• The Journal of the Acoustical Society of Korea
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• v.18 no.6
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• pp.9-16
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• 1999

As a part of target motion analysis(TMA) with highly noisy bearings-only measurements from a passive sonar system, a nonlinear batch estimator is proposed to provide the initial estimates to a sequential estimator called the modified gain extended Kalman filter(MGEKF). Based on the system observability analysis of passive target tracking, a practical and effective method is suggested to determine the observer maneuvers for improved TMA performance through system observability enhancing. Also suggested is a method to determine observer location for enhanced system observability at the initial phase of TMA from various engagement boundaries which represent the relationship between observer-target relative geometrical data and system observability. The proposed TMA methods are tested by a series of computer simulation runs.

• Journal of Advanced Navigation Technology
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• v.6 no.2
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• pp.119-129
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• 2002

Maneuvering targets are difficult to track for the Kalman filter since the target model of tracking filter might not fit the real target trajectory and the statistical characteristics of the target maneuver are unknown in advance. In order to track such a highly maneuvering target, several schemes have been proposed and improved the tracking performance in some extent. Among those tracking schemes the Input Estimation (IE), Variable Dimension (VD) and Turning Acceleration Estimator (TAE) became popular. However, so far their tracking performances were analyzed individually and were not compared. In this paper, the tracking performances of the typical IE, VD and TAE schemes for a maneuvering target are compared. Monte-Carlo Simulations for three maneuvering profiles are carried out and the results are analyzed towards practical applications.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.562-572
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• 2003

A matched-target model inversion method was developed for a passive sonar to estimate the position of moving targets. Based on the well known matched-field processing in underwater acoustics, the method finds target position by matching the measured target directions and frequencies with the corresponding values of the proposed target model. For the efficient and accurate estimations, the parameter searching was accomplished using a hybrid optimizing method, which first starts with a global optimization such as generic algorithm or simulated annealing then applies a local optimization of a simple down hill algorithm. The suggested method was testified using simulations for three different moving scenarios. The simulation results showed that the method is robust in convergence, even under the situation of over 5 times standard deviation of Gaussian distribution of measured error, and is practical in calculation time as well.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.855-861
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• 2007

In real system application, the IMM-based position tracking algorithm requires robust performance, less computing resources and easy design procedure with respect to the uncertain target maneuvering, To solve these problems, an adaptive fuzzy interacting multiple model (AFIMM) algorithm, which is based on the well-defined basis sub-models and well-adjusted mode transition probabilities (MTPs), is proposed. Simulation results show that the proposed algorithm effectively solves the problems in the real system application of the IMM-based position tracking algorithm.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.82-89
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• 2012

This paper presents the intelligent tracking algorithm for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. Fuzzy c-mean clustering and predicted impact point are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by fuzzy c-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. The filtering process in a series of the algorithm which estimates the target value recognize the nonlinear maneuvering target as linear one because the filter recognize only remained noise by extracting acceleration from the positional error. After filtering process, we get the estimates target by compensating extracted acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. To maximize the effectiveness of the proposed system, we construct the multiple model structure. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.602-605
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• 1995

In this paper, we provide the new alogorithm for maneuvering target tracking in clutter environment using perception net. The perception net, as a structural representation of the sensing capabilities of a system, may supply the constraints that target must be satisfied with. The results form perception net applying to IMMPDA are compared with those obtained from IMMPDA.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.06a
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• pp.365-367
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• 2013

해상감시레이더는 관제지역의 해상교통정보를 수집하는 해상교통관제시스템의 주요 센서로, 다양한 운동 특성을 갖는 선박의 안정적인 추적과 위치, 속도, 침로 등의 정확한 정보를 제공하는 것은 VTS 성능 개선 및 서비스 고도화에 매우 중요한 요소 기술이다. 본 논문에서는 해상교통관제시스템에서 다양한 기동 특성을 갖는 선박의 정확한 추적을 위하여 상호작용 다중필터(IMM) 추정기를 이용한 추적 알고리즘을 설계하고, 모의실험을 통하여 필터 뱅크의 구성에 따른 성능 비교 및 분석을 수행한다.

• Journal of Advanced Navigation Technology
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• v.7 no.2
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• pp.217-226
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• 2003

Recently Lim has proposed a linear, recursive, unbiased minimum variance filter for a maneuvering target based on the maneuver dynamics modeled as a jump process of Poisson-type. In the proposed filter it was assumed that the state transition parameters of the jump used for target maneuver modeling are a priori known to the filter. However, in most cases they are not known in practice. In this paper, we consider the influence of system (target) modeling error on the performance of the proposed tracking filter arising from the maneuver tracking. For qualitative analysis Monte-Carlo simulations are carried out against employing the maneuver model with different state transition parameters from the actual values.

• Journal of Advanced Navigation Technology
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• v.4 no.1
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• pp.50-66
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• 2000

For a long time target maneuvers in tracking problem have been a difficult task to handle. Once a maneuvering such as abrupt change in target accelerations occur, the tracking fiter no longer yields a reasonable estimate of the target position. In order to resolve this cumbersome maneuvering problem. Advanced methods have here proposed : Colored noise, IE(Input Estimation), VD(Variable Dimension), IMM(Interaction Multiple Model), Jump-type processes and jerk model, etc. In this paper, tracking performance of the jerk model is analyzed. Jerk model in which the derivative of target acceleration is included as a state recently attracted considerable attraction. Firstly 3-dimensional Kalman filter is described on the basis of jerk model. Then using this filter, Monte-Carlo simulations are carried out and the filter formance with respect to the variation of jerk time-constant is analyzed. Especially, since jerk model's transient performance is expected to be poor, the performance of analysis of transient response of the model is included too.

• Journal of IKEEE
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• v.11 no.4
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• pp.137-144
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• 2007

Fire Control System(FCS) errors can be classified as hardware errors and software errors, and one of the software errors is from target tracking filter which estimates target's location, velocity, acceleration, and so on. It affects function of ballistic calculation equipment significantly. For gun to form predicted hitting point accurately and enhance hitting rate, we need status information of target's future location. Target tracking filter algorithms consist of Single Singer Model, Fixed Gain filter algorithm, IMM, PBIMM and so on. This paper will design IMM tracking filer, which is going to be! applied to domestic warship. Target tracking filter using CV model, Song model and CRT model for IMM tracking filter is made, and tracking ability is analyzed through Monte-Carlo simulation.