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

• 한국군사과학기술학회지
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• 제8권3호
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• pp.5-10
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• 2005

This paper presents the new in-flight alignment method using the flight distance of vehicle in order to improve the performance of the heading error estimation. In the proposed method, the Kalman filter having the difference between GPS and SDINS position as measurements is used for levelling of SDINS and heading error is estimated utilizing the flight distance information. It is shown in the simulation results that the in-flight method proposed in this paper has the high accuracy in heading error estimation and the heading error can be very quickly estimated at the high speed vehicle, compared with the existing method using the Kalman filter.

• Journal of Positioning, Navigation, and Timing
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• 제4권4호
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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.

• 제어로봇시스템학회논문지
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• 제12권11호
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• pp.1124-1129
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• 2006

In this paper, in-flight alignment algorithm using UKF is presented for an SDINS aided by SSBL or GPS system under large initial heading error. The EKF usually applied for this task. This approximates the propagation of mean and covariance accurate to first-order only. To overcome this limitation, the unscented transformation that achieves second order approximation is applied to the in-flight alignment. To analyze the performance of the proposed method, simulations for S-type trajectory are carried out. The results show that performance of EKF and UKF are the almost same when the initial heading error is smaller than $30^{\circ}$, but UKF has a better performance for large initial heading error about $45^{\circ}$.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.109-113
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• 2006

This paper presents an in-flight alignment method for strapdown inertial navigation systems based on the line-of-sight information. Unlike the existing methods, the proposed method utilizes only the 2-axis angle measurements of the onboard image sensor and does not require any explicit range measurements between the vehicle and landmarks. To improve the accuracy of all the position, velocity, and attitude estimates through the in-flight alignment, an error model of the image-sensor-aided SDINS is derived. A simulation study demonstrates that the accuracy of SDINS can be improved by the line-of-sight information only.

• International Journal of Aeronautical and Space Sciences
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• 제18권3호
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• pp.565-573
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• 2017

This paper presents a multistage in-flight alignment (MIFA) method for a strapdown inertial navigation system (SDINS) suitable for moving vehicles with no initial attitude references. A SDINS mounted on a moving vehicle frequently loses attitude information for many reasons, and it makes solving navigation equations impossible because the true motion is coupled with an undefined vehicle attitude. To determine the attitude in such a situation, MIFA consists of three stages: a coarse horizontal attitude, coarse heading, and fine attitude with adaptive Kalman navigation filter (AKNF) in order. In the coarse horizontal alignment, the pitch and roll are coarsely estimated from the second order damping loop with an input of acceleration differences between the SDINS and GPS. To enhance estimation accuracy, the acceleration is smoothed by a scalar filter to reflect the true dynamics of a vehicle, and the effects of the scalar filter gains are analyzed. Then the coarse heading is determined from the GPS tracking angle and yaw increment of the SDINS. The attitude from these two stages is fed back to the initial values of the AKNF. To reduce the estimated bias errors of inertial sensors, special emphasis is given to the timing synchronization effects for the measurement of AKNF. With various real flight tests using an UH60 helicopter, it is proved that MIFA provides a dramatic position error improvement compared to the conventional gyro compass alignment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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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 ...

• 한국군사과학기술학회지
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• 제13권4호
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• pp.708-715
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• 2010

In Strapdown Inertial Navigation System, alignment accuracy is the most important factor to determine the performance of navigation. However by an existing self-alignment method, it takes a long time to acquire the alignment accuracy that we want. So, to attain the desired alignment accuracy in as little as $\bigcirc$ minutes, we have developed the precise multi-position alignment method. In this paper, it is proposed a inertial measurement matching transfer alignment method among alignment methods to minimize the alignment error in a short time. It is based on a mixed velocity-DCM matching method be suitable to the operating environment of vertical launching system. The compensation methods to reduce misalign error, especially azimuth angle error incurred by measurement time-delay error and body flexure error are analyzed and evaluated with simulation. This simulation results are finally confirmed by experimentations using FMS(Flight Motion Simulator) in Lab and the integration test to follow the fire control mission.

• 제어로봇시스템학회논문지
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• 제20권4호
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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.

• 한국항공우주학회지
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• 제34권11호
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• pp.42-46
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• 2006

SDINS 운항중 정렬에 적용 가능한 GPS 반송파 위상변화율 측정 모델을 유도하여 새로운 SDINS/GPS 복합항법 시스템 구성 방법을 제안한다. 제안된 SDINS/GPS 복합항법 필터의 성능 분석을 공분산 해석기법을 이용하여 수행하고 이의 결과를 실제 차량 실험을 통하여 검증한다. 제안된 결합기법은 2개 이상의 안테나를 갖는 SDINS/GPS 결합시스템에 적용가능하며 기수각 추정에 직접적으로 연계된 GPS 측정치를 생성함으로써 빠른 SDINS의 기수각 추정을 가능하게 함으로써 SDINS/GPS의 항법 성능을 향상시키게 된다.