• Title/Summary/Keyword: 무향 칼만필터

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Fault Detection of Small Turbojet Engine for UAV Using Unscented Kalman Filter and Sequential Probability Ratio Test (무향칼만필터와 연속확률비 평가를 이용한 무인기용 소형제트엔진의 결함탐지)

  • Han, Dong Ju
    • Journal of Aerospace System Engineering
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    • v.11 no.4
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    • pp.22-29
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    • 2017
  • A study is performed for the effective detection method of a fault which is occurred during operation in a small turbojet engine with non-linear characteristics used by unmanned air vehicle. For this study the non-linear dynamic model of the engine is derived from transient thermodynamic cycle analysis. Also for inducing real operation conditions the controller is developed associated with unscented Kalman filter to estimate noises. Sequential probability ratio test is introduced as a real time method to detect a fault which is manipulated for simulation as a malfunction of rotational speed sensor contaminated by large amount of noise. The method applied to the fault detection during operation verifies its effectiveness and high feasibility by showing good and definite decision performances of the fault.

Flight Path Measurement of Drones Using Microphone Array and Performance Improvement Method Using Unscented Kalman Filter (마이크로폰 어레이를 이용한 드론의 비행경로 측정과 무향칼만필터를 이용한 성능 개선법에 대한 연구)

  • Lee, Jiwon;Go, Yeong-Ju;Kim, Seungkeum;Choi, Jong-Soo
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.46 no.12
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    • pp.975-985
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    • 2018
  • The drones have been developed for military purposes and are now used in many fields such as logistics, communications, agriculture, disaster, defense and media. As the range of use of drones increases, cases of abuse of drones are increasing. It is necessary to develop anti-drone technology to detect the position of unwanted drones using the physical phenomena that occur when the drones fly. In this paper, we estimate the DOA(direction of arrival) of the drone by using the acoustic signal generated when the drone is flying. In addition, the dynamics model of the drones was applied to the unscented kalman filter to improve the microphone array detection performance and reduce the error of the position estimation. Through simulation, the drone detection performance was predicted and verified through experiments.

CenterTrack-EKF: Improved Multi Object Tracking with Extended Kalman Filter (CenterTrack-EKF: 확장된 칼만 필터를 이용한 개선된 다중 객체 추적)

  • Hyun-Sung Yang;Chun-Bo Sim;Se-Hoon Jung
    • Smart Media Journal
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    • v.13 no.5
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    • pp.9-18
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    • 2024
  • Multi-Object trajectory modeling is a major challenge in MOT. CenterTrack tried to solve this problem with a Heatmap-based method that tracks the object center position. However, it showed limited performance when tracking objects with complex movements and nonlinearities. Considering the degradation factor of CenterTrack as the dynamic movement of pedestrians, we integrated the EKF into CenterTrack. To demonstrate the superiority of our proposed method, we applied the existing KF and UKF to CenterTrack and compared and evaluated it on various datasets. The experimental results confirmed that when EKF was integrated into CenterTrack, it achieved 73.7% MOTA, making it the most suitable filter for CenterTrack.

Relative Navigation Study Using Multiple PSD Sensor and Beacon Module Based on Kalman Filter (복수 PSD와 비콘을 이용한 칼만필터 기반 상대항법에 대한 연구)

  • Song, Jeonggyu;Jeong, Junho;Yang, Seungwon;Kim, Seungkeun;Suk, Jinyoung
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.46 no.3
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    • pp.219-229
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    • 2018
  • This paper proposes Kalman Filter-based relative navigation algorithms for proximity tasks such as rendezvous/docking/cluster-operation of spacecraft using PSD Sensors and Infrared Beacon Modules. Numerical simulations are performed for comparative analysis of the performance of each relative-navigation technique. Based on the operation principle and optical modeling of the PSD Sensor and the Infrared Beacon Module used in the relative navigation algorithm, a measurement model for the Kalman filter is constructed. The Extended Kalman Filter(EKF) and the Unscented Kalman Filter(UKF) are used as probabilistic relative navigation based on measurement fusion to utilize kinematics and dynamics information on translational and rotation motions of satellites. Relative position and relative attitude estimation performance of two filters is compared. Especially, through the simulation of various scenarios, performance changes are also investigated depending on the number of PSD Sensors and IR Beacons in target and chaser satellites.

A Study on the Prediction Technique of Impact Dispersion Area for Flight Safety Analysis (비행안전분석을 위한 낙하분산영역 예측 기법에 대한 연구)

  • Choi, Kyu-Sung;Sim, Hyung-Seok;Ko, Jeong-Hwan;Chung, Eui-Seung
    • Aerospace Engineering and Technology
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    • v.13 no.2
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    • pp.177-184
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    • 2014
  • Flight safety analyses concerned with Launch Vehicle are performed to measure the risk to the people, ship and aircraft using impact point and impact dispersion area of debris generated by on-trajectory failures and malfunction turns. Predictions of impact point and impact dispersion area are essential for launch vehicle's flight safety analysis. Usually, impact dispersion area can be estimated in using Monte-Carlo simulation. However, Monte-Carlo method requires more several hundreds of iterative calculations which requires quite some time to produce impact dispersion area. Herein, we check the possibility of applying JU(Julier Uhlmann) transformation and Taguchi method instead of Monte-Carlo method and we propose a best method in terms of compuational time to produce impact dispersion area by comparing the results of the three methods.