• Title/Summary/Keyword: track accuracy

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Experiment on Track-keeping Performance using Free Running Model Ship (모형 선박을 이용한 선박 침로유지 실험 연구)

  • Im, Nam-Kyun;Tran, Van-Luong
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.18 no.3
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    • pp.221-226
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    • 2012
  • This research presents an analysis of algorithm for ship track-keeping along a given trajectory. The maneuver of a free running model ship guiding through a simple path are presented. In order to solve the above problem, a desired trajectory is usually determined by GPS points in a pre-fixed place then these points are set in a pre-programmed navigation so that the ship would be automatically tracked. Proportional-Derivative(PD) control which is useful for fast response controllers was used in this program as a course keeping system. A high accuracy GPS receiver was installed on the model ship that could provide positions frequently, the system will compare and give out the remaining distance and heading to the target way-point. The results of ship auto track-keeping experiment will be explained in order to illustrate the adjustment in controlling parameters. These results can be utilized as a preliminary step to carry out the experiment of ship collision avoidance system and automatic berthing in the future.

Kinematic Modeling of a Track Trolley Using Extended Kalman Filter (확장 칼만필터를 이용한 궤도틀림 트롤리의 운동학적 모형화)

  • Lee, Jun S.;Choi, Il Yoon;Kim, Sun Hee;Um, Ju Hwan
    • Journal of the Korean Society for Railway
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    • v.18 no.5
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    • pp.447-456
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    • 2015
  • Continuous as well as discrete measurement of the track geometry based on a track trolley are investigated to enhance the efficiency of the trolley and to minimize the measurement errors. A new kinematic model based on the track coordinates involving transition and circular curves is developed to improve the accuracy of the measurement; a nonlinear Extended Kalman Filter (EKF) is employed to linearize the governing equations. The proposed model is verified with the ideal track geometry in terms of both discrete and continuous measurement. Comparison with the previous models is also made to prove the applicability of the kinematic model.

Generation of DEM by Correcting Blockage Areas on ASTER Stereo Images (ASTER 스테레오 영상의 폐색영역 보정에 의한 DEM 생성)

  • Lee, Jin-Duk;Park, Jin-Sung
    • Journal of the Korean Association of Geographic Information Studies
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    • v.13 no.1
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    • pp.155-163
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    • 2010
  • The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on-board the NASA's Terra spacecraft provides along-track digital stereo image data at 15m resolution with a base-height ratio 0.6. Automated stereocorrelation procedure was implemented using the ENVI 4.1 software to derive DEMs with $15m{\times}15m$ in 43km long and 50km wide area using the ASTER stereo images. The accuracy of DEMs was analyzed in comparison with those which were obtained from digital topographic maps of 1:25,000 scale. Results indicate that RMSE in elevation between ${\pm}7$ and ${\pm}20m$ could be achieved. Excluding cloud, water and building areas as the factors which make RMSE value exceeding 10m, the accuracy of DEMs showed RMSE of ${\pm}5.789m$. Therefore for the purpose of elevating accuracy of topographic information, we intended to detect the cloud areas and shadow areas by a landcover classification method, remove those areas on the ASTER DEM and then replace with those areas detached from the cartographic DEM by band math.

Analysis of Operational Availability under Changing Failure Rate and Supportability (무기체계의 고장률과 지원수준의 변화에 따른 운용가용도 변화 분석)

  • Tak, Jung Ho;Jung, Won
    • Journal of Applied Reliability
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    • v.18 no.1
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    • pp.1-7
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    • 2018
  • Purpose: Maintaining appropriate operational availability (Ao) is a key element of combat victory, but estimates vary according to estimation methods. The purpose of this study is to improve the accuracy of estimating operational availability by tracing the changes of the weapon system's failure rate, repair rate, and the level of logistic support. Methods: In order to track the change in the operating availability, the MDT (mean down time) is modeled by adding the repair time and the ALDT (administration and logistic delay time) to the service time. Results: Using the field data of the weapon system A operated by the ROKAF, the failure rate follows a non-homogeneous Poisson process that changes with time, and it is modeled considering the changing repair rate and the logistic support time. Conclusion: The accuracy of the analytical results was verified by comparing the actual operating data with the estimated availability. The results of this study can be used to track and evaluate the availability in a realistic situation where the failure rate and maintenance rate continuously change in operating environment.

