• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.4
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• pp.332-340
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• 2011

A missile with a strapdown seeker should properly estimate line-of-sight(LOS) rate using its attitude information and the look angle of the seeker because LOS rate information in an inertial coordinate system, which is used for a proportional navigation(PN) homing guidance, can not be obtained directly. However, an unnecessary feedback loop(Parasite Loop) is formed in the guidance and control loop, and it may cause the guidance performance degradation or even the unstability of the system(Parasite Effect). This paper presents estimation methods for the LOS rate information and effective ways to minimize the parasite effect using Routh-Hurwitz stability criterion. Various numerical simulations are also included to verify the proposed methods.

• Journal of Sensor Science and Technology
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• v.8 no.2
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• pp.139-147
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• 1999

In this paper, we present the new angular velocity pick-off method for DTG (dynamically tuned gyroscope) which is widely used in various inertial navigation systems and motion control systems. In case of the external angular velocity input, the proposed scheme can make a smaller tilt-angle rather than that of conventional PI method in the transient and steady state because it has an additional inner rebalance loop with a mathematical model of the real gyroscope. So, without any mechanical redesign of the DTG, its dynamic range can be enlarged by the proposed method. The theoretical analysis and simulation model of DTG with the proposed scheme are given. Finally, the proposed scheme is verified.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.3
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• pp.285-291
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• 2004

GPS photogrammetry or the GPS/INS photogrammetry, which are based on the direct measurement of the projection centers and attitude at the moment of camera exposure time through loading the GPS receiver or INS in aircraft. Both photogrammetric methods can offer us to acquire the exterior orientation parameters with only minimum ground control points, even the ground control process could be completely skipped. Consequently, we can drastically reduce the time and cost for the mapping process. In this thesis, test flight was conducted in Suwon area to evaluate the performance of accuracy and efficiency through the analysis of results among the three photogrammetric methods, that is, traditional photogrammetry, GPS photogrammetry and GPS/INS photogrammetry. Test results shows that a large variety of advantages of GPS photogrammetry and GPS/INS photogrammetry against traditional photogrammetry is to be verified. Especially, the number of ground control points for the exterior orientation could be saved more than 70～80%, respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.135-143
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• 2009

Integrating the Global Positioning System (GPS) and Inertial Navigation System (INS) sensor technologies using the precise GPS Carrier phase measurements is a methodology that has been widely applied in those application fields requiring accurate and reliable positioning and attitude determination; ranging from 'kinematic geodesy', to mobile mapping and imaging, to precise navigation. However, such integrated system may not fulfil the demanding performance requirements when the baseline length between reference and mobil user GPS receiver is grater than a few tens of kilometers. This is because their positioning/attitude determination is still very dependent on the errors of the GPS observations, so-called "baseline dependent errors". This limitation can be remedied by the integration of GPS and INS sensors, using multiple reference stations. Hence, in order to derive the GPS distance dependent errors, this research proposes measurement processing algorithms for multiple reference stations, such as a reference station ambiguity resolution procedure using linear combination techniques, a error estimation based on Kalman filter and a error interpolation. In addition, all the algorithms are evaluated by processing real observations and results are summarized in this paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.548-549
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• 2015

무인 잠수정은 자율 무인잠수정(이하 'AUV' 또는 '자율무인잠수정'을 혼용)과 원격조정잠수정(이하 'ROV'로 지칭)으로 분류를 할 수 있다. ROV는 테더 게이블로 인한 작업 범위의 한계와 운동성능 효율이 떨어지는 단점을 지니고 있어, 테더 케이블이 필요 없는 AUV에 대한 필요성이 증대되고 있다. 추측 항법 시스템인 관성 항법 시스템(inertial navigation system, 이하 'INS'로 지칭)은 외부 도움없이 관성측정 장치(inertial measurement unit, 이하 'IMU'로 지칭)를 활용하여 구성된 시스템을 말한다. IMU는 자이로 스코프(gyroscope), 가속도계(accelerometer), 지자기(magnetic)센서로 구성된 측정 장치로 3개의 센서를 사용하여 상호 보정을 통한 기동 체의 위치, 속도 및 자세 정보를 제공한다. 복합항법시스템은 추측항법시스템이 가지는 누적오차와 측위 항법시스템이 가지는 외부환경에 대한 단점을 상호 보완하는 방법으로 연구가 진행 중이다. 하지만 심해서 또는 해양의 특성에 따라 측위 시스템이 사용되지 못하기 때문에 추측 항법시스템의 다양한 관성 센서를 활용한 상로 보완과 신호처리 방법을 통한 연구 개발이 진행 중이다. 다양한 센서 정보를 통합하는 목적으로 칼만 필터와 같은 최적 필터기법이 보편적으로 사용되고 있다. 칼만 필터는 확률 선형 시스템에 대하여 공정잡음 및 측정 잡음이 가우시안 확률 분포를 따를 때 최적의 추정자가 된다. 또한 가우시안 조건을 만족하지 않는 경우에도 선형 추정자 중에 추정 오차의 분산이 가장 작은 추정자이다. 칼만 필터가 최상의 성능을 발휘 하려면 공정잡음과 측정 잡음의 실제 값을 정확히 알아내는 것이 중요하다. 잡음 수준에 대한 정보가 부정확 할 경우 칼만 필터는 발산 할 수 있기 때문에 시스템에서 잡음 수준의 공산은 칼만 필터의 최적 이득을 결정하는 중요한 요소로 추정치에 큰 영향을 준다. 따라서 칼만 필터를 추측항법시스템에 적용 시킬 경우 실제 모텔의 잡음 공분산을 정확히 추정할 수 있는 기법이 요구된다. 추측항법시스템은 다양한 센서를 활용하기 때문에 움직이는 기동 표적에 적용시 잡음공분상이 변하기 때문에 항법시스템이 저하 될 수 있다. 본 연구에서는 다양한 센서를 융합하여 해양 생체 로봇의 정밀 자세 제어가 가능한 시스템을 제안하고자 한다.

