• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.599-609
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• 2010

Many of financial data are explained via diffusion models in modern financial research. Various types of estimation methods of diffusion processes were suggested by many authors. In this paper, we tested the properties of the NLL estimation method, suggested by Shoji and Ozaki (1998), of diffusion processes in the view of the bias and variance of the estimators and applied the method to estimate the model parameters for the U.S. fedral funds rate data and Korean inter-bank exchange rate data. By simulation study we showed that the NLL method provides relatively good estimators, in the meaning that the estimator has less bias than the Euler method, while keeping the variance similar level. We also provide the NLL estimates of U.S fedral funds rate data and Korean inter-bank exchange rate data.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.2
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• pp.155-162
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• 2016

TASS(Towed Array Sonar System) is a sonar system which tows the sensor array behind a platform. Array shape is generally assumed to be a straight line. But the array shape is often distorted by oceanic current or platform maneuvering which causes the performance loss of signal processing method like beamforming. So array shape estimation methods are needed. Typically the method based on Kalman filter using heading sensor is used. In practice, the measurement is corrupted by biases which are caused by rotation of the tow cable, varying magnetic fields and slowly varying stresses in the mechanical construction. Although they can't be calibrated but can be estimated. In this paper, we suggest the array shape estimation method based on Kalman filter compensating the sensor biases.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6C
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• pp.505-511
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• 2008

The global navigation satellite system (GNSS) is using a direct sequence/spread spectrum (DS/SS) modulation. In order to recover the information data, the DS/SS system first performs a two-step synchronization process: acquisition and tracking. The acquisition process adjusts the phase difference between the received and locally generated acquisition sequences within ${\pm}T_c/2$ or less, where $T_c$ is the chip period. The tracking process performs fine synchronization. In this paper, we focus on the tracking issue. The single delta delay locked loop($\Delta$-DLL) is the optimal tracking scheme for a GNSS in the absence of multipath signals, where $\Delta$ means the spacing between the early and late correlation time offset. In the multipath environments, however, the $\Delta$-DLL suffers from huge estimation bias(denoted by $\beta$) caused by distorted correlation values. Although some modified schemes such as a $\Delta$-DLL with a narrow $\Delta$ and a double delta DLL (${\Delta}^{(2)}$-DLL) were proposed to reduce the estimation bias, they cannot remove the estimation bias completely and need more accurate acquisition process. This paper proposes a novel tracking scheme that can dramatically reduce the estimation bias, using the maximum slope change among the correlation outputs.

• Journal of Korean Society on Water Environment
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• v.31 no.3
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• pp.241-252
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• 2015

Runoff behaviors by five bias correction methods were analyzed, which were Change Factor methods using past observed and estimated data by the estimation scenario with average annual calibration factor (CF_Y) or with average monthly calibration factor (CF_M), Quantile Mapping methods using past observed and estimated data considering cumulative distribution function for entire estimated data period (QM_E) or for dry and rainy season (QM_P), and Integrated method of CF_M+QM_E(CQ). The peak flow by CF_M and QM_P were twice as large as the measured peak flow, it was concluded that QM_P method has large uncertainty in monthly runoff estimation since the maximum precipitation by QM_P provided much difference to the other methods. The CQ method provided the precipitation amount, distribution, and frequency of the smallest differences to the observed data, compared to the other four methods. And the CQ method provided the rainfall-runoff behavior corresponding to the carbon dioxide emission scenario of SRES A1B. Climate change scenario with bias correction still contained uncertainty in accurate climate data generation. Therefore it is required to consider the trend of observed precipitation and the characteristics of bias correction methods so that the generated precipitation can be used properly in water resource management plan establishment.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.2
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• pp.169-172
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• 2019

Frequency-modulated continuous wave(FMCW) radars with array antennas are widely used because of their light weight and relatively high resolution. A usual approach for the joint range and angle estimation of a target using an array FMCW radar is to create a range-angle matrix with the deramped received signal, and subsequently apply two-dimensional(2D) frequency estimation methods such as 2D fast Fourier transform on the range-angle matrix. However, such frequency estimation approaches cause bias errors since the frequencies in the range-angle matrix are not independent. Therefore, we propose a new maximum likelihood-based algorithm for joint range and angle estimation of targets using array FMCW radar, and demonstrate that the proposed algorithm achieves the Cram?r-Rao bounds, both for range as well as angle estimation.

• Journal of Astronomy and Space Sciences
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• v.28 no.4
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• pp.267-271
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• 2011

I developed an enhanced correction method for Ricean bias which occurs in linear polarization measurement. Two known methods for Ricean bias correction are reviewed. In low signal-to-noise area, the method based on the mode of the equation gives better representation of the fractional polarization. But a caution should be given that the accurate estimation of noise level, i.e. ${\sigma}$ of the polarized flux, is important. The maximum likelihood method is better choice for high signal-to-noise area. I suggest a hybrid method which uses the mode of the equation at the low signal-to-noise area and takes the maximum likelihood method at the high signal-to-noise area. A modified correction coefficient for the mode solution is proposed. The impact on the depolarization measure analysis is discussed.

• ETRI Journal
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• v.30 no.6
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• pp.774-782
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• 2008

An operational orbit determination (OD) and prediction system for the geostationary Communication, Ocean, and Meteorological Satellite (COMS) mission requires accurate satellite positioning knowledge to accomplish image navigation registration on the ground. Ranging and tracking data from a single ground station is used for COMS OD in normal operation. However, the orbital longitude of the COMS is so close to that of satellite tracking sites that geometric singularity affects observability. A method to solve the azimuth bias of a single station in singularity is to periodically apply an estimated azimuth bias using the ranging and tracking data of two stations. Velocity increments of a wheel off-loading maneuver which is performed twice a day are fixed by planned values without considering maneuver efficiency during OD. Using only single-station data with the correction of the azimuth bias, OD can achieve three-sigma position accuracy on the order of 1.5 km root-sum-square.

• Journal of the Korean Institute of Telematics and Electronics
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• v.19 no.2
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• pp.23-30
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• 1982

In this paper, two methods (Kalman filter and Conventional) are investigated to reduce the bias error in the INS (Intertial Navigation System) vertical channel. The schemes by these methods show better performance (estimation error and response) than the others commonly used. Comparison results show that the scheme by Kalman filter method gives much better performance than the Conventional method.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.670-674
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• 1992

This paper presents a velocity regulation scheme for a DC motor subjected to random torque and velocity measurement noises of white noise type as well as unknown constant load torque (bias). The scheme separately estimates an unknown bias in addition to state estimation by the bias-free Kalman Filter, and reflects the effect of the bias estimate to the armature input voltage such that velocity variations be regulated. It is shown via computer simulations that the performance of the present scheme is superior to that of the conventional analog PI regulator.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1127-1135
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• 2014

Genome-wide association studies (GWAS) are designed to discover genetic variants such as single nucleotide polymorphisms (SNPs) that are associated with human complex traits. Although there is an increasing interest in the application of GWAS methodologies to population-based cohorts, many published GWAS have adopted a case-control design, which raise an issue related to a sampling bias of both case and control samples. Because of unequal selection probabilities between cases and controls, the samples are not representative of the population that they are purported to represent. Therefore, non-random sampling in case-control study can potentially lead to inconsistent and biased estimates of SNP-trait associations. In this paper, we proposed inverse-probability of sampling weights based on disease prevalence to eliminate a case-control sampling bias in estimation and testing for association between SNPs and quantitative traits. We apply the proposed method to a data from the Korea Association Resource project and show that the standard estimators applied to the weighted data yield unbiased estimates.