• Title/Summary/Keyword: distance accuracy

Search Result 1,691, Processing Time 0.025 seconds

Position error estimation of sub-array in passive ranging sonar based on a genetic algorithm (유전자 알고리즘 기반의 수동측거소나 부배열 위치오차 추정)

  • Eom, Min-Jeong;Kim, Do-Young;Park, Gyu-Tae;Shin, Kee-Cheol;Oh, Se-Hyun
    • The Journal of the Acoustical Society of Korea
    • /
    • v.38 no.6
    • /
    • pp.630-636
    • /
    • 2019
  • Passive Ranging Sonar (PRS) is a type of passive sonar consisting of three sub-array on the port and starboard, and has a characteristic of detecting a target and calculating a bearing and a distance. The bearing and distance calculation requires physical sub-array position information, and the bearing and distance accuracy performance are deteriorated when the position information of the sub-array is inaccurate. In particular, it has a greater impact on distance accuracy performance using plus value of two time-delay than a bearing using average value of two time-delay. In order to improve this, a study on sub-array position error estimation and error compensation is needed. In this paper, We estimate the sub-array position error based on enetic algorithm, an optimization search technique, and propose a method to improve the performance of distance accuracy by compensating the time delay error caused by the position error. In addition, we will verify the proposed algorithm and its performance using the sea-going data.

Capturing Distance Parameters Using a Laser Sensor in a Stereoscopic 3D Camera Rig System

  • Chung, Wan-Young;Ilham, Julian;Kim, Jong-Jin
    • Journal of Sensor Science and Technology
    • /
    • v.22 no.6
    • /
    • pp.387-392
    • /
    • 2013
  • Camera rigs for shooting 3D video are classified as manual, motorized, or fully automatic. Even in an automatic camera rig, the process of Stereoscopic 3D (S3D) video capture is very complex and time-consuming. One of the key time-consuming operations is capturing the distance parameters, which are near distance, far distance, and convergence distance. Traditionally these distances are measured by tape measure or triangular indirect measurement methods. These two methods consume a long time for every scene in shot. In our study, a compact laser distance sensing system with long range distance sensitivity is developed. The system is small enough to be installed on top of a camera and the measuring accuracy is within 2% even at a range of 50 m. The shooting time of an automatic camera rig equipped with the laser distance sensing system can be reduced significantly to less than a minute.

A Study for Improving the Positioning Accuracy of DGPS Based on Multi-Reference Stations by Applying Exponential Modeling on Pseudorange Corrections

  • Kim, Koon-Tack;Park, Kwan-Dong;Lee, Eunsung;Heo, Moon Beom
    • Journal of Positioning, Navigation, and Timing
    • /
    • v.2 no.1
    • /
    • pp.9-17
    • /
    • 2013
  • In this paper, a pseudorange correction regeneration algorithm was developed to improve the positioning accuracy of DGPS using multi-reference stations, and the optimal minimum number of reference sites was determined by trying out different numbers of reference. This research was conducted using from two to five sites, and positioning errors of less than 1 m were obtained when pseudorange corrections are collected from at least four reference stations and interpolated as the pseudorange correction at the rover. After determining the optimal minimum number of reference stations, the pseudorange correction regeneration algorithm developed was tested by comparison with the performance of other algorithms. Our approach was developed based on an exponential model. If pseudorange corrections are regenerated using an exponential model, the effect of a small difference in the baseline distance can be enlarged. Therefore, weights can be applied sensitively even when the baseline distance differs by a small amount. Also weights on the baseline distance were applied differently by assigning weights depending on the difference of the longest and shortest baselines. Through this method, the positioning accuracy improved by 19% compared to the result of previous studies.

Classification for landfast sea ice types in Greenland with texture analysis images (텍스쳐 이미지를 이용한 그린란드 정착빙의 분류)

  • Hwang, Do-Hyun;Hwang, Byong-Jun;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.8 no.4
    • /
    • pp.589-593
    • /
    • 2013
  • Remote sensing of SAR images is suitable for sea ice observations to obtain the sea ice data if clouds or weather conditions change. There are various types of sea ice, classification results can be seen more easily to detect the change by types of sea ice. In this study, we classified the image by supervised classification method, which is minimum distance was used. Also, we compared the overall accuracy when compared to the results with classification result of SAR images and the result of texture images. When using Radarsat-2 texture images, the overall accuracy was the highest, generally, when using the SAR images had higher overall accuracy.

The Evaluation of Distance Accuracy and The Test Target Manufacturing of A Terrestrial Laser Scanner (TLS용 테스트 타깃의 개발과 거리측정 정확도 검증)

  • Lee, In-Su;Tcha, Dek-Kie;Suh, Ho-Suhng
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.30 no.3
    • /
    • pp.279-285
    • /
    • 2012
  • Albeit the use of terrestrial 3D laser scanner (TLS) in the parts of landslide monitoring, cultural heritage documentation, civil engineering, urban engineering, etc. is increasing more and more, there is no international standardization regulation about the accuracy evaluation of the geometric element values, target, instrument calibration and test procedures, etc. Accordingly, this study deals with the manufacturing of TLS performance test target and the evaluation of TLS distance measurement and shows its suitability as the test target.

