• 제목/요약/키워드: GPS position correction

검색결과 84건 처리시간 0.021초

무한원점과 단일 비젼 시스템을 이용한 자율주행을 위한 실시간 GPS 위치 데이터 보정 (Real time GPS position data correction using the vanishing point and a monocular vision system for autonomous land navigation)

  • 정준익;노도환
    • 대한전자공학회논문지SP
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    • 제41권6호
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    • pp.187-193
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    • 2004
  • 본 논문에서는 무한원점의 특성과 단일 비젼 시스템을 이용하여 자율 주행을 위한 GPS 위치 데이터 보정법을 제안한다. 실제 도로를 약 60 km의 거리를 주행하며 제안한 방법에 적용한 주행실험 결과를 제시하였다. 제안하는 방법은 직선도로의 환경에서 GPS 위치 오차론 최소 약 53% 이상 감소시켰고, 거리로는 0.5m 이내로 추정되었다. 그러나 곡선도로와 직선이 아닌 산악도로 등의 도로환경에서 정확도를 판별하기 어려운 관계로 직선도로에서의 오차만을 제시하였다.

카메라와 무한원점을 이용한 주행중 실시간 GPS 위치 보정 (Real time GPS position correction using a camera and the vanishing point when a vehicle runs)

  • 김보성;정준익;노도환
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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    • pp.508-510
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    • 2004
  • In this paper, we proposed the GPS position data correction method for autonomous land navigation using vanishing point property and a monocular vision system. Simulations are carried out over driving distances of approximately 60 km on the basis of realistic road data. In straight road, the proposed method reduces GPS position error to minimum more than 63% and positioning errors within less than 0.5m are observed. However, the average accuracy of the method is not presented. because it is difficult to estimate it in curve road or other road environments.

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Performance Analysis of Low-Order Surface Methods for Compact Network RTK: Case Study

  • Song, Junesol;Park, Byungwoon;Kee, Changdon
    • Journal of Positioning, Navigation, and Timing
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    • 제4권1호
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    • pp.33-41
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    • 2015
  • Compact Network Real-Time Kinematic (RTK) is a method that combines compact RTK and network RTK, and it can effectively reduce the time and spatial de-correlation errors. A network RTK user receives multiple correction information generated from reference stations that constitute a network, calculates correction information that is appropriate for one's own position through a proper combination method, and uses the information for the estimation of the position. This combination method is classified depending on the method for modeling the GPS error elements included in correction information, and the user position accuracy is affected by the accuracy of this modeling. Among the GPS error elements included in correction information, tropospheric delay is generally eliminated using a tropospheric model, and a combination method is then applied. In the case of a tropospheric model, the estimation accuracy varies depending on the meteorological condition, and thus eliminating the tropospheric delay of correction information using a tropospheric model is limited to a certain extent. In this study, correction information modeling accuracy performances were compared focusing on the Low-Order Surface Model (LSM), which models the GPS error elements included in correction information using a low-order surface, and a modified LSM method that considers tropospheric delay characteristics depending on altitude. Both of the two methods model GPS error elements in relation to altitude, but the second method reflects the characteristics of actual tropospheric delay depending on altitude. In this study, the final residual errors of user measurements were compared and analyzed using the correction information generated by the various methods mentioned above. For the performance comparison and analysis, various GPS actual measurement data were collected. The results indicated that the modified LSM method that considers actual tropospheric characteristics showed improved performance in terms of user measurement residual error and position domain residual error.

AVM 정지선인지기반 도심환경 종방향 측위보정 알고리즘 (AVM Stop-line Detection based Longitudinal Position Correction Algorithm for Automated Driving on Urban Roads)

  • 김종호;이현성;유진수;이경수
    • 자동차안전학회지
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    • 제12권2호
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    • pp.33-39
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    • 2020
  • This paper presents an Around View Monitoring (AVM) stop-line detection based longitudinal position correction algorithm for automated driving on urban roads. Poor positioning accuracy of low-cost GPS has many problems for precise path tracking. Therefore, this study aims to improve the longitudinal positioning accuracy of low-cost GPS. The algorithm has three main processes. The first process is a stop-line detection. In this process, the stop-line is detected using Hough Transform from the AVM camera. The second process is a map matching. In the map matching process, to find the corrected vehicle position, the detected line is matched to the stop-line of the HD map using the Iterative Closest Point (ICP) method. Third, longitudinal position of low-cost GPS is updated using a corrected vehicle position with Kalman Filter. The proposed algorithm is implemented in the Robot Operating System (ROS) environment and verified on the actual urban road driving data. Compared to low-cost GPS only, Test results show the longitudinal localization performance was improved.

