• Title/Summary/Keyword: 위치추정 알고리즘

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Multiple Reference Network Data Processing Algorithms for High Precision of Long-Baseline Kinematic Positioning by GPS/INS Integration (GPS/INS 통합에 의한 고정밀 장기선 동적 측위를 위한 다중 기준국 네트워크 데이터 처리 알고리즘)

  • Lee, Hung-Kyu
    • 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.

The study of improving the performance of lower direction finding ability due to the interfered phase difference of circular array Antennas (원형배열안테나의 위상간섭에 의한 방향탐지 성능저하 개선연구)

  • Chung, Jae-Woo;Kim, Young-Kil
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2010.05a
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    • pp.535-539
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    • 2010
  • This paper include to study DoA(Direction of Arrival) for radio collection and monitoring system. The direction finding calculated by applying the CVDF (Correlation Vector Direction Finding) algorithm for the five circular dipole antenna over V / UHF band. To improve the accuracy of direction finding by applying CVDF algorithm needs to obtain ideal phase difference each antennas. However, a circular array antenna phase difference pattern may be distorted on a specific frequency band or to particular direction. The effect of installing each array antennas circularly and the effect of the interference of center pole (located in the center of a circular array antenna mount) may make the distortion of phase pattern. If you use an active antenna instead of passive antenna to obtain good sensitivity, you would measure the more distortion. This paper propose how to change combination of antennas to measure the phase in real-time and how to use antenna beam patterns for minimizing the degradation phenomena at applying simple CVDF algorithm and increasing the direction finding capability.

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Algorithm Development for Extract O/D of Air Passenger via Mobile Telecommunication Bigdata (모바일 통신 빅데이터 기반 항공교통이용자 O/D 추출 알고리즘 연구)

  • Bumchul Cho;Kihun Kwon
    • The Journal of Bigdata
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    • v.8 no.2
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    • pp.1-13
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    • 2023
  • Current analysis of air passengers mainly relies on statistical methods, but there are limitations in analyzing detailed aspects such as travel routes, number of regional passengers and airport access times. However, with the advancement of big data technology and revised three data acts, big data-based transportation analysis has become more active. Mobile communication data, which can precisely track the location of mobile phone terminals, can serve as valuable analytical data for transportation analysis. In this paper, we propose a air passenger Origin/Destination (O/D) extraction algorithm based on mobile communication data that overcomes the limitations of existing air transportation user analysis methods. The algorithm involves setting airport signal detection zones at each airport and extracting air passenger based on their base station connection history within these zones. By analyzing the base station connection data along the passenger's origin-destination paths, we estimate the entire travel route. For this paper, we extracted O/D information for both domestic and international air passengers at all domestic airports from January 2019 to December 2020. To compensate for errors caused by mobile communication service provider market shares, we applied a adjustment to correct the travel volume at a nationwide citizen level. Furthermore correlation analysis was performed on O/D data and aviation statistics data for air traffic users based on mobile communication data to verify the extracted data. Through this, there is a difference in the total amount (4.1 for domestic and 4.6 for international), but the correlation is high at 0.99, which is judged to be useful. The proposed algorithm in this paper enables a comprehensive and detailed analysis of air transportation users' travel behavior, regional/age group ratios, and can be utilized in various fields such as formulating airport-related policies and conducting regional market analysis.

Analysis Method for Full-length LiDAR Waveforms (라이다 파장 분석 방법론에 대한 연구)

  • Jung, Myung-Hee;Yun, Eui-Jung;Kim, Cheon-Shik
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.44 no.4 s.316
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    • pp.28-35
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    • 2007
  • Airbone laser altimeters have been utilized for 3D topographic mapping of the earth, moon, and planets with high resolution and accuracy, which is a rapidly growing remote sensing technique that measures the round-trip time emitted laser pulse to determine the topography. The traveling time from the laser scanner to the Earth's surface and back is directly related to the distance of the sensor to the ground. When there are several objects within the travel path of the laser pulse, the reflected laser pluses are distorted by surface variation within the footprint, generating multiple echoes because each target transforms the emitted pulse. The shapes of the received waveforms also contain important information about surface roughness, slope and reflectivity. Waveform processing algorithms parameterize and model the return signal resulting from the interaction of the transmitted laser pulse with the surface. Each of the multiple targets within the footprint can be identified. Assuming each response is gaussian, returns are modeled as a mixture gaussian distribution. Then, the parameters of the model are estimated by LMS Method or EM algorithm However, each response actually shows the skewness in the right side with the slowly decaying tail. For the application to require more accurate analysis, the tail information is to be quantified by an approach to decompose the tail. One method to handle with this problem is proposed in this study.