Map Error Measuring Mechanism Design and Algorithm Robust to Lidar Sparsity (라이다 점군 밀도에 강인한 맵 오차 측정 기구 설계 및 알고리즘)

  • Jung, Sangwoo;Jung, Minwoo;Kim, Ayoung
    • The Journal of Korea Robotics Society
    • /
    • v.16 no.3
    • /
    • pp.189-198
    • /
    • 2021
  • In this paper, we introduce the software/hardware system that can reliably calculate the distance from sensor to the model regardless of point cloud density. As the 3d point cloud map is widely adopted for SLAM and computer vision, the accuracy of point cloud map is of great importance. However, the 3D point cloud map obtained from Lidar may reveal different point cloud density depending on the choice of sensor, measurement distance and the object shape. Currently, when measuring map accuracy, high reflective bands are used to generate specific points in point cloud map where distances are measured manually. This manual process is time and labor consuming being highly affected by Lidar sparsity level. To overcome these problems, this paper presents a hardware design that leverage high intensity point from three planar surface. Furthermore, by calculating distance from sensor to the device, we verified that the automated method is much faster than the manual procedure and robust to sparsity by testing with RGB-D camera and Lidar. As will be shown, the system performance is not limited to indoor environment by progressing the experiment using Lidar sensor at outdoor environment.

A Study on the Improvement of Orthophoto Accuracy According to the Flight Photographing Technique and GCP Location Distance in Orthophoto Generation Using UAV (무인항공기를 활용한 정사영상제작에서 지상기준점 위치간격과 비행촬영기법에 따른 정사영상정확도 향상에 관한 연구)

  • Yun, Bu-Yeol;Yoon, Won-Sub
    • Journal of the Korean Society of Industry Convergence
    • /
    • v.21 no.6
    • /
    • pp.345-354
    • /
    • 2018
  • It is conservative to say that lots of research is performed as measures to use UAV for application to the rapid spatial information and its application is faced with settlement stage to some extent. In addition, Korea Land and Geospatial Informatix Corporation autonomously produces work regulation which is applied to every kind of orders and National Geographic Information Institute (2018) has notified public surveying work instructions about unmanned aerial device for the rapid spatial information construction. The results acquired by UAV are comprised of contents about accuracy improvements for the orthophoto when reviewing pertinent regulations. The results acquired by UAV are comprised of contents about accuracy improvements for the orthophoto when reviewing pertinent regulations. As a result, it is known that error amount has been sharply increased from 400m separation distance, and this study proposes that cross flight is able to reduce irregular error occurrence as measures to acquire stable results.

GCP Placement Methods for Improving the Accuracy of Shoreline Extraction in Coastal Video Monitoring

  • Changyul Lee;Kideok Do;Inho Kim;Sungyeol Chang
    • Journal of Ocean Engineering and Technology
    • /
    • v.38 no.4
    • /
    • pp.174-186
    • /
    • 2024
  • In coastal video monitoring, the direct linear transform (DLT) method with ground control points (GCPs) is commonly used for geo-rectification. However, current practices often overlook the impact of GCP quantity, arrangement, and the geographical characteristics of beaches. To address this, we designed scenarios at Chuam Beach to evaluate how factors such as the distance from the camera to GCPs, the number of GCPs, and the height of each point affect the DLT method. Accuracy was assessed by calculating the root mean square error of the distance errors between the actual GCP coordinates and the image coordinates for each setting. This analysis aims to propose an optimal GCP placement method. Our results show that placing GCPs within 200 m of the camera ensures high accuracy with few points, whereas positioning them at strategic heights enhances shoreline extraction. However, since only fixed cameras were used in this study, factors like varying heights, orientations, and resolutions could not be considered. Based on data from a single location, we propose an optimal method for GCP placement that takes into account distance, number, and height using the DLT method.

Word sense disambiguation using dynamic sized context and distance weighting (가변 크기 문맥과 거리가중치를 이용한 동형이의어 중의성 해소)

  • Lee, Hyun Ah
    • Journal of Advanced Marine Engineering and Technology
    • /
    • v.38 no.4
    • /
    • pp.444-450
    • /
    • 2014
  • Most researches on word sense disambiguation have used static sized context regardless of sentence patterns. This paper proposes to use dynamic sized context considering sentence patterns and distance between words for word sense disambiguation. We evaluated our system 12 words in 32,735sentences with Sejong POS and sense tagged corpus, and dynamic sized context showed 92.2% average accuracy for predicates, which is better than accuracy of static sized context.

A Study on Deep Reinforcement Learning Framework for DME Pulse Design

  • Lee, Jungyeon;Kim, Euiho
    • Journal of Positioning, Navigation, and Timing
    • /
    • v.10 no.2
    • /
    • pp.113-120
    • /
    • 2021
  • The Distance Measuring Equipment (DME) is a ground-based aircraft navigation system and is considered as an infrastructure that ensures resilient aircraft navigation capability during the event of a Global Navigation Satellite System (GNSS) outage. The main problem of DME as a GNSS back up is a poor positioning accuracy that often reaches over 100 m. In this paper, a novel approach of applying deep reinforcement learning to a DME pulse design is introduced to improve the DME distance measuring accuracy. This method is designed to develop multipath-resistant DME pulses that comply with current DME specifications. In the research, a Markov Decision Process (MDP) for DME pulse design is set using pulse shape requirements and a timing error. Based on the designed MDP, we created an Environment called PulseEnv, which allows the agent representing a DME pulse shape to explore continuous space using the Soft Actor Critical (SAC) reinforcement learning algorithm.