• Title/Summary/Keyword: 표적 추정

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3-D Source Localization using Maximum Likelihood Estimate in Multi-path Environment with Inhomogeneous Sound Speed (비균일 음속 다중경로 환경에서 ML 추정기법을 이용한 표적의 3차원 위치추정)

  • Choi B. W.;Park D. H.;Kim J. S.;Shin C. H.;Lee J. H.;Lee K. K.
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.155-160
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    • 2004
  • 배열센서를 사용한 표적의 위치 추정은 레이다 및 소나에서 잘 알려진 문제이다. 최근에 Lee 등은 1 차원 수평 선배열 센서만을 사용하여 다중경로를 통해 들어오는 신호로부터 표적의 3 차원 위치를 추정하였다. 그러나 이 알고리즘에서 수중에서의 음속은 수심에 관계없이 일정하다고 가정하였기 때문에 음속이 수심에 따라 다양하게 변화하는 실제 수중환경에서는 그 추정성능이 현저히 저하된다. 따라서 본 논문에서는 표적의 거리, 깊이, 방위각으로 구성되는 3 차원 위치 추정을 위해 비균일 음속환경에서의 음파전달모델(ray propagation model)을 이용한 ML 기법(maximum likelihood estimation)을 적용하였으며 일정한 음속을 가정한 Lee 기법의 추정치를 초기값으로 한 탐색을 통해 ML 기법의 연산량을 감소시켰다.

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Multi-Small Target Tracking Algorithm in Infrared Image Sequences (적외선 연속 영상에서 다중 소형 표적 추적 알고리즘)

  • Joo, Jae-Heum
    • Journal of the Institute of Convergence Signal Processing
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    • v.14 no.1
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    • pp.33-38
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    • 2013
  • In this paper, we propose an algorithm to track multi-small targets in infrared image sequences in case of dissipation or creation of targets by using the background estimation filter, Kahnan filter and mean shift algorithm. We detect target candidates in a still image by subtracting an original image from an background estimation image, and we track multi-targets by using Kahnan filter and target selection. At last, we adjust specific position of targets by using mean shift algorithm In the experiments, we compare the performance of each background estimation filters, and verified that proposed algorithm exhibits better performance compared to classic methods.

RLSLTDE Algorithm for Bearing Estimation of the Underwater Acoustic Signal (수중음향신호 입사방위 추정을 위한 RLSLTDE 알고리즘)

  • Choi, Jae-Yong;Son, Kweon;Dho, Kyeong-Cheol
    • The Journal of the Acoustical Society of Korea
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    • v.19 no.5
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    • pp.84-90
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    • 2000
  • The bearing detection of radiated target noise is very important at underwater acoustic measurement and passive detection. It differs the arrival tines of received signal at each sensor. Therefore, the bearing can be obtained from the time delay. This paper proposes a new algorithm using the RLSL adaptive filter for TDE. The proposed method is particularly attractive when there is a limitation of priori information about the received signal spectra and when the delay is subject to variation. As the simulation results, it is shown that the proposed algorithm has better convergence characteristics and TDE speed, and so that the usefulness of proposed algorithm is confirmed.

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Target Localization Method based on Extended Kalman Filter using Multipath Time Difference of Arrival (다중경로 도달시간차이를 이용한 확장칼만필터 기반의 표적 위치추정 기법)

  • Cho, Hyeon-Deok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.6
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    • pp.251-257
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    • 2021
  • An underwater platform operating a passive sonar needs to acquire the target position to perform its mission. In an environment where sea-floor reflections exist, the position of a target can be estimated using the difference in the arrival time between the signals received through multipaths. In this paper, a method of localization for passive sonar is introduced, based on the EKF (Extended Kalman Filter) using the multipath time difference of arrival in underwater environments. TMA (Target Motion Analysis) requires accumulated measurements for long periods and has limitations on own-ship movement, allowing it to be used only in certain situations. The proposed method uses an EKF, which takes measurements of the time differences of the signal arrival in multipath environments. The method allows for target localization without restrictions on own-ship movement or the need for an observation time. To analyze the performance of the proposed method, simulation according to the distance and depth of the target was performed repeatedly, and the localization error according to the distance and water depth were analyzed. In addition, the correlation with the estimated position error was assessed by analyzing the arrival time difference according to the water depth.

Moving Target Localization using Wavelet based Wireless Sensor Node Collaborative Signal Processing (웨이블릿 기반의 무선 센서 노드 협력 신호처리를 이용한 이동 표적 위치 추정)

  • Cha, Dae-Hyun;Lee, Tae-Young;Hong, Jin-Keun;Han, Kun-Hui;Hwang, Chan-Sik
    • Proceedings of the KAIS Fall Conference
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    • 2009.12a
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    • pp.953-956
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    • 2009
  • 무선 센서 네트워크에서 이동하는 표적의 위치를 추정하기 위한 연구는 센서 노드의 에너지가 제한 되어 있어 센서 노드 상호간의 협력적인 신호처리 기법이 필수적이다. 기존의 무선 센서 네트워크에서 이동 표적의 위치를 추정하는 방법은 각 센서 노드에서 이동 표적으로부터 수신된 신호를 이용해 수신신호강도, 잡음제거, 압축 등의 신호처리를 수행하고 기지국으로 전송하는 형태이다. 이런 기존의 기법은 애드 호크 방법의 무선 센서 네트워크에는 적용이 어렵고, 각 센서 노드에서 신호처리 및 통신에 의한 에너지 소모가 크기 때문에 무선 센서 네트워크의 생존 시간이 짧아지게 된다. 본 논문에서는 웨이블릿 기반의 무선 센서 네트워크의 협력적 신호 처리 방법을 제안한다. 제안된 방법은 웨이블릿 변환을 이용한 센서노드에서의 에너지 효율적 특징추출을 수행하고 각 센서 노드간의 특징 전송을 통해 표적의 위치를 추정한다.

