• Title, Summary, Keyword: bearing only tracking

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Efficient Target Tracking with Adaptive Resource Management using a Passive Sensor (수동센서를 이용한 효율적인 표적추적을 위한 적응적 자원관리 알고리듬 연구)

  • Kim, Woo Chan;Lee, Haeho;Ahn, Myonghwan;Lee, Bum Jik;Song, Taek Lyul
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.7
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    • pp.536-542
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    • 2016
  • To enhance tracking efficiency, a target-tracking filter with a resource management algorithm is required. One of the resource management algorithms chooses or evaluates the proper sampling time using cost functions which are related to the target tracking filter. We propose a resource management algorithm for bearing only tracking environments. Since the tracking performance depends on the system observability, the bearing-only tracking is one of challenging target-tracking fields. The proposed algorithm provides the adaptive sampling time using the variation rate of the error covariance matrix from the target-tracking filter. The simulation verifies the efficiency performance of the proposed algorithm.

Nonlinear Bearing Only Target Tracking Filter (방위각 정보만을 이용한 비선형 표적추적필터)

  • Yoon, Jangho
    • Journal of Aerospace System Engineering
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    • v.10 no.1
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    • pp.8-14
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    • 2016
  • The optimal estimation of a bearing only target tracking problem be achieved through the solution of the Fokker-Planck equation and the Bayesian update. Recently, a nonlinear filtering algorithm using a direct quadrature method of moments in which the associated Fokker-Planck equation can be propagated efficiently and accurately was proposed. Although this approach has demonstrated its promising in the field of nonlinear filtering in several examples, the "degeneracy" phenomenon, similar to that which exists in a typical particle filter, occasionally appears because only the weights are updated in the modified Bayesian rule in this algorithm. Therefore, in this paper to enhance the performance, a more stable measurement update process based upon the update equation in the Extended Kalman filters and a more accurate initialization and re-sampling strategy for weight and abscissas are proposed. Simulations are used to show the effectiveness of the proposed filter and the obtained results are promising.

Properties of a bearing-only target tracking filter (방위각 정보만을 이용한 표적추적 필터의 특성연구)

  • 허남수;김인환;황창선;이만형
    • 제어로봇시스템학회:학술대회논문집
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    • pp.789-793
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    • 1990
  • Preprocessing technique of the measurement bearing data is presented to improve the tar-get estimation accuracy for the bearing-only target notion analysis (TMA). Computer simulation is performed to compare with respect to the extended Kalman filter. By computer simulation, the target filter estimator with preprocessing Is both stable and robust to the measurement bearing noise.

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A design of target tracking filter using bearing-only (방위각만을 이용한 표적 추적 필터 설계)

  • 이양원;김경기;김영수
    • 제어로봇시스템학회:학술대회논문집
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    • pp.562-565
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    • 1987
  • This paper addresses the development of the estimation algorithm to acquire target position, velocity and course using bearing-only measurements in two dimensional environment. System state equations are derived from modified polar coordinates instead of existing Cartesian coordinates system. The Extended Kalman Filter is used to constitute the estimation algorithm because of state equation's nonlinearity. The computer simulation is done to verify the performance of derived algorithm. Simulation result showed that estimated state value of filter was converged to the true value in 10 minutes.

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Study on Nonlinear Filter Using Unscented Transformation Update (무향변환을 이용한 비선형 필터에 대한 연구)

  • Yoon, Jangho
    • Journal of Aerospace System Engineering
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    • v.10 no.1
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    • pp.15-20
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    • 2016
  • The optimal estimation of a general continuous-discrete system can be achieved through the solution of the Fokker-Planck equation and the Bayesian update. Due the high nonlinearity of the equation of motion of the system and the measurement model, it is necessary to linearize the both equation. To avoid linearization, the filter based on Fokker-Planck equation is designed. with the unscented transformation update mechanism, in which the associated Fokker-Planck equation was solved efficiently and accurately via discrete quadrature and the measurement update was done through the unscented transformation update mechanism. This filter based on the Direct Quadrature Moment of Method(DQMOM) and the unscented transformation update is applied to the bearing only target tracking problem. The proposed filter can still provide more accurate estimation of the state than those of the extended Kalman filter especially when measurements are sparse. Simulation results indicate that the advantages of the proposed filter based on the DQMOM and the unscented transformation update make it a promising alternative to the extended Kalman filter.

