• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.211-211
• /
• 2000

The multiple targets tracking problem has been one of main issues in the radar applications area in the last decade. Besides the standard Kalman filtering, various methods including the variable dimension filter, input estimation filter, interacting multiple model (IMM) filter, federated variable dimension filter with input estimation, probable data association (PDA) filter etc. have been proposed to address the tracking and sensor fusion issues. In this paper, two existing tracking algorithms, i.e. the IMMPDA filter and the variable dimension filter with input estimation (VDIE), are combined for the purpose of improving the tracking performance of maneuvering targets in clutter. To evaluate the tracking performance of the proposed algorithm, three typical maneuvering patterns i.e. Waver, Pop-Up, and High-Diver motions, are defined and are applied to the modified IMMPDA filter considered as well as the standard IMM filter. The smaller RMS tracking errors, in position and velocity, of the modified IMMPDA filter than the standard IMM filter are demonstrated through computer simulations.

• Proceedings of the KIEE Conference
• /
• 1998.07b
• /
• pp.592-594
• /
• 1998

In the single-input and single-output system, the parameter of plant is scalar polynomial, but in the multiple input and multiple output, it accompanies, being matrix polynomial, the consideration of observable conrolability index or problems of non-commutation in matrix polynomial as well as degree, and it is more complex to deal with. Therefore, it is thought that a full reserach on the single-input and single-output system is not made. This reserach propose that problems of minimum variance self-tuning regulator of multivariable system and pole placement self-tuning regulator.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.37 no.4
• /
• pp.239-244
• /
• 2014

The conventional clustering approaches are mostly based on minimizing total dissimilarity of input and output. However, the clustering approach may not be helpful in some cases of clustering decision making units (DMUs) with production feature converting multiple inputs into multiple outputs because it does not care converting functions. Data envelopment analysis (DEA) has been widely applied for efficiency estimation of such DMUs since it has non-parametric characteristics. We propose a new clustering method to identify groups of DMUs that are similar in terms of their input-output profiles. A real world example is given to explain the use and effectiveness of the proposed method. And we calculate similarity value between its result and the result of a conventional clustering method applied to the example. After the efficiency value was added to input of K-means algorithm, we calculate new similarity value and compare it with the previous one.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.5
• /
• pp.121-127
• /
• 2013

When input power is small, nonideal symmetric balance incomplete block design(BIBD) code design is effective in the spectral-amplitude-code(SAC) optical code-division multiple-access (OCDMA) system. But the number of simultaneous users is not sufficient. To overcome this property, we propose 2-D BIBD codes, where nonideal BIBD codes are used as spectral code and ideal BIBD codes are used as spatial codes. Analytical results show that the number of simultaneous users increases significantly.

• Proceedings of the IEEK Conference
• /
• 2007.07a
• /
• pp.481-482
• /
• 2007

This paper demonstrates OFDM with adaptive modulation applied to Multiple-Input Multiple-Output (MIMO) systems. We apply an optimization algorithm to obtain a bit and power allocation for each subcarrier assuming instantaneous channel knowledge. The analysis and simulation is considered in two stages. The first stage involves the application of a variable-rate variable-power MQAM technique for a Single-Input Single-Output(SISO) OFDM system. This is compared with the performance of fixed OFDM transmission where a constant rate is applied to each subcarrier. The second stage applies adaptive modulation to a general MIMO system by making use of the Singular Value Decomposition to separate the MIMO channel into parallel subchannels. For a two-input antenna, two-output antenna system, the performance is compared with the performance of a system using selection diversity at the transmitter and maximal ratio combining at the receiver.

• Proceedings of the KIEE Conference
• /
• 2003.07d
• /
• pp.2085-2087
• /
• 2003

A new interacting multiple model (IMM) method based on intelligent input estimation (IIE) is proposed for tracking a maneuvering target. In the proposed method, the acceleration level of each sub-filter is determined by IIE using the fuzzy system, which is optimized by the genetic algorithm (GA). The tracking performance of the proposed method is compared with those of the input estimation (IE) technique and the adaptive interacting multiple model (AIMM) method in computer simulations.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.11a
• /
• pp.999-1004
• /
• 2004

In this study, we identify contribution of structure-borne-noise of vehicle HVAC system using Multi-Dimensional spectral analysis (MDSA) method. Firstly, to identify the applicability of MDSA method, the case of HVAC system was modeled with four input / single output system. The four inputs which is given vibration data is composed of blower, evaporator, heater and duct. The single output is noise data from driver's seat. When the blower motor is operating, we analyze the contributions of four input / single output. As a result of experiment, we identify efficiency of systems modeled with four input / single output through ordinary coherence function (OCF) and multiple coherence function (MCF).

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.11
• /
• pp.2298-2304
• /
• 2015

In this paper, we provide a new approach which optimizes the vertical tilting angle of the base station for multi-cell multiple-input single-output (MISO) downlink active antenna systems (AAS). Instead of the conventional optimal algorithm which requires an exhaustive search, we propose simple and near optimal algorithms. First, we represent a large system approximation based vertical beamforming algorithm which is applied to the average sum rate by using the random matrix theory. Next, we suggest a signal-to-leakage-and-noise ratio (SLNR) based vertical beamforming algorithm which simplifies the optimization problem considerably. In the simulation results, we demonstrate that the performance of the proposed algorithms is near close to the exhaustive search algorithm with substantially reduced complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.7
• /
• pp.2614-2632
• /
• 2015

A multiple symbol detection (MSD) algorithm is proposed relying on soft information for ultra-wideband systems, where differential space-time block code is employed. The proposed algorithm aims to calculate a posteriori probabilities (APP) of information symbols, where a forward and backward message passing mechanism is implemented based on the BCJR algorithm. Specifically, an MSD metric is analyzed and performed for serving the APP model. Furthermore, an autocorrelation sampling is employed to exploit signals dependencies among different symbols, where the observation window slides one symbol each time. With the aid of the bidirectional message passing mechanism and the proposed sampling approach, the proposed MSD algorithm achieves a better detection performance as compared with the existing MSD. In addition, when the proposed MSD is exploited in conjunction with channel decoding, an iterative soft-input soft-output MSD approach is obtained. Finally, simulations demonstrate that the proposed approaches improve detection performance significantly.

• Journal of Satellite, Information and Communications
• /
• v.10 no.1
• /
• pp.22-28
• /
• 2015

In this paper, we propose a new computationally efficient joint iterative multi-input multi-output (MIMO) detection scheme using a soft interference cancellation and minimum mean squared-error (SIC-MMSE) method. The critical computational burden of the SIC-MMSE scheme lies in the multiple inverse operations of the complex matrices. We find a new way which requires only a single matrix inversion by utilizing the Taylor series expansion of the matrix, and thus the computational complexity can be reduced. The computational complexity reduction increases as the number of antennas is increased. The simulation results show that our method produces almost the same performances as the conventional SIC-MMSE with reduced computational complexity.