• 제목/요약/키워드: Estimation of Target Tracking Performance

검색결과 132건 처리시간 0.023초

레이다 시선 측정치를 활용하는 선형 표적 추적필터 기반 함포 사격제원계산장치 성능향상 방법 (Performance Improvement Approach to Naval Gun Fire Control System Based on Linear Target Tracking Filter with Radar Line-of-sight Measurements)

  • 서의석
    • 한국군사과학기술학회지
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    • 제27권4호
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    • pp.446-456
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    • 2024
  • This paper addresses a novel approach to performance enhancement of the naval gun fire control system(FCS) by using the projectile tracking filter without any distortion of radar measurements. Under the assumption that the maneuvering between the projectile and the ship equipped with the radar is not quite large, this method is based on the concept of polar-coordinate target tracking, which separates the range estimation filter and the direction cosine estimation filter. Note that using polar-coordinates allows tracking to be performed in the same coordinate system from which the radar line-of-sight(LOS) measurements are obtained, unlike the conventional tracking process in Cartesian. Also, it is easy to implement in real-time and guarantees consistent estimates due to its linear filter structure. With the help of the above method, therefore, the proposed filter is able to improve the overall performance of FCS which requires stability of projectile estimates within a short engagement time. The effectiveness of the presented scheme is validated through computer simulations.

기동 표적 추적을 위한 유전알고리즘 기반 퍼지 모델링 기법 (GA based fuzzy modeling method for tracking a maneuvering target)

  • 노선영;이범직;주영훈;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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    • pp.2702-2704
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    • 2005
  • This paper proposes the genetic algorithm (GA)-based fuzzy modeling method for intelligent tracking of a maneuvering target. When the maneuvering to turn or taking evasive action, the performance of the standard Kalman filter has been degraded because residual between the modeled target dynamics and the actual target dynamics. To solve this problem, the state prediction error is minimized by the intelligent estimation method. Then, this filter is corrected by measurement corrections which is the fuzzy system. The performance of the proposed method is compared with those of the input estimation(IE) technique through computer simulation.

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Target Birth Intensity Estimation Using Measurement-Driven PHD Filter

  • Zhang, Huanqing;Ge, Hongwei;Yang, Jinlong
    • ETRI Journal
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    • 제38권5호
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    • pp.1019-1029
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    • 2016
  • The probability hypothesis density (PHD) filter is an effective means to track multiple targets in that it avoids explicit data associations between the measurements and targets. However, the target birth intensity as a prior is assumed to be known before tracking in a traditional target-tracking algorithm; otherwise, the performance of a conventional PHD filter will decline sharply. Aiming at this problem, a novel target birth intensity scheme and an improved measurement-driven scheme are incorporated into the PHD filter. The target birth intensity estimation scheme, composed of both PHD pre-filter technology and a target velocity extent method, is introduced to recursively estimate the target birth intensity by using the latest measurements at each time step. Second, based on the improved measurement-driven scheme, the measurement set at each time step is divided into the survival target measurement set, birth target measurement set, and clutter set, and meanwhile, the survival and birth target measurement sets are used to update the survival and birth targets, respectively. Lastly, a Gaussian mixture implementation of the PHD filter is presented under a linear Gaussian model assumption. The results of numerical experiments demonstrate that the proposed approach can achieve a better performance in tracking systems with an unknown newborn target intensity.

GMM-TS를 이용한 표적기동분석용 배치구간 및 초기상태 추정 기법 (Batch Time Interval and Initial State Estimation using GMM-TS for Target Motion Analysis)

  • 김우찬;송택렬
    • 제어로봇시스템학회논문지
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    • 제18권3호
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    • pp.285-294
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    • 2012
  • Using bearing measurement only, target motion state is not directly obtained so that TMA (Target Motion Analysis) is needed for this situation. TMA is a nonlinear estimation technique used in passive SONAR systems. Also it is the one of important techniques for underwater combat management systems. TMA can be divided to two parts: batch estimation and sequential estimation. It is preferable to use sequential estimation for reducing computational load as well as adaptively to target maneuvers, batch estimation is still required to attain target initial state vector for convergence of sequential estimation. Selection of batch time interval which depends on observability is critical in TMA performance. Batch estimation in general utilizes predetermined batch time interval. In this paper, we propose a new method called the BTIS (Batch Time Interval and Initial State Estimation). The proposed BTIS estimates target initial status and determines the batch time interval sequentially by using a bank of GMM-TS (Gaussian Mixture Measurement-Track Splitting) filters. The performance of the proposal method is verified by a Monte Carlo simulation study.

