• 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 the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.739-747
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• 2010

In this paper, we propose new data association method called the Highest Probability Data Association(HPDA) using a Signal Amplitude information ordering method applied to active sonar tracking and track initiation in cluttered environment. The performance of HPDA is tested in a series of Monte Carlo simulations runs and is compared with the existing Probabilistic Data Association with Amplitude Information(PDA-AI) for active sonar tracking in clutter. The proposed HPDA algorithm is also applied to automatic track initiation in clutter and its performance is compared with the existing IPDA-AI algorithm.