• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.867-870
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• 1996

Often an INS has to be aligned in navigation. In these cases it is necessary to obtain some reference information on the state of the aligned INS(Slave) such as its position, its velocity of its angular rate. Usually the reference information is velocity which is supplied by another reference INS. In the alignment state the velocity computed by the reference INS(Master) is compared with that computed by the slave INS and the difference which is indicative of the slave misalignment with respect to the master, is processed by a Kalman filter which estimates misalignment as well as the slave gyro and accelerometer error states. The operation of aligning a slave INS with a master INS comparing quantities computed by both INS is known as transfer alignment. The delivery vehicle performs error these maneuvers enable the TA Kalman filter to separate between the tilt errors and the accelerometer biases which otherwise are unobservable. The basic objective this paper is to study the observability enhancement by ship's maneuvering and matching methods during transfer alignment at sea.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.783-789
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• 2011

Target tracking performance improvement using multi-sensor data fusion is a challenging work. However, biases in the measurements should be removed before various data fusion techniques are applied. In this paper, a bias removing algorithm using measurement data from multi-radar tracking systems is proposed and evaluated by computer simulation. To predict bias estimation performance in various geometric relations between the radar systems and target, a system observability index is proposed and tested via computer simulation results. It is also studied that target tracking which utilizes multi-sensor data fusion with bias-removed measurements results in better performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.515-518
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• 2004

This paper presents a method that improves the performance of the personal voice dialling system in which speaker Independent phoneme HMM's are used. Since the speaker independent phoneme HMM based voice dialing system uses only the phone transcription of the input sentence, the storage space could be reduced greatly. However, the performance of the system is worse than that of the system which uses the speaker dependent models due to the phone recognition errors generated when the speaker Independent models are used. In order to solve this problem, a new method that jointly estimates transformation vectors for the speaker adaptation and transcriptions from training utterances is presented. The biases and transcriptions are estimated iteratively from the training data of each user with maximum likelihood approach to the stochastic matching using speaker-independent phone models. Experimental result shows that the proposed method is superior to the conventional method which used transcriptions only.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.827-833
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• 2016

In this paper, we propose a deep least squares support vector machine (LS-SVM) for regression problems, which consists of the input layer and the hidden layer. In the hidden layer, LS-SVMs are trained with the original input variables and the perturbed responses. For the final output, the main LS-SVM is trained with the outputs from LS-SVMs of the hidden layer as input variables and the original responses. In contrast to the multilayer neural network (MNN), LS-SVMs in the deep LS-SVM are trained to minimize the penalized objective function. Thus, the learning dynamics of the deep LS-SVM are entirely different from MNN in which all weights and biases are trained to minimize one final error function. When compared to MNN approaches, the deep LS-SVM does not make use of any combination weights, but trains all LS-SVMs in the architecture. Experimental results from real datasets illustrate that the deep LS-SVM significantly outperforms state of the art machine learning methods on regression problems.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.258-258
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• 2010

In this work, back bias effects in the program of the silicon-oxide-nitride-oxide-silicon (SONOS) cell using two-step pulse sequence, are investigated. Two-step pulse sequence is composed of the forward biases for collecting the electrons at the substrate terminal and back bias for injecting the hot electrons into the nitride layer. With an aid of the back bias for electron injection, we obtain a program time as short as 600 ns and an ultra low-voltage operation with a substrate voltage of -3 V.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.5
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• pp.533-538
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• 2015

Thermal characterization of individual pixels in microbolometer infrared image sensors is needed for optimal design and improved performance. In this work, we used thermoreflectance microscopy on uncooled microbolometer image sensors to investigate the thermal characteristics of individual pixels. Two types of microbolometer image sensors with a shared-anchor structure were fabricated and thermally characterized at various biases and vacuum levels by measuring the temperature distribution on the surface of the microbolometers. The results show that thermoreflectance microscopy can be a useful thermal characterization tool for microbolometer image sensors.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.114.1-114
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• 2001

GPS Receiver gives pseudorange Doppler and integrated carrier phase for measurements to compute navigation information. Thought the integrated carrier phase can be transfer to the equal domain as pseudorange by multiplying the wave length of the received signal, in order to get position information from the carrier phase measurements the integer ambiguity should be resolved. And differencing technique is generally used to eliminate the common error terms of the integrated carrier phase measurements between robber and server. In short baseline double-differencing operation has effect on elimination the common biases for both stations and thus ambiguity resolution are to be reliable. But the baseline increases, the integer ambiguity resolution is hardly, due to the correlated common error is increase ...

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.86.5-86
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• 2002

The measurement sensor may contain unknown bias in addition to the white noise in the measurement sequence. In this paper, fault detection and diagnosis scheme for the measurement sensor is developed based on the adaptive estimator. The proposed scheme consists of a parallel bank of Kalman-type filters each matched to a set of different possible biases, a mode probability evaluator, an estimate combiner at the outputs of the filters, a bias estimator, and a fault detection and diagnosis logic. Monte Carlo simulations for the PWR steam generator in the nuclear power plant are provided to illustrate the effectiveness of the proposed scheme.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.3
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• pp.175-181
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• 2018

The use of dual-frequency measurements from the Global Navigation Satellite System (GNSS) enables us to observe precise ionospheric total electron content (TEC). Currently, many GNSS reference stations in South Korea provide both GPS and GLONASS data. In the present study, we estimated the grid-based TEC values and relative receiver differential code biases (DCB) from a GNSS network operated by the Korea Astronomy and Space Science Institute. In addition, we compared the diurnal variations in a TEC time series from solutions of the GPS only, the GLONASS only, and combined GPS/GLONASS processing. A significant difference between the GPS only TEC and combined GPS/GLONASS TEC at a specific grid point over South Korea appeared near the solar terminator. It is noted that GLONASS measurements can contribute to observing a variation in ionospheric TEC over high latitude regions.

• Publications of The Korean Astronomical Society
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• v.18 no.1
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• pp.69-74
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• 2003

A CCD camera for the BOES (Bohyunsan Observatory Echelle Spectrograph) has been developed. The camera consists of a 2048 ${\times}$ 4096 format CCD, a SDSU Gen-I CCD controller, and a continuous flow cryostat (CFC) designed by the ESO. In order to control the CCD under SDSU Gen-I controller, the voltage level of all the biases and clocks were lowered by -6V. The CFC showed cooling time of about 10 hour, after which the chip temperature settled down with variation less than ${\pm}1^{\circ}C$. The final chip temperature is around -105$^{\circ}C$ with the setting value for the CFC as -170$^{\circ}C$.