• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.6
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• pp.38-46
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• 2008

A distributed system for tracking multiple targets with a pair of multifunction radars is proposed and implemented. The system performs track-to-track association and track-to-track fusion at the fusion center to form fused tracks. The association and fusion are performed using target state information linked via communication nodes from a radar at a remote location. Many factors can affect the track-to-track association and fusion performances. They include delays in data transmission buffer of the remote radar, the error in estimating time-stamp of the remote radar, and the gating in track-to-track association. The effects on association and fusion performances due to these factors are investigated through extensive numerical simulations.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.1
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• pp.85-92
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• 2008

An architecture for multiple radar tracking systems can be broadly categorized according to the methods in which the tracking functions are performed : central-level tracking and distributed tracking. In the central-level tracking, target tracking is performed using observations from all radar systems. This architecture provides optimal solution to target tracking. In distributed tracking, tracking is performed at each radar system and the composite track information is formed through track fusion integrating multiple radar-level tracks. Track-to-track fusion and track-to-track association are required to perform in this architecture. In this paper, issues and recent research on the two tracking architectures are surveyed.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.4
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• pp.513-518
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• 2012

In this paper, we proposed a method of fast track merging which is the foundation of track to track association technique. The existing method of track merging is performed throughout comparison between tracks to tracks. Therefore, it has heavy calculation time. In our research, we developed a method for fast clustering by using nearest neighbor measurement identification. The simulation results show that the proposed method is more faster than previous method about 3.3%. We expect that this method could be effectively used in multi-target tracking particularly in heavy clutter environment.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.3
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• pp.334-342
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• 2012

Data association is important technology which designate final destination in the target tracking. The joint probabilistic data association(JPDA) algorithm provides excellent ability to maintain track on multiple targets. Currently, it is not easily implemented in real time because of track coalescence & switch. The aim of this paper is to develop probabilistic filters that increase JPDA's sensitivity and decrease track coalescence & switch in a cluttered environments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.681-691
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• 2017

In the clutter environment, it is necessary to update the target tracking filter by detecting the target signal among many measured value data obtained via the radar system, the track does not diverge, and tracking performance is maintained. The method of associating the measurement most relevant to the target track among numerous measurement values is referred to as data association. PSNF and PSNF-m are data association methods of SN-series. In this paper, we provide an IPSNF-m(Integrated Probabilistic Strongest Neighbor Filter-m) algorithm with a track management method based on the track existence probability in PSNF-m algorithm. This algorithm considers not only the presence of the target but also the case where the target is present but not detected. Calculating the probability of each caseenables efficient management. In order to verify the performance of the proposed IPSNF-m, the track existence probability of the IPSNF algorithm applying the track management technique to PSNF, which is known to have similar performance to PSNF-m, is derived. Through simulation in the same environment, we compare and analyze the proposed algorithm with RMSE, Confirmed True Track, and Track Existence Probability that show better performance in terms of track retention and estimation than the existing PSNF-m and IPSNF algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.141-146
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• 1992

Joint probabilistic data association filter(JPDAF) for multi-target tracking was developed for real-time implementation, while it abandoned an algorithm for track initiation. In this paper, we propose three features for track initiation that can be adapted to the JPDA filter. In addition, with the proposed approaches, the performance of track maintenance is evaluated in the case of tracks being near. To eliminate the abundant false tracks, we exploit the simple method using the state error covariances. Simulations are performed to demonstrate the efficiency of the proposed approaches.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.733-739
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• 2008

This article proposes algorithms for the automatic initiation of the tracks of maneuvering targets in cluttered environments. These track initiation algorithms consist of IPDA-AI(Integrated Probabilistic Data Association-Amplitude Information) and MPDA(Most Probable Data Association) in an Interacting Multiple Model(IMM) configuration, and they are referred to as the IMM-IPDAF-AI and IMM-MPDA respectively. The IMM portion consists of several filters based on different dynamical models to handle target maneuvers. Each of the filters utilizes an IPDA-AI(or MPDA) algorithm to deal with the problem of track existence in the presence of clutter. Although the primary purpose of this study is to deal with the track initiation problem, the IMM-IPDAF-AI and IMM-MPDA can also be used for the maintenance of existing tracks and the termination of tracks for targets when they disappear. For illustrative purposes, simulation is used to compare the performance of the algorithms proposed to other track formation algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.126-131
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• 2014

This paper is concerned with a track management method for a naval combat system which receives the tracks information from multi-sensors and multi-tactical datalinks. Since the track management of processing the track information from diverse sources can be formulated as a data fusion problem, this paper will deal with the data fusion architecture, track association and track information determination algorithm for the track management of naval combat systems.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.10
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• pp.982-990
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• 2010

In a target tracking system using image information from a CCD (Charged Couple Device) or an IIR (Imaging Infra-red) sensor, occluded targets can result in track losses. If the target is occlued by background objects such as buildings or trees, probability of track existence will be reduced sharply and track will be terminated due to track maintenance algorithms. This paper proposes data association algorithm based on target existence for the robust tracking performance. we suggest the HPDA (Highest Probability Data Association) algorithm based on target existence and the tracking performance is compared with the established method based on target perceivability. Image tracking simulation that utilizes virtual 3D images and real IR images is employed to evaluate the robustness of the proposed tracking algorithm.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.4
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• pp.411-421
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• 1992

In the conventional track while scan (TWS) system, there are two major functions to be performed : detection and tracking. These two functions are normally designed and optimised independently. So TWS algorithm ignores the available decision features that can help in resolving the plot-to-track association ambiguity. Therefore conventional TWS system cna't track the targets in a densed multi-target environment. This paper presents a new TWS algorithm for multi-target track to solve the existing TWS system problem in clutter environment. The algorithm proposed in this paper is derived by modifying the part of joint probabilistic data association (JPDA) algotithm to get the one to one correspondence instead of multiple correspondence and combined with maneuvering detection logic so that it could also track the low maneuvering targets. Simulations to confirm the performance are done in crossing, parallel and maneuvering target. The proposed algorithm was successfully tracking targets above target situations.