• Title/Summary/Keyword: Kalman FIlter Estimation

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Autonomous Tracking of Micro-Sized Flying Insects Using UAV: A Preliminary Results

  • Ju, Chanyoung;Son, Hyoung Il
    • Journal of the Korean Society of Industry Convergence
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    • v.23 no.2_1
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    • pp.125-137
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    • 2020
  • Tracking micro-sized insects is one of the challenges of protecting ecosystems and biodiversity. In this study, we propose an approach for the autonomous tracking of micro-sized flying insects, and develop an unmanned aerial vehicle (UAV)-based robotic system. The Kalman filter is applied to the received signal strength emitted from radio telemetry to estimate the position while reducing the measurement error and noise. The autonomous tracking strategy is a method in which the UAV rotates at one point to measure the signal strength and control its position in the strongest direction of the signal. We also design a system architecture comprising a tracking sensor system and a UAV system for micro-sized insects. The estimation and autonomous tracking of the target position by the proposed system are verified and evaluated through dynamic simulation. Therefore, in this study, we propose and validate a UAV-based tracking system for micro-sized flying insects, which has not been proposed in studies conducted thus far.

A Study on the Crust Deformation in and Around Korean Peninsula Using DGPS Data

  • Cho, Jin-Dong;Park, Jun Ku
    • Journal of the Korean Geophysical Society
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    • v.9 no.3
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    • pp.151-158
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    • 2006
  • Highly accurate surface velocity estimation using modern geodetic techniques plays very important role in the geological and geophysical interpretation. Researches with GPS are ongoing in many countries of the world. This study aims to estimate the amount of crustal deformation and the direction of deformation in the Korean Peninsula and in its neighbor. We used GAMIT that is a comprehensive GPS analysis package developed at MIT. Then, a Global Kalman filter called GLOBK is used to combine the results from GAMIT and to estimate the relative and absolute velocity vector for the crustal deformations. To estimate station velocity accuracy and reliably, it is extremely important to pay great attention to the reference frame. Firstly, using the Suwon (SUWN) of Eurasian plate as main frame, we estimate the relative amount of crustal deformation and a direction of Eurasian plate and North American plate, Secondly, using ITRF 2000 as main frame, we estimate the absolute crustal deformation of Eurasian plate and North American plate. The continent of Eurasian where has the Korean Peninsula deforms 33.36 mm per year to East-Southeast (ESE), and Japanese Tsukuba (TSKB) in North American plate deforms to South-Southwest (SSW). Finally, the Korean Peninsula is approaching the Japanese Island and the rate of horizontal crustal deformation between the Suwon and the Tsukuba is about 31.98 mm per year in the moving direction of N85.9oW (274.1o) for the past three years.

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Electro-Thermal Model Based-Temperature Estimation Method of Lithium-Ion Battery for Fuel-Cell and Battery Hybrid Railroad Propulsion System (하이브리드 철도차량 시스템의 전기-열 모델 기반 리튬이온 배터리 온도 추정 방안)

  • Park, Seongyun;Kim, Jaeyoung;Kim, Jonghoon;Ryu, Joonhyoung;Cho, Inho
    • The Transactions of the Korean Institute of Power Electronics
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    • v.26 no.5
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    • pp.357-363
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    • 2021
  • Eco-friendly hybrid railroad propulsion system with fuel-cell and battery was suggested to reduce carbon dioxide gas and replace retired diesel railroads. Lithium-ion battery with high energy/power density and long lifetime is selected as the energy source at the battery side due to its excellent performance. However, the performance of lithium-ion batteries was affected by temperature, current rate, and operating condition. Temperature is known to be the most influential factor in changing battery parameters. In addition, appropriate thermal management is required to ensure the safe and effective operation of lithium-ion battery. Electro-thermal coupled model with varying parameter depends on temperature, and state-of-charge (SOC) is suggested to estimate battery temperature. The electric-thermal coupled model contains diffusion current using parameter identification by adaptive control algorithm when considering thermal diffusion effect. An experiment under forced convection was conducted using cylindrical cell and 18 parallel-connected battery module to demonstrate the method.