• Economic and Environmental Geology
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• v.48 no.6
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• pp.451-465
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• 2015

The free-air anomalies are computed using a data set from various types of gravity measurements in the Korean Peninsula area. The gravity values extracted from the Earth Gravitational Model 2008 are used in the surrounding region. The upward continuation technique suggested by Dragomir is used in the computation of the external free-air anomalies at various altitudes. The integration radius 10 times the altitude is used in order to keep the accuracy of results and computational resources. The direct geodesic formula developed by Bowring is employed in integration. At the 1-km altitude, the free-air anomalies vary from -41.315 to 189.327 mgal with the standard deviation of 22.612 mgal. At the 3-km altitude, they vary from -36.478 to 156.209 mgal with the standard deviation of 20.641 mgal. At the 1,000-km altitude, they vary from 3.170 to 5.864 mgal with the standard deviation of 0.670 mgal. The predicted free-air anomalies at 3-km altitude are compared to the published free-air anomalies reduced from the airborne gravity measurements at the same altitude. The rms difference is 3.88 mgal. Considering the reported 2.21-mgal airborne gravity cross-over accuracy, this rms difference is not serious. Possible causes in the difference appear to be external free-air anomaly simulation errors in this work and/or the gravity reduction errors of the other. The external gravity field is predicted by adding the external free-air anomaly to the normal gravity computed using the closed form formula for the gravity above and below the surface of the ellipsoid. The predicted external gravity field in this work is expected to reasonably present the real external gravity field. This work seems to be the first structured research on the external free-air anomaly in the Korean Peninsula area, and the external gravity field can be used to improve the accuracy of the inertial navigation system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.4
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• pp.342-351
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• 2010

UAV (Unmanned Aerial Vehicle) have an INS(Inertial Navigation System) equipment and also have an electro-optical Equipment for mission. This paper proposes the vision based attitude estimation algorithm using Kalman Filter and Optical flow for UAV. Optical flow is acquired from the movie of camera which is equipped on UAV and UAV's attitude is measured from optical flow. In this paper, Kalman Filter has been used for the settlement of the low reliability and estimation of UAV's attitude. Algorithm verification was performed through experiments. The experiment has been used rate table and real flight video. Then, this paper shows the verification result of UAV's attitude estimation algorithm. When the rate table was tested, the error was in 2 degree and the tendency was similar with AHRS measurement states. However, on the experiment of real flight movie, maximum yaw error was 21 degree and Maximum pitch error was 7.8 degree.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1121-1126
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• 2017

Various studies such as INS(: Inertial Navigation System) are conducting to estimate the position of UAV, because the GPS information of UAV is at risk like the GPS jamming. The position estimation using DoA and RTT are used to apply many radar systems, and that process can be applied in datalink of UAV. The general monopulse feed in UAV datalink is Multi-horn, because of the wide BW(: Band Width) and frequency range. And it needs wide SNR range of tracking because of the limited transmit power of airborne unit. The estimation error of position increase at low SNR, and the DoA is valid in only 3dB beam width but high SNR causes false of mainlobe detection because of large sidelobe. In this paper, We propose the method to achieve higher accuracy of DoA estimation on low SNR and review some idea that able to detect mainlobe.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.177-186
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• 2017

Recently, Autonomous vehicles are getting hot attention. Amazon, the biggest online shopping service provider is developing a delivery system that uses drones. This kinds of platforms are need accurate attitude information for navigation. In this paper, a structure design of AHRS using low-cost inertia sensor is proposed. To estimate attitudes a Kalman filter which uses a quaternion based dynamic model, bias-removed measurements from MEMS Gyro, raw measurements from MEMS accelerometer and magnetometer, is designed. To remove bias from MEMS Gyro, an additional Kalman filter which uses raw Gyro measurements and attitude estimates, is designed. The performance of implemented AHRS is compared with high price off-the-shelf 3DM-GX3-25 AHRS from Microstrain. The Gyro bias was estimated within 0.0001[deg/s]. And from the estimated attitude, roll and pitch angle error is smaller than 0.2 and 0.3 degree. Yaw angle error is smaller than 6 degree.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.26-34
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• 2008

The information of traversability and path planning is essential for UGV(Unmanned Ground Vehicle) navigation. Such information can be obtained by analyzing 3D terrain. In this paper, we present the method of 3D terrain modeling with color information from a camera, precise distance information from a 2D Laser Range Finder(LRF) and wheel encoder information from mobile robot with less data. And also we present the method of 3B terrain modeling with the information from GPS/IMU and 2D LRF with less data. To fuse the color information from camera and distance information from 2D LRF, we obtain extrinsic parameters between a camera and LRF using planar pattern. We set up such a fused system on a mobile robot and make an experiment on indoor environment. And we make an experiment on outdoor environment to reconstruction 3D terrain with 2D LRF and GPS/IMU(Inertial Measurement Unit). The obtained 3D terrain model is based on points and requires large amount of data. To reduce the amount of data, we use cubic grid-based model instead of point-based model.