레이더 측정 잡음 추정을 통한 기동 표적 추적 성능 향상 (Performance Improvement of Maneuvering Target Tracking with Radar Measurement Noise Estimation)

  • 전대근;은연주;고현;염찬홍
    • 한국항공우주학회지
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    • 제39권1호
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    • pp.25-32
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    • 2011
  • 항공관제용 감시자료 처리시스템에 의한 기동 표적 추적에 있어서 레이더의 측정 잡음 분산은 상태 추정기의 입력으로서, 추적 정확도에 영향을 주는 주요한 요소 중 하나이다. 본 연구에서는 레이더의 측정 잡음 분산을 상수가 아닌 변수로 지정하여, 다중 IMM 필터의 우도함수를 통해 매 시간 측정 잡음 분산을 실시간으로 추정하는 알고리즘을 제시하였다. Monte Carlo 시뮬레이션 결과 측정 잡음 분산 값을 실제 값 대비 5% 이내 수준으로 예측함을 확인하였고, 이를 통해 기동 표적 추적 성능을 향상시킬 수 있음을 확인하였다.

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.

복합모델 다차량 추종 기법을 이용한 차량 주행 제어 (Vehicle Cruise Control with a Multi-model Multi-target Tracking Algorithm)

  • 문일기;이경수
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2004년도 추계학술대회
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    • pp.696-701
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    • 2004
  • A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion, have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

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기동입력의 직접추정에 의한 표적상태 추정 (Target State Estimation by Direct Estimation of Maneuvering Input)

  • 김종화;이만형;황장선
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1989년도 하계종합학술대회 논문집
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    • pp.70-74
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    • 1989
  • To track the target trajectory with maneuvers, unknown maneuvering inputs must be estimated. To do this the direct estimation algorithm using generalized least square technique is developed based on the procedure of failure detection and identification(FDI) theory. Through the simulation using maneuvering target scenario, tracking performance and efficiency of the algorithm developed here are investigated.

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

  • 주재흠
    • 융합신호처리학회논문지
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    • 제14권1호
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    • pp.33-38
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    • 2013
  • 본 논문은 적외선 연속 영상에서 배경 추정 필터와 칼만 필터, 평균 이동 알고리즘을 사용하여 다중 소형 표적들의 소멸과 생성시에도 표적들의 위치를 추적하는 시스템을 제안한다. 배경 추정 영상파 원 영상과의 차 영상을 사용해서 정지 영상에서의 표적 후 정보를 구하고, 칼만 필터와 후보 표적의 분류를 이용하여 다중 표적을 추적 한다. 마지막으로 평균 이동 알고리즘을 사용하여 표적들의 세부 위치를 조정한다. 실험을 통하여 배경 추정 필터들의 성능을 비교 분석하였고, 제안하는 알고리즘이 기존의 추적 시스템과 비교하여 안정적으로 추적이 됨을 확인하였다.

삼각측량법 기반의 정지 표적 정밀 크기 추정기법 연구 (A Study on the Static Target Accurate Size Estimation Algorithm with Triangulation)

  • 정윤식;김진환
    • 제어로봇시스템학회논문지
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    • 제21권10호
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    • pp.917-923
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    • 2015
  • In this paper, the TSE (Triangulation based target Size Estimator) algorithm is presented to estimate static target size at IIR (Imaging Infrared) environment. The size information is important factor for accurate IIR target tracking. But the IIR sensor can't generate distance between missile and target to calculate target size. In order to overcome the problem, we propose TSE algorithm which based on triangulation measurement. The performance of proposed method is tested at target intercept scenario. The experiment results show that the proposed algorithm has suitable performance for the accurate static target size estimating.