• Title, Summary, Keyword: 칼만 필터

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Quadratic Kalman Filter Object Tracking with Moving Pictures (영상 기반의 이차 칼만 필터를 이용한 객체 추적)

  • Park, Sun-Bae;Yoo, Do-Sik
    • The Journal of Advanced Navigation Technology
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    • v.20 no.1
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    • pp.53-58
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    • 2016
  • In this paper, we propose a novel quadratic Kalman filter based object tracking algorithm using moving pictures. Quadratic Kalman filter, which is introduced recently, has not yet been applied to the problem of 3-dimensional (3-D) object tracking. Since the mapping of a position in 2-D moving pictures into a 3-D world involves non-linear transformation, appropriate algorithm must be chosen for object tracking. In this situation, the quadratic Kalman filter can achieve better accuracy than extended Kalman filter. Under the same conditions, we compare extended Kalman filter, unscented Kalman filter and sequential importance resampling particle filter together with the proposed scheme. In conculsion, the proposed scheme decreases the divergence rate by half compared with the scheme based on extended Kalman filter and improves the accuracy by about 1% in comparison with the one based on unscented Kalman filter.

3-D Facial Motion Estimation Using Iterative Extended Kalman Filter (반복적 확장 칼만 필터를 이용한 얼굴의 3차원 움직임량 추정)

  • Park, Gang-Ryeong;Kim, Jae-Hui
    • The KIPS Transactions:PartB
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    • v.8B no.1
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    • pp.28-34
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    • 2001
  • 컴퓨터 시각 인식 방법을 이용하여 얼굴의 3차원 움직임 량을 추정하고자 하는 연구는 가상 현실 환경에서 얼굴 움직임에 의한 3차원 그래픽 화면 조정, 시뮬레이터에서의 훈련자 얼굴 움직임에 의한 화면 조정 및 모니터상의 시선 위치 파악 등을 위해 필수적으로 요구되는 기술로서 최근 활발히 연구되고 있다. 기존에 얼굴의 3차원 움직임 량을 추정하고자 하는 연구들은 대부분 확장 칼만 필터(extended kalman filter)를 이용하였으나, 이러한 방법은 필터의 초기 값을 정확하게 설정해야하는 제약 요소를 갖고 있으며, 또한 얼굴의 회전 방향 변화 시 이에 대처하지 못하는 경우 역시 종종 발생한다. 본 논문에서는 이러한 문제점을 해결하기 위하여 확장 칼만 필터의 변형 형태인 반복적 확장 칼만 필터를 이용하여 얼굴의 3차원 움직임 량을 추정하였다. 반복적 확장 칼만 필터에서는 확장 칼만 필터에서 계산되어 나오는 추정 오차 공분산 행렬 값이 미리 정해진 임계치보다 커지는 경우, 현재 얼굴의 움직임 량을 제대로 추정하지 못하고 있는 것으로 판단하여 칼만 필터에서 사용하는 회전 및 이동 속도, 그리고 회전 및 이동 각 속도를 변형함으로써 얼굴의 움직임 량을 정확하게 추정할 수 있도록 하는 방법이다. 실험 결과 반복적 확장 칼만 필터를 사용하였을 경우에 얼굴의 급격한 회전 방향 변화에도 얼굴의 3차원 움직임 량을 정확하게 추정할 수 있음을 알 수 있었다.

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A Performance Comparison of Nonlinear Kalman Filtering Based Terrain Referenced Navigation (비선형 칼만 필터 기반의 지형참조항법 성능 비교)

  • Mok, Sung-Hoon;Bang, Hyo-Choong;Yu, Myeong-Jong
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.40 no.2
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    • pp.108-117
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    • 2012
  • This paper focuses on a performance analysis of TRN among various nonlinear filtering methods. In a TRN research, extended Kalman filter(EKF) is a basic estimation algorithm. In this paper, iterated EKF(IEKF), EKF with stochastic linearization(SL), and unscented Kalman filter(UKF) algorithms are introduced to compare navigation performance with original EKF. In addition to introduced sequential filters, bank of Kalman filters method, which is one of the batch method, is also presented. Finally, by simulating an artificial aircraft mission, EKF with SL was chosen as the most consistent filter in the introduced sequential filters. Also, results suggested that the bank of Kalman filters can be alternative for TRN, when a fast convergence of navigation solution is needed.

Parameter tuning of Kalman fulter Using a Fuzzy Logic Control (퍼지 논리를 이용한 칼만 필터의 파라메터 조정)

  • 방은오;강성인;이상배
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.346-349
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    • 1997
  • 칼만 필터는 피드백 제어의 형태를 사용하는 플랜트를 추정한다. 플랜트의 잡음이나 측정 외란이 발생하더라도 상태를 추정하여 최적의 제어를 행한다. 상태를 추정하기 위하여 칼만 필터의 이득 Kk를 저절하고, 이 이득은 칼만 필터의 파라메터인 측정 오차 공분산 Rk과 프로세서 잡음 오차 공분산 Qk를 조정함으로써 뛰어난 필터 수행을 얻을 수 있다. 그러나 필터 파라메터 Rk, Qk는 필터 연산 이전에 측정되어야 하지만, 현재는 전문가가 전문적인 지식을 바탕으로 파라메터를 조정하여 시스템을 제어하고 있다. 따라서 이러한 비효율적인 작업을 퍼지 논리 제어기를 이용하여 온-라인에서 최적의 파라메터 Rk를 구하고자 한다.