Comparisons of Core Temperature Between a Telemetric Pill and Heart Rate Estimated Core Temperature in Firefighters

  • Pearson, Stephen J.;Highlands, Brian;Jones, Rebecca;Matthews, Martyn J.
    • Safety and Health at Work
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    • v.13 no.1
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    • pp.99-103
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    • 2022
  • Background: Firefighters may experience high environmental temperatures or carry out intensive physical tasks, or both, which leads to increased core body temperature and risk of fatalities. Hence there is a need to remotely and non-invasively monitor core body temperature. Methods: Estimated (heart rate algorithm) and actual core body temperature (ingested telemetric pill) measures were collected simultaneously for comparison during training exercises on 44 firefighter volunteers. Results: Prediction of core body temperature varied, with no specific identifiable pattern between the algorithm values and directly measured body core temperatures. Group agreement of Lin's Concordance of 0.74 (95% Upper 0.75, lower CI 0.73), was deemed poor. Conclusion: From individual agreement data Lin's Concordance was variable (Min 0.11, CI 0.13-0.01; Max 0.83, CI 0.86-0.80), indicating that the heart rate algorithm approach was not suitable for core body temperature monitoring in this population group, especially at the higher more critical core body temperatures seen.

Grey algorithmic control and identification for dynamic coupling composite structures

  • ZY Chen;Ruei-yuan Wang;Yahui Meng;Timothy Chen
    • Steel and Composite Structures
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    • v.49 no.4
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    • pp.407-417
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    • 2023
  • After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. Many domain schemes based on the measured vibration computations, including least squares estimation and neural fuzzy logic control, have been studied and found to be effective for online/offline monitoring of structural damage. Traditional strategies require all external stimulus data (input data) which have been measured available, but this may not be the generalized for all structures. In this article, a new method with unknown inputs (excitations) is provided to identify structural matrix such as stiffness, mass, damping and other nonlinear parts, unknown disturbances for example. An analytical solution is thus constructed and presented because the solution in the existing literature has not been available. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.

A Real-time Particle Filtering Framework for Robust Camera Tracking in An AR Environment (증강현실 환경에서의 강건한 카메라 추적을 위한 실시간 입자 필터링 기법)

  • Lee, Seok-Han
    • Journal of Digital Contents Society
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    • v.11 no.4
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    • pp.597-606
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    • 2010
  • This paper describes a real-time camera tracking framework specifically designed to track a monocular camera in an AR workspace. Typically, the Kalman filter is often employed for the camera tracking. In general, however, tracking performances of conventional methods are seriously affected by unpredictable situations such as ambiguity in feature detection, occlusion of features and rapid camera shake. In this paper, a recursive Bayesian sampling framework which is also known as the particle filter is adopted for the camera pose estimation. In our system, the camera state is estimated on the basis of the Gaussian distribution without employing additional uncertainty model and sample weight computation. In addition, the camera state is directly computed based on new sample particles which are distributed according to the true posterior of system state. In order to verify the proposed system, we conduct several experiments for unstable situations in the desktop AR environments.

Similarity-based Dynamic Clustering Using Radar Reflectivity Data (퍼지모델을 이용한 유사성 기반의 동적 클러스터링)

  • Lee, Han-Soo;Kim, Su-Dae;Kim, Yong-Hyun;Kim, Sung-Shin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2011.10a
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    • pp.219-222
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    • 2011
  • There are number of methods that track the movement of an object or the change of state, such as Kalman filter, particle filter, dynamic clustering, and so on. Amongst these method, dynamic clustering method is an useful way to track cluster across multiple data frames and analyze their trend. In this paper we suggest the similarity-based dynamic clustering method, and verifies it's performance by simulation. Proposed dynamic clustering method is how to determine the same clusters for each continuative frame. The same clusters have similar characteristics across adjacent frames. The change pattern of cluster's characteristics in each time frame is throughly studied. Clusters in each time frames are matched against each others to see their similarity. Mamdani fuzzy model is used to determine similarity based matching algorithm. The proposed algorithm is applied to radar reflectivity data over time domain. We were able to observe time dependent characteristic of the clusters.

