vehicle attitude error. So, we can maintain a precise attitude in spite of existing the initial attitude error. Using the uplinked position information from a land-based radar system, the new algorithm estimates the attitude of the SDINS during flight ...

• Journal of Positioning, Navigation, and Timing
• /
• 제4권4호
• /
• pp.181-186
• /
• 2015

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.

• 제어로봇시스템학회논문지
• /
• 제8권6호
• /
• pp.524-532
• /
• 2002

This paper presents a new in-flight alignment method for an SDINS under large initial heading error. To handle large heading error, a new attitude error model is introduced. The attitude errors are divided into heading error and leveling errors using a newly defined horizontal frame. Some navigation error dynamic models are derived from the attitude error model for indirect feedback filtering of the in-flight alignment system. A Kalman filter with Position measurement is designed to estimate navigation errors as the indirect feedback filter Simulation results show that the proposed in-flight alignment method reduces the heading error very quickly from more than 40deg to about 5deg so as to apply a refined navigation filter. The total alignment process including leveling mode and navigation mode in addition to the proposed one allows large initial values not only in heading error but also in leveling errors.

• International Journal of Control, Automation, and Systems
• /
• 제1권4호
• /
• pp.444-452
• /
• 2003

An integration system with multi-measurement sets can be realized via combined application of a centralized and federated Kalman filter. It is difficult for the centralized Kalman filter to remove a failed sensor in comparison with the federated Kalman filter. All varieties of Kalman filters monitor innovation sequence (residual) for detection and isolation of a failed sensor. The innovation sequence, which is selected as an indicator of real time estimation error plays an important role in adaptive mechanism design. In this study, the centralized Kalman filter with adaptive measurement fusion is introduced by means of innovation sequence. The objectives of adaptive measurement fusion are automatic isolation and recovery of some sensor failures as well as inherent monitoring capability. The proposed adaptive filter is applied to the GPS/SDINS integration system with an additional sensor. Simulation studies attest that the proposed adaptive scheme is effective for isolation and recovery of immediate sensor failures.

• 한국정밀공학회지
• /
• 제4권4호
• /
• pp.56-71
• /
• 1987

Determination of navigation variables (latitude, longitude, and altitude) near the earth's surface is termed 'Terrestrial Navigation'. The quantities that are measured inertially are the total acceleration (or the integral fo this acceleration over a fixed time interval) and the total angular rate (or the integral of this angular rate over the same time interval). These measurements when suitably compensated can be manipulated to yield the navigation variables. Hence, it is essential that the initial values of position, orientation and velocity are accurately set up during the initial alignment process. Initial alignment of gimballed inertial navigation system ( GINS) is accomplished by gyrocompassing techniques. These cannot be used, in the case of strapdown inertial navigation system(SDINS), where the inertial instruments are directly strapped down to a vehicle frame. The basic objective of this paper is the development of digital method for the determination of the initial axes erection of a SDINS from vibration and sway currupted data on the launch pad.