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A New Intelligent Tracking Algorithm Using Fuzzy Kalman Filter (퍼지 칼만 필터를 이용한 새로운 지능형 추적 알고리즘)

  • Noh Sun-Young;Joo Young-Hoon;Park Jin-Bae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.5
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    • pp.593-598
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    • 2005
  • The standard Kalman filter has been used to estimate the states of the target, but in the presence of a maneuver, its error is occurred and performance may be seriously degraded. To solve this problem, this paper presents a new intelligent tracking algorithm using the fuzzy Kalman filter. In this algorithm, the unknown acceleration is regarded as an additive process noise by using the fuzzy logic based on genetic algorithm(GA) method. And then, the modified filter is corrected by the new update equation method which is a fuzzy system using the relation between the filter residual and its variation. To shows the feasibility of the suggested method with only one filter, the computer simulations system are provided, this method is compared with multiple model method.

Multiple Targets Detection by using CLEAN Algorithm in Matched Field Processing (정합장처리에서 CLEAN알고리즘을 이용한 다중 표적 탐지)

  • Lim Tae-Gyun;Lee Sang-Hak;Cha Young-Wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.9
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    • pp.1545-1550
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    • 2006
  • In this paper, we propose a method for applying the CLEAN algorithm to an minimum variance distortionless response(MVDR) to estimate the location of multiple targets distributed in the ocean. The CLEAN algorithm is easy to implement in a linear processor, yet not in a nonlinear processor. In the proposed method, the CSDM of a Dirty map is separated into the CSDM of a Clean beam and the CSDM of the Residual, then an individual ambiguity surface(AMS) is generated. As such, the CLEAN algorithm can be applied to an MVDR, a nonlinear processor. To solve the ill-conditioned problem related to the matrix inversiion by an MVDR when using the CLEAN algorithm, Singular value decomposition(SVD) is carried out, then the reciprocal of small eigenvalues is replaced with zero. Experimental results show that the proposed method improves the performance of an MVDR.

Object Tracking Based on Centroids Shifting with Scale Adaptation (중심 이동 기반의 스케일 적응적 물체 추적 알고리즘)

  • Lee, Suk-Ho;Choi, Eun-Cheol;Kang, Moon-Gi
    • Journal of Korea Multimedia Society
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    • v.14 no.4
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    • pp.529-537
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    • 2011
  • In this paper, we propose a stable scale adaptive tracking method that uses centroids of the target colors. Most scale adaptive tracking methods have utilized histograms to determine target window sizes. However, in certain cases, histograms fail to provide good estimates of target sizes, for example, in the case of occlusion or the appearance of colors in the background that are similar to the target colors. This is due to the fact that histograms are related to the numbers of pixels that correspond to the target colors. Therefore, we propose the use of centroids that correspond to the target colors in the scale adaptation algorithm, since centroids are less sensitive to changes in the number of pixels that correspond to the target colors. Due to the spatial information inherent in centroids, a direct relationship can be established between centroids and the scale of target regions. Generally, after the zooming factors that correspond to all the target colors are calculated, the unreliable zooming factors are filtered out to produce a reliable zooming factor that determines the new scale of the target. Combined with the centroid based tracking algorithm, the proposed scale adaptation method results in a stable scale adaptive tracking algorithm. It tracks objects in a stable way, even when the background colors are similar to the colors of the object.

Estimation of target distance based on fractional Fourier transform analysis of active sonar linear frequency modulation signals (능동소나 linear frequency modulation 신호의 fractional Fourier transform 분석에 기반한 표적의 거리 추정)

  • Hyung, Sungwoong;Park, Myungho;Hwang, Soobok;Bae, Keunsung
    • The Journal of the Acoustical Society of Korea
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    • v.35 no.1
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    • pp.8-15
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    • 2016
  • As a generalized form of the conventional Fourier transform, fractional Fourier transform (FrFT) can analyze a signal at intermediate domain between time and frequency domains with a transform order ${\alpha}$. Especially, FrFT has a number of advantages in the analysis of LFM (Linear Frequency Modulation) signals due to its robustness to noise. In this paper, we have proposed a new method to detect and estimate the distance of the target from the FrFT spectrum of the received echo signal. Experimental results have validated the proposed method, and shown that reliable target distance could be estimated in noise and reverberation environments.

Target Velocity Estimation Technique Using CPA Analysis at the Moving Receiver (CPA분석을 이용한 기동하는 수신기에서의 표적 속도 추정기법)

  • Lee, Su-Hyoung;Kim, Jeong-Soo;Lee, Kyun-Kyung
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.4
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    • pp.336-342
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    • 2009
  • A conventional Closest Point of Approach (CPA) analysis allows a non-maneuvering moving source that is radiating a constant frequency tone to be located using doppler shifted frequency measurements obtained by a stationary receiver. The original frequency, relative speed of the target, time at the CPA, and range from the CPA to the sensor are estimated by the conventional CPA. However, this paper proposes a new CPA analysis that allows the motion parameters of a target to be estimated using the bearing and frequency measurements obtained by a moving receiver that has a constant velocity. The validity of the proposed estimation scheme is confirmed through a performance analysis and simulation study.