• ETRI Journal
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• v.42 no.1
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• pp.26-35
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• 2020

Herein, we consider uplink multiuser massive multiple-input multiple-output systems when multiple users transmit information symbols to a base station (BS) by applying simple space-time block coding (STBC). At the BS receiver, two detection filters for each user are used to detect the STBC information symbols. One of these filters is for odd-indexed symbols and the other for even-indexed symbols. Using constrained output variance metric minimization, we first derive a special relation between the closed-form optimal solutions for the two detection filters. Then, using the derived special relation, we propose a new blind adaptive algorithm for implementing the minimum output variance-based optimal filters. In the proposed adaptive algorithm, filter weight vectors are updated only in the region satisfying the special relation. Through a theoretical analysis of the convergence speed and a computer simulation, we demonstrate that the proposed scheme exhibits faster convergence speed and lower steady-state bit error rate than the conventional scheme.

• Korean Journal of Optics and Photonics
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• v.14 no.5
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• pp.555-564
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• 2003

WDM thin film filters for fiber optical communication were designed using Fabry-Prot type multiple cavity filters and an equivalent thin film technique. As the number of cavities in multiple cavity filters increases, it becomes difficult to design the filters due to a great number of variables (the number of cavities, period of reflectors, order of spacers). To solve the problem of design, we treated the fewest variables, regarding symmetrical thin films as equivalent layers, and we applied structural and numerical formulas based on an analysis method of multiple cavity filters. The equivalent thin film technique was able to provide systematic and quantitative design of the WDM thin film filters.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.6
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• pp.413-419
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• 2003

The objective of this paper is to survey and put in perspective the existing methods of dynamic filter development. This includes theories and practices for linear and nonlinear filters, multiple model filters, and data association methods for tracking in multitarget environment. The presentation of this paper is motivated by recent surge of interest in the area of designing feedback control systems with reduced number of sensors, detection and identification of abrupt changes, and multitarget tracking in clutter. It is hoped to be useful in view of the need to take a grasp of existing techniques before using them in practice and developing new techniques.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.539-544
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• 2004

We investigate a visual object tracking algorithm based upon particle filters, namely CONDENSATION, in order to combine multiple observation models such as active contours of digitally subtracted image and the particle measurement of object color. The former is applied to matching the contour of the moving target and the latter is used to independently enhance the likelihood of tracking a particular color of the object. Particle filters are more efficient than any other tracking algorithms because the tracking mechanism follows Bayesian inference rule of conditional probability propagation. In the experimental results, it is demonstrated that the suggested contour tracking particle filters prove to be robust in the cluttered environment of robot vision.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.859-866
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• 2009

The article discusses an issue of estimating the airspeed of an autonomous flying vehicle. Airspeed is the difference between ground speed and wind speed. It is desirable to know any two among the three speeds for navigation, guidance and control of an autonomous vehicle. For example, ground speed and position are used to guide a vehicle to a target point and wind speed and airspeed are used to maximize flight performance such as a gliding range. However, the target vehicle has not an airspeed sensor but a ground speed sensor (GPS/INS). So airspeed or wind speed has to be estimated. Here, airspeed is to be estimated. A vehicle's dynamics and its dynamic parameters are used to estimate airspeed with attitude and angular speed measurements. Kalman filter is used for the estimation. There are also two major sources arousing a robust estimation problem; wind speed and altitude. Wind speed and direction depend on weather conditions. Altitude changes as a vehicle glides down to the ground. For one reference altitude, multiple model Kalman filters are pre-designed based on several reference airspeeds. We call this group of filters as a cluster. Filters of a cluster are activated simultaneously and probabilities are calculated for each filter. The probability indicates how much a filter matches with measurements. The final airspeed estimate is calculated by summing all estimates multiplied by probabilities. As a vehicle glides down to the ground, other clusters that have been designed based on other reference altitudes are activated. Some numerical simulations verify that the proposed method is effective to estimate airspeed.

• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.556-561
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• 2011

It is generally known that particle filters can produce consistent target tracking performance in comparison to the Kalman filter for non-linear and non-Gaussian systems. In this paper, I propose a Rao-Blackwellized multiple model particle filter(RBMMPF) to enhance computational efficiency of the particle filters as well as to reduce sensitivity of modeling. Despite that the Rao-Blackwellized particle filter needs less particles than general particle filter, it has a similar tracking performance with a less computational load. Comparison results for performance is listed for the using single sensor information RBMMPF and using multisensor data fusion RBMMPF.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.21-28
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• 2016

In this paper, we propose a fast small target detection method using multiple filters, and describe system implementation using IPP libraries. To detect small targets in Infra-Red images, it is mandatory that you should apply a filter to eliminate a background and identify the target information. Moreover, by using a suitable algorithm for the environments and characteristics of the target, the filter must remove the background information while maintaining the target information as possible. For this reason, in the proposed method we have detected small targets by applying multi area(spatial) filters in a low luminous environment. In order to apply the multi spatial filters, the computation time can be increased exponentially in case of the sequential operation. To build this algorithm in real-time systems, we have applied IPP library to secure a software optimization and reduce the computation time. As a result of applying real environments, we have confirmed a detection rate more than 90%, also the computation time of the proposed algorithm have been improved about 90% than a typical sequential computation time.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.476-483
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• 2010

If the data are pre-whitened, then gradient adaptive algorithms which are simpler than higher order statistics algorithms can be used in adaptive blind signal estimation. In this paper, we propose a blind subband affine projection algorithm for multiple-input multiple-output adaptive equalization in the blind environments. All of the adaptive filters in subband affine projection equalization are decomposed to polyphase components, and the coefficients of the decomposed adaptive sub-filters are updated by defining the multiple cost functions. An infinite impulse response filter bank is designed for the data pre-whitening. Pre-whitening procedure through subband filtering can speed up the convergence rate of the algorithm without additional computation. Simulation results are presented showing the proposed algorithm's convergence rate, blind equalization and blind signal separation performances.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.36-41
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• 2018

An image intensifying device is equipment that makes weak objects visible in a dark environment, such as making nighttime bright enough to let objects be visually observed. It is possible to obtain a clear image by amplifying the light in the presence of a certain amount of weak light. However, in an extremely low-light environment, where even moonlight is not present, there is not enough light to amplify anything, and the sharpness of the screen deteriorates. In this paper, a method is proposed to improve image quality by using multiple filters and anisotropic diffusion for output noise of the image-intensifying device in extreme low-light environments. For the experiment, the output of the image-intensifying device was obtained under extremely low-light conditions, and signal processing for improving the image quality was performed. The configuration of the filters for signal processing uses anisotropic diffusion after applying a median filter and a Wiener filter for effective removal of salt-and-pepper noise and Gaussian noise, which constitute the main noise appearing in the image. Experimental results show that the improvement visually enhanced image quality. Both peak signal-to-noise ratio (PSNR) and SSIM, which are quantitative indicators, show improved values.

• Journal of Broadcast Engineering
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• v.15 no.5
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• pp.617-630
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• 2010

At 37th VCEG meeting in Jan. 2009, Toshiba proposed Quadtree-based Adaptive Loop Filter (QALF). The basic concept of QALF is to apply Wiener filter to decoded image after the conventional deblocking filter and to represent the filter on/off flag data for each basic filtering unit in a more efficient way of quadtree structure. QALF could enhance the compression performance of around more than 9%, but the structure of one filter for a decoded frame leaves room for further improvement in the sense that optimal filter for one region of a frame could quite different from the optimal filter for other parts of a picture. This paper proposes multiple adaptive loop filters for better utilization of local characteristics of decoded frame to optimize the region-based Wiener filters. Additional filters, proposed in this paper, cover separate spatial area of each decoded frame according to the performance of previously designed filter(s) to provide the flexibility of rate-distortion based selection of the number of filters.