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칼만필터를 이용한 해양선박의 위치제어에 대한 연구

  • Lee, Ho;Lee, Seung-Geon
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • pp.74-76
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    • 2012
  • 칼만이론 및 Unscented 변환 기반의 Unscented 칼만필터를 이용하여 동적위치제어시스템을 설계하였다. Unscented 칼만필터는 기존의 칼만필터처럼 비선형운동방정식을 선형화 할 필요없이 비선형운동방정식 그대로 사용할수 있다. Unscented 칼만필터를 이용하여 설계한 동적위치제어시스템을 MATLAB SIMULINK프로그램을 이용하여 해양선박에 대해 컴퓨터시뮬레이션을 진행하였다.

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Sensorless speed control of permanent magnet synchronous motor using square-root extended kalman filter (제곱근 확장 칼만 필터에 의한 영구자석 동기전동기의 센서리스 속도제어)

  • Moon, Cheol;Kwon, Young-Ahn
    • Journal of the Korean Society of Marine Engineering
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    • v.40 no.3
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    • pp.217-222
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    • 2016
  • This study investigates the design, analysis, and implementation of the square-root extended Kalman filter by using an algorithm derived by combining the Potter or Carlson algorithm with the modified Gram-Schmidt algorithm, for sensorless speed control of a permanent-magnet synchronous motor. The sensitivity of the Kalman filter to round-off errors is a well-known problem. A possible way to address this limitation is by combining the square-root concept and Kalman filter that can improve the numerical performance and solve instability-related problems such as divergence. This paper presents the design and analysis of the implementation of such a square-root extended Kalman filter. To demonstrate the performance of the proposed filter, experimental results under several operating conditions, such as high and low speeds, reversal rotation, detuned parameters and load test, have been analyzed. Further, code sizes and operation times have been compared. Experimental results establish the performance of the proposed square-root extended Kalman filter-based estimation technique for sensorless speed control of a permanent-magnet synchronous motor.

Kalman Filter Residual Calculation of a 75-ton Liquid Rocket Engine under an Artificial Fault (75톤급 액체로켓엔진의 가상적 고장 상황에서의 칼만 필터 잔차 생성)

  • Lee, Kyelim;Cha, Jihyoung;Ko, Sangho;Park, Soon-Young;Jung, Eunhwan
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • pp.218-223
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    • 2017
  • This paper deals with a fault diagnosis algorithm using the Kalman filter for a 75-ton Liquid Propellant Rocket Engine (LPRE). To design the Kalman filter, we linearized a non-linear simulation model of a 75-ton LPRE at an operating point, and checked the performance of the Kalman filter by comparing the measured values with estimated values of the states. Then, we artificially injected a fault of the turbopump efficiency into the simulation to confirm the performance of the fault diagnosis algorithm with the developed Kalman filter by comparing the variation of the residuals of the normal state with that of the fault cases.

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An Adaptive Hybrid Filter for WiFi-Based Positioning Systems (와이파이 기반 측위 시스템을 위한 적응형 혼합 필터)

  • Park, Namjoon;Jung, Suk Hoon;Moon, Yoonho;Han, Dongsoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.12 no.4
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    • pp.76-86
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    • 2013
  • As the basic Kalman filter is limited to be used for indoor navigation, and particle filters incur serious computational overhead, especially in mobile devices, we propose an adaptive hybrid filter for WiFi-based indoor positioning systems. The hybrid filter utilizes the same prediction framework of the basic Kalman filter, and it adopts the notion of particle filters only using a small number of particles. Restricting the predicts of a moving object to a small number of particles on a way network and substituting a dynamic weighting scheme for Kalman gain are the key features of the filter. The adaptive hybrid filter showed significantly better accuracy than the basic Kalman filter did, and it showed greatly improved performance in processing time and slightly better accuracy compared with a particle filter.

The Unscented Kalman Filter Based Backward Filters for the Precise INS/GPS System (정밀 INS/GPS시스템을 위한 언센티드 칼만 필터 기반의 역방향 필터연구)

  • Kwon, Jay-Hyoun;Lee, Jong-Ki;Lee, Ji-Sun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.13 no.2
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    • pp.157-167
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    • 2010
  • Unscented Kalman filter based backward filter is derived and the positions from extended Kalman filter, unscented Kalman filter, and extended Kalman smoother are compared and analyzed through a simulation test. Considering the poor GPS signal reception, the simulation is performed under the assumption of only the start and end points of the trajectory, composed of 4 curves and 5 straight sections in the area of $40m{\times}40m $, are known. The test shows that the smoothers generate much better positioning results of 8~9m improvement compared to those from the forward filters. For the comparison between the smoothers, the analysis is performed separately for the curves and straight segments. In both cases, the unscented Kalman smoother generates better positioning error; 10cm and 23cm improved positioning results in straight segment and curves, respectively.

Trace of Moving Object using Structured Kalman Filter (구조적 칼만 필터를 이용한 이동 물체의 추적)

  • Jang, Dae-Sik;Jang, Seok-Woo;Kim, Gye-young;Choi, Hyung-Il
    • Journal of KIISE:Software and Applications
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    • v.29 no.5
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    • pp.319-325
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    • 2002
  • Tracking moving objects is one of the most important techniques in motion analysis and understanding, and it has many difficult problems to solve. Especially, estimating and identifying moving objects, when the background and moving objects vary dynamically, are very difficult. It is possible under such a complex environment that targets may disappear totally or partially due to occlusion by other objects. The Kalman filter has been used to estimate motion information and use the information in predicting the appearance of targets in succeeding frames. In this paper, we propose another version of the Kalman filter, to be called structured Kalman filter, which can successfully work its role of estimating motion information under a deteriorating condition such as occlusion. Experimental results show that the suggested approach is very effective in estimating and tracking non-rigid moving objects reliably.