• 제목/요약/키워드: Adaptive Kalman filter

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A Study on a effective Information Compressor Algorithm for the variable environment variation using the Kalman Filter

  • Choi, Jae-Yun
    • 한국컴퓨터정보학회논문지
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    • 제23권4호
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    • pp.65-70
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    • 2018
  • This paper describes a effective information compressor algorithm for the fourth industrial technology. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because input images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a effective information algorithm for variable environment variable under outdoor is proposed, which apply the Kalman Estimation Modeling and adaptive threshold on pixel level to separate foreground and background images from current input image. In results, the better SNR of about 3dB~5dB and about 10%~25% noise distribution rate in the proposed method. Furthermore, it was showed that the moving objects can be detected on various shadows under outdoor and better result Information.

적응 차수 조노토픽 칼만 필터를 활용한 비정상 비행상태 항공기의 실시간 시스템 식별 (Real-time System Identification of Aircraft in Upset Condition Using Adaptive-order Zonotopic Kalman Filter)

  • 김성민;헨드라 구남완 하노;수브라마냠 사델라;김윤수
    • 한국항공우주학회지
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    • 제50권2호
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    • pp.93-101
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    • 2022
  • 실속, 결빙, 센서 이상 등으로 인해 일어나는 제어불능 또는 비정상 비행 상황은 항공기의 추락으로 이어지기 때문에 필수적으로 대비해야 한다. 이와 관련해 비정상 비행 상황에서 항공기의 동적 특성을 정확하게 파악하는 것은 매우 중요하다. 본 논문에서는 일시적인 센서 이상이 발생한 고받음각의 비정상 비행상태 항공기에 대해서 기존의 칼만 필터 기반의 시스템 식별법 대비 보다 효과적인 적응 차수 조노토픽 칼만 필터와 이동창-최소자승법을 활용한 시스템 식별법을 제시하였다. 제안한 방법을 실제 비행 데이터에 적용하고 그 성능을 기존 연구 결과와 비교하였다.

국부 영상 활동도에 적응적인 칼만 필터를 이용한 HDR 세부 영상 레이어의 잡음 제거 (Noise Reduction of HDR Detail Layer Using a Kalman Filter Adapted to Local Image Activity)

  • 김태규;송인호;이성학
    • 한국멀티미디어학회논문지
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    • 제22권1호
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    • pp.10-17
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    • 2019
  • In High Dynamic Range (HDR) image processing, tone mapping is the process to compress an input image into a Low Dynamic Range (LDR) image. In most cases, the reason that detail preservation is prior to take over tone mapping is that the dynamic range is significantly different between input and output images. In the case of iCAM06, details are separated by using a bilateral filter, however, it causes noise amplification at the dim surround region. Thus, we suggest that the detail signal, which is separated from the bilateral filter, is combined with the base signal after an adaptive Kalman filter is applied according to the local standard deviation. We confirmed that the proposed method enhances the HDR images quality by checking the noise reduction in a dim surround region.

Multiuser Channel Estimation Using Robust Recursive Filters for CDMA System

  • Kim, Jang-Sub;Shin, Ho-Jin;Shin, Dong-Ryeol
    • Journal of Communications and Networks
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    • 제9권3호
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    • pp.219-228
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    • 2007
  • In this paper, we present a novel blind adaptive multiuser detector structure and three robust recursive filters to improve the performance in CDMA environments: Sigma point kalman filter (SPKF), particle filter (PF), and Gaussian mixture sigma point particle filter (GMSPPF). Our proposed robust recursive filters have superior performance over a conventional extended Kalman filter (EKF). The proposed multiuser detector algorithms initially use Kalman prediction form to estimated channel parameters, and unknown data symbol be predicted. Second, based on this predicted data symbol, the robust recursive filters (e.g., GMSPPF) is a refined estimation of joint multipaths and time delays. With these estimated multipaths and time delays, data symbol detection is carried out (Kalman correction form). Computer simulations show that the proposed algorithms outperform the conventional blind multiuser detector with the EKF. Also we can see it provides a more viable means for tracking time-varying amplitudes and time delays in CDMA communication systems, compared to that of the EKF for near-far ratio of 20 dB. For this reason, it is believed that the proposed channel estimators can replace well-known filter such as the EKF.

GPS/IMU/OBD 융합기반 ACF/IMMKF를 이용한 차량 Pitch 추정 알고리즘 (Vehicular Pitch Estimation Algorithm with ACF/IMMKF Based on GPS/IMU/OBD Data Fusion)

  • 김주원;이명수;이상선
    • 한국통신학회논문지
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    • 제40권9호
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    • pp.1837-1845
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    • 2015
  • 도심지환경에서 정확한 차량 위치를 추정하기 위해서는 종방향 속도가 필요하다. 이러한 종방향 속도는 노면경사, 즉 차량의 피치각(Pitch) 산출을 통해서 가능하다. 하지만 단일 센서와 알고리즘을 이용한 피치각 추정에는 정확한 값을 기대할 수 없다. 본 논문에서는 정확한 피치각 추정을 위해 AKF(Adaptive Kalman Filter)와 CF(Complementary Filter)로 구성된 ACF(Adaptive Complementary Filter)를 이용하여 IMU(Inertial Measurement Unit)의 프로세스 노이즈와 측정에러를 주행환경에 맞게 조절하고, 이에 GPS(Global Positioning System)와 OBD(Onboard Equipment) 데이터를 융합한다. 그리고 노면 경사 모델에 따른 필터에 시스템 모델 최적화를 위해 IMMKF(Interactive Multiple Model Kalman Filter)를 사용하여 주행환경에 적합한 최종 피치각을 추정한다.