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Radome Slope Estimation using Mode Parameter Renewal Method of IMM Algorithm (IMM 알고리듬의 모드 계수 갱신 방법을 통한 레이돔 굴절률 추정)

  • Kim, Young-Mo;Back, Ju-Hoon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.5
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    • pp.763-770
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    • 2017
  • A radome mounted on the front of an aircraft can cause refraction errors for various reasons that occur during maneuver in seeking and tracking a target. This refraction error means that the microwave seeker is detecting apparent target. An Interactive Multiple Model (IMM) algorithm is applied to estimate radome slope mounted on an aircraft in 3D space. However, even though the parameter of uncertain system model such as radome slope can be estimated, the estimated performance can not be guaranteed when it exceeds the range of the predicted value. In this paper, we propose a method to update the predicted value by using the radome slope as the mode parameter of the IMM algorithm, and confirm the radome slope estimation performance of the proposed method.

Estimation of MineRo's Kinematic Parameters for Underwater Navigation Algorithm (수중항법 알고리즘을 위한 미내로 운동학 파라미터 예측)

  • Yeu, Tae-Kyeong;Yoon, Suk-Min;Park, Soung-Jea;Hong, Sup;Choi, Jong-Su;Kim, Hyung-Woo;Kim, Dae-Won;Lee, Chang-Ho
    • Ocean and Polar Research
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    • v.33 no.1
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    • pp.69-76
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    • 2011
  • A test miner named MineRo was constructed for the purpose of shallow water test of mining performance. In June of 2009, the performance test was conducted in depth of 100 m, 5 km away from Hupo-port (Korean East Sea), to assess if the developed system is able to collect and lift manganese nodules from seafloor. In August of 2010, in-situ test of automatic path tracking control of MineRo was performed in depth of 120 m at the same site. For path tracking control, a localization algorithm determining MineRo's position on seabed is prerequisite. This study proposes an improved underwater navigation algorithm through estimation of MineRo's kinematic parameters. In general, the kinematic parameters such as track slips and slip angle are indirectly calculated using the position data from USBL (Ultra-Short Base Line) system and heading data from gyro sensors. However, the obtained data values are likely to be different from the real values, primarily due to the random noise of position data. The aim of this study is to enhance the reliability of the algorithm by measuring kinematic parameters, track slips and slip angle.

Single-axis Hardware in the Loop Experiment Verification of ADCS for Low Earth Orbit Cube-Satellite

  • Choi, Minkyu;Jang, Jooyoung;Yu, Sunkyoung;Kim, O-Jong;Shim, Hanjoon;Kee, Changdon
    • Journal of Positioning, Navigation, and Timing
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    • v.6 no.4
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    • pp.195-203
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    • 2017
  • A 2U cube satellite called SNUGLITE has been developed by GNSS Research Laboratory in Seoul National University. Its main mission is to perform actual operation by mounting dual-frequency global positioning system (GPS) receivers. Its scientific mission aims to observe space environments and collect data. It is essential for a cube satellite to control an Earth-oriented attitude for reliable and successful data transmission and reception. To this end, an attitude estimation and control algorithm, Attitude Determination and Control System (ADCS), has been implemented in the on-board computer (OBC) processor in real time. In this paper, the Extended Kalman Filter (EKF) was employed as the attitude estimation algorithm. For the attitude control technique, the Linear Quadratic Gaussian (LQG) was utilized. The algorithm was verified through the processor in the loop simulation (PILS) procedure. To validate the ADCS algorithm in the ground, the experimental verification via a single axis Hardware-in-the-loop simulation (HILS) was used due to the simplicity and cost effectiveness, rather than using the 3-axis HILS verification (Schwartz et al. 2003) with complex air-bearing mechanism design and high cost.