도심 자율주행을 위한 라이다 정지 장애물 지도 기반 위치 보정 알고리즘 (LiDAR Static Obstacle Map based Position Correction Algorithm for Urban Autonomous Driving)

  • 노한석;이현성;이경수
    • 자동차안전학회지
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    • 제14권2호
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    • pp.39-44
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    • 2022
  • This paper presents LiDAR static obstacle map based vehicle position correction algorithm for urban autonomous driving. Real Time Kinematic (RTK) GPS is commonly used in highway automated vehicle systems. For urban automated vehicle systems, RTK GPS have some trouble in shaded area. Therefore, this paper represents a method to estimate the position of the host vehicle using AVM camera, front camera, LiDAR and low-cost GPS based on Extended Kalman Filter (EKF). Static obstacle map (STOM) is constructed only with static object based on Bayesian rule. To run the algorithm, HD map and Static obstacle reference map (STORM) must be prepared in advance. STORM is constructed by accumulating and voxelizing the static obstacle map (STOM). The algorithm consists of three main process. The first process is to acquire sensor data from low-cost GPS, AVM camera, front camera, and LiDAR. Second, low-cost GPS data is used to define initial point. Third, AVM camera, front camera, LiDAR point cloud matching to HD map and STORM is conducted using Normal Distribution Transformation (NDT) method. Third, position of the host vehicle position is corrected based on the Extended Kalman Filter (EKF).The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment and showed better performance than only lane-detection algorithm. It is expected to be more robust and accurate than raw lidar point cloud matching algorithm in autonomous driving.

위성배치정보와 보정정보 맵핑 알고리즘을 이용한 저가형 GPS 수신기의 DGPS 서비스 적용 방안 연구 (A Study on the DGPS Service Utilization for the Low-cost GPS Receiver Module Based on the Correction Projection Algorithm)

  • 박병운;윤동환
    • 한국항해항만학회지
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    • 제38권2호
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    • pp.121-126
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    • 2014
  • 본 논문은 저가형 GPS 수신 모듈에 DGPS 서비스를 적용하기 위한 방안으로 NMEA GPGSV 데이터의 위성 배치 정보에 포함된 위성 앙각과 방위각으로 관측 행렬을 구성한 후, 거리기반 보정정보를 위치영역으로 투영하여 기 산출된 위치 오차 벡터를 수정하는 방안을 제시하였다. 저가형 수신기인 U-blox LEA-5H 모델의 출력 데이터에 제안한 알고리즘을 적용한 결과 주 활동 시간인 낮 시간에 수평 오차 RMS를 1.8m에서 1m 이내로 줄였으며, 수직 정확도는 RMS 5.8m에서 1.4m로 75% 향상시킴을 확인하였다. 본 논문에서 제안하는 방식은 하드웨어의 변경없이 소프트웨어만으로 저가형 GPS의 성능을 DGPS 수준으로 향상시키는 기법이므로, 소비자와 제조사의 부담을 경감시켜 향후 제공될 고정밀 측위 서비스 인프라의 활성화에 기여할 수 있을 것으로 기대된다.

RLSLF 방식을 적용하여 저가의 GPS 모듈로 구성된 DGPS 시스템의 효율적인 구현 (The Efficient Implementation of DGPS System with Low Cost GPS modules Using a Recursive Least Squares Lattice Filtering Method)

  • 이창복;주세철;김기두;김영범
    • 전자공학회논문지B
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    • 제32B권10호
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    • pp.1338-1346
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    • 1995
  • In this paper, we suggest the implementation of a DGPS system using two low cost commercial C/A code GPS modules and modems and its efficient operational techniques to provide DGPS service which guarantees the position accuracy of better than 10 meters for more users. The proposed DGPS system can be implemented easil at low cost because it needs a GPS module and a modem for each reference station and user. The reference station makes plans of the receiving schedule from the satellite set at each period and then provides the correction data for various satellite sets in a period. The main contribution of this paper is that users can utilize the correction data continuously and efficiently through the recursive least squares lattice filtering method. Experimental results show the position accuracy of better than 10 meters using the suggested DGPS system in almost real time.

