• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.559-566
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• 2006

In the real system application, the interacting multiple model (IMM) based algorithm requires less computing resources as well as a good performance with respect to the various target maneuverings. And it further requires an easy design procedure in terms of its structures and parameters. To solve these problems, a fuzzy interacting multiple model (FIMM) algorithm, which is based on the basis sub-models defined by considering the maneuvering property and the time-varying mode transition probabilities designed by using the mode probabilities as inputs of a fuzzy decision maker, is proposed. To verify the performance of the proposed algorithm, airborne target tracking is performed. Simulation results show that the FIMM algorithm solves all problems in the real system application of the IMM based algorithm.

• International Journal of Control, Automation, and Systems
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• v.5 no.3
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• pp.307-316
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• 2007

In real system application, the interacting multiple model (IMM) based algorithm operates with the following problems: it requires less computing resources as well as a good performance with respect to the various target maneuvering, it requires a robust performance with respect to the time-varying measurement noise, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an adaptive fuzzy interacting multiple model (AFIMM) algorithm, which is based on the basis sub-models defined by considering the maneuvering property and the time-varying mode transition probabilities designed by using the mode probabilities as the inputs of the fuzzy decision maker whose widths are adjusted, is proposed. To verify the performance of the proposed algorithm, a radar target tracking is performed. Simulation results show that the proposed AFIMM algorithm solves all problems in the real system application of the IMM based algorithm.

• 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 Korea Institute of Military Science and Technology
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• v.8 no.3 s.22
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• pp.24-32
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• 2005

This paper describes the tracking filter performance for Naval Gun Ballistic Computation Unit(BCU). BCU needs tracing filter for gun firing. Using data of tracking sensor, BCU calculates the future position of Target and Gun order in the time of flight. In this paper, tracing filter is designed with interacting multiple model(IMM). The tracking algorithm based on the IMM requirers a considerable number of sub-model for the various maneuvering target in order to have a good performance. But, in the case of ship target, the maneuvering is restricted compared with the air target. Considering the maneuvering properties and adjusting the mode transition probabilities and the process noise of sub-model, We designed the IMM3 algorithm for Naval tracking filter with three sub-model.

• Bulletin of the Korean Chemical Society
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• v.12 no.4
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• pp.387-392
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• 1991

We present a theoretical investigation of the inelastic atom-surface phonon scattering for a model He-Si(100) system by the classical trajectory-quantum forced oscillator(DECENT) method. Single and multi-phonon transition probabilities of normal modes are calculated for several initial beam orientations and several initial kinetic energies. In order to understand surface structure effects, the calculation has been done on both reconstructed and unreconstructed surfaces of the He/Si(100) system. The origin of mode specificity for energy transfer is discussed. The contribution of one, two, and multi-phonon events to the total energy transfer between 0 and 600 K is also given.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.4 s.19
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• pp.5-12
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• 2004

The tracking algorithm based on the interacting multiple model(IMM) requires a considerable number of sub-models for the various maneuvering targets in order to have a good performance. But it is not feasible to use the nm algorithm in the real system because of the computational burden. Therefore, we need an algorithm which requires less computing resources while maintaining a good performance. In this paper, we propose a fuzzy interacting multiple model algorithm(FIMMA) for the tracking of maneuvering targets, which uses a minimal number of sub-models by considering the maneuvering properties and adjusts the mode transition probabilities by using the mode probability as a fuzzy input. In order to verify the performance of FIMMA, the developed algorithm is applied to the tracking of i borne targets. Simulation results show that the FIMMA is very effective in the tracking of maneuvering targets.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3A
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• pp.205-214
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• 2011

In 3rd generation project partnership long term evolution, wireless multicast techniques which send the same data to multiple users under single frequency networks have attracted much attention. In the multicast system, the transmission mode needs to be selected for efficient data transfer while satisfying the multicast coverage requirement. To achieve this, users' channel state information (CSI) should be available at the transmitter. However, it requires too much uplink feedback resource if all the users are allowed to transmit their CSI at all the time. To solve this problem, in this paper, the multicast coverage prediction is suggested. In the proposed algorithm, each user measures its transition probabilities between the success and the fail state of the decoding. Then, it periodically transmits its CSI to the basestation. Using these feedbacks, the basestation can predict the multicast coverage. From the simulation results, we demonstrate that the proposed scheme can predict the multicast system coverage.