A Study on the Cycle-slip Detection for GPS Carrier-phase based Positioning of Land Vehicle (차량 환경에서 GPS 반송파 기반 위치 결정을 위한 반송파 불연속 측정치 검출에 대한 연구)

  • Kim, Youn-Sil;Song, Jun-Ssol;Yun, Ho;Kee, Chang-Don
    • Journal of Advanced Navigation Technology
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    • v.17 no.6
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    • pp.593-599
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    • 2013
  • In this paper, the GPS cycle-slip detection for carrier-phase based positioning of land vehicle is presented. For the carrier phase based positioning, cycle-slip detection is necessary to get the reliability of positioning result. There exists many cycle-slip detection algorithms, but we detect the cycle-slip by using the monitoring value which is defined as residual between the carrier phase measurement and estimated value from low-cost inertial sensor. To achieve goal of paper, low-cost cycle-slip detection system, permissible specification region of inertial sensor is derived. By using the result of permissible region, appropriate inertial sensor of cycle-slip detection can be decided, proper cost and proper specification. To verify the result of this paper, we conduct the rate table test. As a result, required cycle-slip detection performance is satisfied conservatively.

Effective Morphological Layer Segmentation Based on Edge Information for Screen Image Coding (스크린 이미지 부호화를 위한 에지 정보 기반의 효과적인 형태학적 레이어 분할)

  • Park, Sang-Hyo;Lee, Si-Woong
    • The Journal of the Korea Contents Association
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    • v.13 no.12
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    • pp.38-47
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    • 2013
  • An image coding based on MRC model, a kind of multi-layer image model, first segments a screen image into foreground, mask, and background layers, and then compresses each layer using a codec that is suitable to the layer. The mask layer defines the position of foreground regions such as textual and graphical contents. The colour signal of the foreground (background) region is saved in the foreground (background) layer. The mask layer which contains the segmentation result of foreground and background regions is of importance since its accuracy directly affects the overall coding performance of the codec. This paper proposes a new layer segmentation algorithm for the MRC based image coding. The proposed method extracts text pixels from the background using morphological top hat filtering. The application of white or black top hat transformation to local blocks is controlled by the information of relative brightness of text compared to the background. In the proposed method, the boundary information of text that is extracted from the edge map of the block is used for the robust decision on the relative brightness of text. Simulation results show that the proposed method is superior to the conventional methods.

Attention based Feature-Fusion Network for 3D Object Detection (3차원 객체 탐지를 위한 어텐션 기반 특징 융합 네트워크)

  • Sang-Hyun Ryoo;Dae-Yeol Kang;Seung-Jun Hwang;Sung-Jun Park;Joong-Hwan Baek
    • Journal of Advanced Navigation Technology
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    • v.27 no.2
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    • pp.190-196
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    • 2023
  • Recently, following the development of LIDAR technology which can detect distance from the object, the interest for LIDAR based 3D object detection network is getting higher. Previous networks generate inaccurate localization results due to spatial information loss during voxelization and downsampling. In this study, we propose an attention-based convergence method and a camera-LIDAR convergence system to acquire high-level features and high positional accuracy. First, by introducing the attention method into the Voxel-RCNN structure, which is a grid-based 3D object detection network, the multi-scale sparse 3D convolution feature is effectively fused to improve the performance of 3D object detection. Additionally, we propose the late-fusion mechanism for fusing outcomes in 3D object detection network and 2D object detection network to delete false positive. Comparative experiments with existing algorithms are performed using the KITTI data set, which is widely used in the field of autonomous driving. The proposed method showed performance improvement in both 2D object detection on BEV and 3D object detection. In particular, the precision was improved by about 0.54% for the car moderate class compared to Voxel-RCNN.