TIME SERIES PREDICTION USING INCREMENTAL REGRESSION

  • Kim, Sung-Hyun;Lee, Yong-Mi;Jin, Long;Chai, Duck-Jin;Ryu, Keun-Ho
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.635-638
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    • 2006
  • Regression of conventional prediction techniques in data mining uses the model which is generated from the training step. This model is applied to new input data without any change. If this model is applied directly to time series, the rate of prediction accuracy will be decreased. This paper proposes an incremental regression for time series prediction like typhoon track prediction. This technique considers the characteristic of time series which may be changed over time. It is composed of two steps. The first step executes a fractional process for applying input data to the regression model. The second step updates the model by using its information as new data. Additionally, the model is maintained by only recent data in a queue. This approach has the following two advantages. It maintains the minimum information of the model by using a matrix, so space complexity is reduced. Moreover, it prevents the increment of error rate by updating the model over time. Accuracy rate of the proposed method is measured by RME(Relative Mean Error) and RMSE(Root Mean Square Error). The results of typhoon track prediction experiment are performed by the proposed technique IMLR(Incremental Multiple Linear Regression) is more efficient than those of MLR(Multiple Linear Regression) and SVR(Support Vector Regression).

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Visual Object Tracking Fusing CNN and Color Histogram based Tracker and Depth Estimation for Automatic Immersive Audio Mixing

  • Park, Sung-Jun;Islam, Md. Mahbubul;Baek, Joong-Hwan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.3
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    • pp.1121-1141
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    • 2020
  • We propose a robust visual object tracking algorithm fusing a convolutional neural network tracker trained offline from a large number of video repositories and a color histogram based tracker to track objects for mixing immersive audio. Our algorithm addresses the problem of occlusion and large movements of the CNN based GOTURN generic object tracker. The key idea is the offline training of a binary classifier with the color histogram similarity values estimated via both trackers used in this method to opt appropriate tracker for target tracking and update both trackers with the predicted bounding box position of the target to continue tracking. Furthermore, a histogram similarity constraint is applied before updating the trackers to maximize the tracking accuracy. Finally, we compute the depth(z) of the target object by one of the prominent unsupervised monocular depth estimation algorithms to ensure the necessary 3D position of the tracked object to mix the immersive audio into that object. Our proposed algorithm demonstrates about 2% improved accuracy over the outperforming GOTURN algorithm in the existing VOT2014 tracking benchmark. Additionally, our tracker also works well to track multiple objects utilizing the concept of single object tracker but no demonstrations on any MOT benchmark.

Accuracy Assessment of IGSO and GEO of BDS and QZSS Broadcast Ephemeris using MGEX Products

  • Son, Eunseong;Choi, Heonho;Joo, Jungmin;Heo, Moon Beom
    • Journal of Positioning, Navigation, and Timing
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    • v.9 no.4
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    • pp.347-356
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    • 2020
  • In this study, Inclined Geosynchronous Orbit (IGSO) and Geostationary Orbit (GEO) of BeiDou System (BDS) and Quasi Zenith Satellite System (QZSS) satellites positions and clock errors calculated by broadcast ephemeris and compared with Multi-GNSS Experiment (MGEX) products provided by five Analysis Centers (ACs). Root Mean Square Errors (RMSE) calculated for satellite position error. The IGSO results showed that 1.82 m, 0.91 m, 1.28 m in BDS and 1.34 m 0.36 m 0.49 m in QZSS and the GEO results showed that 2.85 m, 6.34 m, 6.42 m in BDS and 0.47 m, 4.79 m, 5.82 m in QZSS in the direction of radial, along-track and cross-track respectively. RMS calculated for satellite clock error. The IGSO result showed that 2.08 ns and 1.24 ns and the GEO result showed that 1.28 ns and 1.12 ns in BDS and QZSS respectively.