Determination of the nonlinear system observability

  • Hwang, Chun-Sik;Park, Jin-Ok
    • 제어로봇시스템학회:학술대회논문집
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    • pp.957-962
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    • 1990
  • A method to determine nonlinear system observability will be introduced here. For the determination of the deterministic nonlinear system observability two conditions connectedness and univalence, are developed and used. Depending on how the conditions are satisfied, observability is classified in three categories : observability in the strict sense, wide sense, and the unobservable case. Including simple linear and nonlinear system example an underwater acoustical locaization tracking nonlinear system, the bearing-only tracking example is analyzed.

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Target Motion Analysis for Active/Passive Mixed-Mode Sonar Systems

  • Taek, Lim-Young;Lyul, Song-Taek
    • 제어로봇시스템학회:학술대회논문집
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    • pp.172.5-172
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    • 2001
  • Target Motion Analysis(TMA) for Passive Sonar Systems with bearing-only measurements needs to enhance system observability to improve target tracking performance by ownship maneuvering. However, tracking problem incurred by weak observaility result in slow convergence of the target estimates. On the other hand, active sonar systems do not have problem associated with system observaility. However, it drawback related to system survivability. In this paper, the algorithm that could be used in Active/passive Mixed-Mode Sonar Systems is proposed to analyze maneuvering target motion and to improve TMA performance. The proposed TMA algorithm is tested by a series of computer simulation runs and the results ...

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Object Tracking in 3-D Space with Passive Acoustic Sensors using Particle Filter

  • Lee, Jin-Seok;Cho, Shung-Han;Hong, Sang-Jin;Lim, Jae-Chan;Oh, Seong-Jun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.9
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    • pp.1632-1652
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    • 2011
  • This paper considers the object tracking problem in three dimensional (3-D) space when the azimuth and elevation of the object are available from the passive acoustic sensor. The particle filtering technique can be directly applied to estimate the 3-D object location, but we propose to decompose the 3-D particle filter into the three planes' particle filters, which are individually designed for the 2-D bearings-only tracking problems. 2-D bearing information is derived from the azimuth and elevation of the object to be used for the 2-D particle filter. Two estimates of three planes' particle filters are selected based on the characterization of the acoustic sensor operation in a noisy environment. The Cramer-Rao Lower Bound of the proposed 2-D particle filter-based algorithm is derived and compared against the algorithm that is based on the direct 3-D particle filter.

Improvement of Target Motion Analysis for a Passive Sonar System with Measurement Bias Estimation (측정각 Bias 보상을 통한 수동소나체계의 표적기동분석 성능 향상 연구)

  • Yoo, Phil-Hoon;Song, Taek-Lyul
    • Proceedings of the KIEE Conference
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    • pp.2011-2013
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    • 2001
  • In this paper the MMAE(Multiple Model Adaptive Estimation) algorithm using the MGEKF(Modified Gain Extended Kalman Filter) of which modes are set to be measurement biases is proposed to enhance the performance of target tracking with bearing only measurements. The state are composed of relative position, relative velocity and taregt acceleration. The mode probability is calculated from the bearing only measurements from the HMS(Hull-Mounted Sonar). The proposed algorithm is tested in a series of computer simulation runs.

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Experimental calibration of forward and inverse neural networks for rotary type magnetorheological damper

  • Bhowmik, Subrata;Weber, Felix;Hogsberg, Jan
    • Structural Engineering and Mechanics
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    • v.46 no.5
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    • pp.673-693
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    • 2013
  • This paper presents a systematic design and training procedure for the feed-forward back-propagation neural network (NN) modeling of both forward and inverse behavior of a rotary magnetorheological (MR) damper based on experimental data. For the forward damper model, with damper force as output, an optimization procedure demonstrates accurate training of the NN architecture with only current and velocity as input states. For the inverse damper model, with current as output, the absolute value of velocity and force are used as input states to avoid negative current spikes when tracking a desired damper force. The forward and inverse damper models are trained and validated experimentally, combining a limited number of harmonic displacement records, and constant and half-sinusoidal current records. In general the validation shows accurate results for both forward and inverse damper models, where the observed modeling errors for the inverse model can be related to knocking effects in the measured force due to the bearing plays between hydraulic piston and MR damper rod. Finally, the validated models are used to emulate pure viscous damping. Comparison of numerical and experimental results demonstrates good agreement in the post-yield region of the MR damper, while the main error of the inverse NN occurs in the pre-yield region where the inverse NN overestimates the current to track the desired viscous force.