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차량 추적 시스템에서 차분기법을 이용한 정밀도 향상에 관한 연구 (Improvement on the Vehicle Positioning Accuracy Using Differential Method for Vehicle Tracking)

  • 장경일;이원우;길계환;김용윤;황춘식
    • 전자공학회논문지S
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    • 제34S권1호
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    • pp.16-25
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    • 1997
  • This paper shows the development of the high accuracy vehicle positioning algorithm using the differential technique in vehicle tracking systems form the existing vehicle position which is acquired from the global positioning system (GPS). The control center receives the satellite ephemerise data and pseudorange correction from the reference station, and vehicle position from the moving vehicle. The pseudorange is calculated with the satellite position and the vehicle position, and corrected by pseudorange correction. Using this corrected pseudorange and kalman filter, more improved vehicle positioning data were obtained.

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Reduction of GPS Latency Using RTK GPS/GNSS Correction and Map Matching in a Car NavigationSystem

  • Kim, Hyo Joong;Lee, Won Hee;Yu, Ki Yun
    • 대한공간정보학회지
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    • 제24권2호
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    • pp.37-46
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    • 2016
  • The difference between definition time of GPS (Global Positioning System) position data and actual display time of car positions on a map could reduce the accuracy of car positions displayed in PND (Portable Navigation Device)-type CNS (Car Navigation System). Due to the time difference, the position of the car displayed on the map is not its current position, so an improved method to fix these problems is required. It is expected that a method that uses predicted future positionsto compensate for the delay caused by processing and display of the received GPS signals could mitigate these problems. Therefore, in this study an analysis was conducted to correct late processing problems of map positions by mapmatching using a Kalman filter with only GPS position data and a RRF (Road Reduction Filter) technique in a light-weight CNS. The effects on routing services are examined by analyzing differences that are decomposed into along and across the road elements relative to the direction of advancing car. The results indicate that it is possible to improve the positional accuracy in the along-the-road direction of a light-weight CNS device that uses only GPS position data, by applying a Kalman filter and RRF.

Assessment of Position Degradation Due to Intermittent Broadcast of RTK MSM Correction Under Various Conditions

  • Yoon, Hyo Jung;Lim, Cheol soon;Park, Byungwoon
    • Journal of Positioning, Navigation, and Timing
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    • 제9권3호
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    • pp.237-248
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    • 2020
  • GNSS has been evolving dramatically in recent years. There are currently 6 GNSS (4 GNSS, AND 2 RNSS) constellations, which are GPS (USA), GLONASS (Russia), BeiDou (China), Galileo (EU), QZSS (Japan), and IRNSS (India). The Number of navigation satellites is expected to be over 150 by 2020. As the number of both constellations and satellites used for the improvement of positioning performance, high accuracy, and robustness of precise positioning is more promising. However, a large amount of the correction messages is required to support the augmentation system for the available satellites of all the constellations. Since bandwidth for the correction messages is generally limited, sending or scheduling the correction messages might be a critical issue in the near future. In this study, we analyze the relationship between the size of the bandwidth and Real-Time Kinematics (RTK) performance. Multiple Signal Messages (MSM), the only Radio Technical Commission for Maritimes (RTCM) message that supports multi-constellation GNSS, has been used for this assessment. Instead of the conventional method that broadcasts all the messages at the same time, we assign the MSM broadcasting interval for each constellation in 5 seconds. An open sky static and dynamic test for this study was conducted on the roof of Sejong University. Our results show that the RTK fixed position accuracy is not affected by the 5-second interval corrections, but the ambiguity fixing rate is degraded for poor DOP cases when RTK correction are transmitted intermittently.