A Test Result on the Positional Accuracy of Kompsat-3A Beta Test Images

  • Oh, Jae Hong;Seo, Doo Chun;Lee, Chang No
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.2
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    • pp.133-142
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    • 2016
  • KOMPSAT-3A (KOrea Multi-Purpose SATellite-3A) was launched in March 25 2015 with specification of 0.5 meters resolution panchromatic and four 2.2 meters resolution multi spectral sensors in 12km swath width at nadir. To better understand KOMPSAT-3A positional accuracy, this paper reports a test result on the accuracy of recently released KOMPSAT-3A beta test images. A number of ground points were acquired from 1:1,000 digital topographic maps over the target area for the accuracy validation. First, the original RPCs (Rational Polynomial Coefficients) were validated without any GCPs (Ground Control Points). Then we continued the test by modeling the errors in the image space using shift-only, shift and drift, and the affine model. Ground restitution accuracy was also analyzed even though the across track image pairs do not have optimal convergence angle. The experimental results showed that the shift and drift-based RPCs correction was optimal showing comparable accuracy of less than 1.5 pixels with less GCPs compared to the affine model.

Topographic Phase Correction of MAl (Multiple Aperture SAR Interferometry) Interferogram (MAI (Multiple Aperture SAR Interferometry) 간섭도의 지형위상보정)

  • Jung, Hyung-Sup;Lu, Zhong
    • Korean Journal of Remote Sensing
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    • v.27 no.2
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    • pp.171-180
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    • 2011
  • MAI (multiple aperture SAR interferometry) method has been recently developed to improve the measurement accuracy of along-track surface deformation. By means of split-beam SAR processing, this novel technique produces forward- and backward-looking interferograms, which are combined to generate an MAI interferogram. The along-track surface deformation can then be derived from the MAI interferogram. The achieved accuracy of the along-track surface deformation is approximately 8 cm for interferograms with a coherence of 0.6. It is commonly recognized that the topographic phase on an MAI interferogram can be ignored. However, in this paper, we have generated an MAI interferogram from an ALOS P ALSAR interferometric pair spanning the 2010 Haiti earthquake, and shown that the topographic phase distortion on the MAI interferogram can reach to about $3.45{\times}10^{-4}$ rad./m. This distortion corresponds to an along-track surface deformation of about 98 cm. We have proposed an efficient method to remove the topographic phase distortion. After correcting the distortion, the topographic phase distortion on the MAI interferogram is reduced to about $7.82{\times}10^{-6}$ rad./m. This means that the proposed method can effectively remove the topographic distortion on the MAI interferogram to improve along-track surface deformation measurement.

Wheel tread defect detection for high-speed trains using FBG-based online monitoring techniques

  • Liu, Xiao-Zhou;Ni, Yi-Qing
    • Smart Structures and Systems
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    • v.21 no.5
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    • pp.687-694
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    • 2018
  • The problem of wheel tread defects has become a major challenge for the health management of high-speed rail as a wheel defect with small radius deviation may suffice to give rise to severe damage on both the train bogie components and the track structure when a train runs at high speeds. It is thus highly desirable to detect the defects soon after their occurrences and then conduct wheel turning for the defective wheelsets. Online wheel condition monitoring using wheel impact load detector (WILD) can be an effective solution, since it can assess the wheel condition and detect potential defects during train passage. This study aims to develop an FBG-based track-side wheel condition monitoring method for the detection of wheel tread defects. The track-side sensing system uses two FBG strain gauge arrays mounted on the rail foot, measuring the dynamic strains of the paired rails excited by passing wheelsets. Each FBG array has a length of about 3 m, slightly longer than the wheel circumference to ensure a full coverage for the detection of any potential defect on the tread. A defect detection algorithm is developed for using the online-monitored rail responses to identify the potential wheel tread defects. This algorithm consists of three steps: 1) strain data pre-processing by using a data smoothing technique to remove the trends; 2) diagnosis of novel responses by outlier analysis for the normalized data; and 3) local defect identification by a refined analysis on the novel responses extracted in Step 2. To verify the proposed method, a field test was conducted using a test train incorporating defective wheels. The train ran at different speeds on an instrumented track with the purpose of wheel condition monitoring. By using the proposed method to process the monitoring data, all the defects were identified and the results agreed well with those from the static inspection of the wheelsets in the depot. A comparison is also drawn for the detection accuracy under different running speeds of the test train, and the results show that the proposed method can achieve a satisfactory accuracy in wheel defect detection when the train runs at a speed higher than 30 kph. Some minor defects with a depth of 0.05 mm~0.06 mm are also successfully detected.