Kalman 알고리즘에 의한 대역분할. 합성형 어댑티브 어레이 안테나의 동작 특성 (Performance Characteristics of Subband Adaptive Array Antenna using Kalman Algorithm)

  • 박재성;오경석;주창복;박남천;정주수
    • 한국정보통신학회논문지
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    • 제3권3호
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    • pp.501-507
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    • 1999
  • 이동체에서 어댑티브 어레이 안테나를 사용하는 경우 가중계수벡터를 전파 환경의 변화에 고속으로 적응시킬 필요가 있다. 4소자 등간격 선형 어레이 안테나 시스템에 있어서 일정 진폭의 포락선을 갖는 BPSK신호나 BFSK 신호에 대하여 신호의 자기상관성을 향상시켜 주므로서 효과적인 다중 간섭파를 제거할 수 있는 대역분할 합성법에 의한 신호처리 기법을 보고한다. 본 논문에서는 S/I=2, S/N=10인 BPSK 신호에 대하여 대역분할ㆍ합성형 신호처리 기법을 LMS 및 Kalman 알고리즘에 적용한 컴퓨터 시뮬레이션 결과 대역분할ㆍ합성형 기법을 사용하므로서 알고리즘의 수렴성이 빠르고 신호의 추종성이 매우 뛰어남을 확인 할 수 있었다.

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Adaptive ${\alpha}-{\beta}$ Tracker for TWS Radar System

  • Kim, Byung-Doo;Lee, Ja-Sung
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.506-509
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    • 2005
  • An adaptive ${\alpha}-{\beta}$ tracker is proposed for tracking maneuvering targets with a track-while-scan radar system. The tracker gain is updated on-line corresponding to the adjusted process noise variance which is obtained via time averaging of the process over a sliding window. The adjusted process noise variance is used to compute the maneuverability index for the tracker gain based on the steady-state Kalman filter equation for each epoch. It is shown via simulation that the proposed approach provides robust and accurate position estimates during the target maneuver while the performance of the conventional ${\alpha}-{\beta}$ tracker is shown much degraded.

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Vision-Based Relative State Estimation Using the Unscented Kalman Filter

  • Lee, Dae-Ro;Pernicka, Henry
    • International Journal of Aeronautical and Space Sciences
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    • 제12권1호
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    • pp.24-36
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    • 2011
  • A new approach for spacecraft absolute attitude estimation based on the unscented Kalman filter (UKF) is extended to relative attitude estimation and navigation. This approach for nonlinear systems has faster convergence than the approach based on the standard extended Kalman filter (EKF) even with inaccurate initial conditions in attitude estimation and navigation problems. The filter formulation employs measurements obtained from a vision sensor to provide multiple line(-) of(-) sight vectors from the spacecraft to another spacecraft. The line-of-sight measurements are coupled with gyro measurements and dynamic models in an UKF to determine relative attitude, position and gyro biases. A vector of generalized Rodrigues parameters is used to represent the local error-quaternion between two spacecraft. A multiplicative quaternion-error approach is derived from the local error-quaternion, which guarantees the maintenance of quaternion unit constraint in the filter. The scenario for bounded relative motion is selected to verify this extended application of the UKF. Simulation results show that the UKF is more robust than the EKF under realistic initial attitude and navigation error conditions.

대전차 위협체 상태추정을 위한 퍼지 규칙기반 적응적 칼만필터 (Fuzzy Rule-Based Adaptive Kalman Filter for State Estimation of Anti-Tank Threats)

  • 이의혁;조규공;박상순;강윤식
    • 한국군사과학기술학회지
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    • 제15권1호
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    • pp.57-65
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    • 2012
  • To neutralize fast Anti-Tank Guided Missiles(ATGMs) or Anti-Tank Rockets(ATRs) projected at short ranges, the trajectories and times that the threats arrive at hard-kill systems should be predicted precisely. The trajectories of ATGMs or ATRs are almost stationary but the velocity and acceleration are very changeable in the terminal stage, so that it is needed to predict the characteristics of ATGMs and ATRs for filtering. In this paper the Fuzzy Rule based Adaptive Kalman Filter(FRAKF) is proposed to estimate the position, velocity and acceleration of the threats with accuracy and the performance of it is compared with the existing tracking filter considering the maneuvering characteristics of threats.

기동표적 추적을 위한 DNA 코딩 기반 지능형 칼만 필터 (DNA Coding-Based Intelligent Kalman Filter for Tracking a Maneuvering Target)

  • 이범직;주영훈;박진배
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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    • pp.118-121
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    • 2002
  • The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the state of the target, but in the presence of a maneuver, its performance may be seliously degraded. In this paper, to solve this problem and track a maneuvering target effectively, DNA coding-based intelligent Kalman filter (DNA coding-based IKF) is proposed. The proposed method can overcome the mathematical limits of conventional methods and can effectively track a maneuvering target with only one filter by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive interacting multiple model (AIMM) method and the GA-based IKF in computer simulations.