• Journal of Institute of Control, Robotics and Systems
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• v.20 no.4
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• pp.468-473
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• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.1038-1044
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• 2016

In this paper, a SDINS(Strapdown Inertial Navigation System) rapid initial alignment technique robust to the pyro-shock in multi-launch rocket system is proposed. The proposed method consists of three steps. Firth, transfer alignment is performed to estimate misalignment between MINS(Master INS) and SINS(Slave INS), and the estimated misalignment is written in the memory when transfer alignment is completed. Next, the pre-filtering process is performed to get rid of the acceleration error induced by launcher vibration. Finally, the horizontal alignment is performed to compensate misalignment variation caused by pyro-shock. We verified the performance of the proposed alignment method comparing with the conventional transfer alignment method. The simulation shows that the proposed initial alignment technique improves alignment performance.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.4
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• pp.181-186
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• 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.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2521-2524
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• 2003

Since inertial sensor errors which increase with time are caused by initial orientation error and sensor errors (accelerometer bias and gyro drift bias), the accuracy of these devices, while still improving, is not adequate for many of today's high-precision, long-duration sea, aircraft, and long-range missile missions. This paper presents a navigation error compensation scheme for Strap-Down Inertial Navigation System (SDINS) using Line-Of-Sight(LOS) vector from star sensor. To be specific, SDINS error model and measurement equation are derived, and Kalman filter is implemented. Simulation results show the bounded-ness of position and attitude errors.

• Journal of the Korean Society for Precision Engineering
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• v.4 no.4
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• pp.56-71
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• 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.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.3
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• pp.132-140
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• 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
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• 1993.10a
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• pp.299-303
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• 1993

In an underwater vehicle, the navigation error is mostly caused by the initial misalignment, the bias of a gyro and an accelerometer, and the sea current. Therefore, it is important that these error sources are estimated and compensated in order to reduce the navigation error. In this paper, the E.M.Log aided SDINS is designed by using the E.M.Log which measures the forward velocity of a vehicle. And the system error state equation and the measurement equation are derived and the suboptimal Kalman Filter is established for this aided SDINS. The simulation result showed that this had an important role in estimating and compensating these error sources, thus reducing the navigation error of an underwater vehicle.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.3
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• pp.368-377
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• 2009

In this paper we study the gyro bias calibration method of SDINS(Strap-Down Inertial Navigation System). Generally, SDINS's calibration is performed in 2-axis(or 3-axis) rate table with chamber for varying ambient temperature. We assumed that the majority of calibration-parameter except for gyro bias is knowned. During gyrobias calibration procedure, it can be induced some disturbances(accelerometer's short-term error induced rate table rotation and anti-vibration mount's rotation). In these cases, old gyro-bias calibration methods(using velocity error or attitude error) have an error, because these disturbances are not detectable at the same time. So that, we propose a new gyro-bias calibration method(heading error minimizing using equivalent linear transformation) that can detect anti-vibration mount's rotation. And we confirm efficiency of the new gyro-bias calibration method by simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.56.1-56
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• 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 ...

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.142-146
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• 1991

In order to develope transfer alignment algorithm which achieves accurate initial alignment of slave strapdown inertial navigation system(SDINS) of a missle using master SDINS of mobile launchers third-order suboptimal filter is constructed to estimate the transformation matrix between two SDINS coordinates. In Kalman Filter formulation, the measurement equation uses that of accelerometer when stationary, and is replaced by that of gyroscope when elevating the missle. This switching method is applied to increase the degree of observability and to remove the error generated by lever arm effect. Simulation results show that the azimuth transfer error is about 0.3 mrad, and confirm that this scheme has a potential for real application.