A Real-Time Head Tracking Algorithm Using Mean-Shift Color Convergence and Shape Based Refinement (Mean-Shift의 색 수렴성과 모양 기반의 재조정을 이용한 실시간 머리 추적 알고리즘)

  • Jeong Dong-Gil;Kang Dong-Goo;Yang Yu Kyung;Ra Jong Beom
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.6
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    • pp.1-8
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    • 2005
  • In this paper, we propose a two-stage head tracking algorithm adequate for real-time active camera system having pan-tilt-zoom functions. In the color convergence stage, we first assume that the shape of a head is an ellipse and its model color histogram is acquired in advance. Then, the min-shift method is applied to roughly estimate a target position by examining the histogram similarity of the model and a candidate ellipse. To reflect the temporal change of object color and enhance the reliability of mean-shift based tracking, the target histogram obtained in the previous frame is considered to update the model histogram. In the updating process, to alleviate error-accumulation due to outliers in the target ellipse of the previous frame, the target histogram in the previous frame is obtained within an ellipse adaptively shrunken on the basis of the model histogram. In addition, to enhance tracking reliability further, we set the initial position closer to the true position by compensating the global motion, which is rapidly estimated on the basis of two 1-D projection datasets. In the subsequent stage, we refine the position and size of the ellipse obtained in the first stage by using shape information. Here, we define a robust shape-similarity function based on the gradient direction. Extensive experimental results proved that the proposed algorithm performs head hacking well, even when a person moves fast, the head size changes drastically, or the background has many clusters and distracting colors. Also, the propose algorithm can perform tracking with the processing speed of about 30 fps on a standard PC.

Comparison between Uncertainties of Cultivar Parameter Estimates Obtained Using Error Calculation Methods for Forage Rice Cultivars (오차 계산 방식에 따른 사료용 벼 품종의 품종모수 추정치 불확도 비교)

  • Young Sang Joh;Shinwoo Hyun;Kwang Soo Kim
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.3
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    • pp.129-141
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    • 2023
  • Crop models have been used to predict yield under diverse environmental and cultivation conditions, which can be used to support decisions on the management of forage crop. Cultivar parameters are one of required inputs to crop models in order to represent genetic properties for a given forage cultivar. The objectives of this study were to compare calibration and ensemble approaches in order to minimize the uncertainty of crop yield estimates using the SIMPLE crop model. Cultivar parameters were calibrated using Log-likelihood (LL) and Generic Composite Similarity Measure (GCSM) as an objective function for Metropolis-Hastings (MH) algorithm. In total, 20 sets of cultivar parameters were generated for each method. Two types of ensemble approach. First type of ensemble approach was the average of model outputs (Eem), using individual parameters. The second ensemble approach was model output (Epm) of cultivar parameter obtained by averaging given 20 sets of parameters. Comparison was done for each cultivar and for each error calculation methods. 'Jowoo' and 'Yeongwoo', which are forage rice cultivars used in Korea, were subject to the parameter calibration. Yield data were obtained from experiment fields at Suwon, Jeonju, Naju and I ksan. Data for 2013, 2014 and 2016 were used for parameter calibration. For validation, yield data reported from 2016 to 2018 at Suwon was used. Initial calibration indicated that genetic coefficients obtained by LL were distributed in a narrower range than coefficients obtained by GCSM. A two-sample t-test was performed to compare between different methods of ensemble approaches and no significant difference was found between them. Uncertainty of GCSM can be neutralized by adjusting the acceptance probability. The other ensemble method (Epm) indicates that the uncertainty can be reduced with less computation using ensemble approach.

Model-Based Plane Detection in Disparity Space Using Surface Partitioning (표면분할을 이용한 시차공간상에서의 모델 기반 평면검출)

  • Ha, Hong-joon;Lee, Chang-hun
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.10
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    • pp.465-472
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    • 2015
  • We propose a novel plane detection in disparity space and evaluate its performance. Our method simplifies and makes scenes in disparity space easily dealt with by approximating various surfaces as planes. Moreover, the approximated planes can be represented in the same size as in the real world, and can be employed for obstacle detection and camera pose estimation. Using a stereo matching technique, our method first creates a disparity image which consists of binocular disparity values at xy-coordinates in the image. Slants of disparity values are estimated by exploiting a line simplification algorithm which allows our method to reflect global changes against x or y axis. According to pairs of x and y slants, we label the disparity image. 4-connected disparities with the same label are grouped, on which least squared model estimates plane parameters. N plane models with the largest group of disparity values which satisfy their plane parameters are chosen. We quantitatively and qualitatively evaluate our plane detection. The result shows 97.9%와 86.6% of quality in our experiment respectively on cones and cylinders. Proposed method excellently extracts planes from Middlebury and KITTI dataset which are typically used for evaluation of stereo matching algorithms.