• Journal of Sensor Science and Technology
• /
• v.18 no.4
• /
• pp.280-285
• /
• 2009

In this paper, we designed a 2-stage CMOS operational amplifier with temperature compensation function using 2-poly 4-metal 0.35 $\mu$m standard CMOS technology. Using two bias circuits, the positive temperature coefficient(PTC) and the negative temperature coefficient(NTC) of the bias circuit are canceled out each other. When reference current circuit is simulated that it has a temperature coefficient of -150 ppm/$^{\circ}C$ with a temperature change from 0 $^{\circ}C$ to 120 $^{\circ}C$. Also the proposed circuit has a temperature coefficient of -0.011 dB/$^{\circ}C$ of DC open loop gain with the same temperature range.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.9
• /
• pp.941-946
• /
• 2011

The Loran-C, a radio navigation system based on TDOA measurements is enhanced to eLoran using TOA measurements instead of TDOA measurements. Many error factors such as PF, SF, ASF, clock errors and unknown biases are included in eLoran TOA measurements. Because these error factors can cause failure in eLoran navigation algorithm, these errors must be compensated for high accuracy eLoran navigation results. Compensation of ASF and unknown biases are difficult to calculate, while the others such as PF and SF are relatively easy to eliminate. In order to compensate all errors in eLoran TOA measurements, a simple GPS aided bias compensation method is suggested in this paper. This method calculates the bias as the difference of TOA measurement and the range between eLoran transmitters and the receiver whose position is determined using GPS. The real data measured in Europe are used for verification of suggested method and navigation algorithm.

• The Journal of the Acoustical Society of Korea
• /
• v.23 no.3
• /
• pp.228-234
• /
• 2004

In this paper, we proposed the compensation technique that overcomes the limitations of the conventional approaches through summing up the bias terms between world's codebook and individual codebook vectors of feature parameters. But, mean compensation without condition can bring higher false acceptance. Therefore, the proposed technique compensates the channel mis-match condition by weighted bias sum using nonlinear function regarding to the distortion between speech and silence. The simulation results show that the FRR (flase reject rate) is decreased 14.95% when the proposed algorithm was applied.

• ETRI Journal
• /
• v.31 no.3
• /
• pp.247-253
• /
• 2009

We propose a Ku-band driver and high-power amplifier monolithic microwave integrated circuits (MMICs) employing a compensating gate bias circuit using a commercial 0.5 ${\mu}m$ GaAs pHEMT technology. The integrated gate bias circuit provides compensation for the threshold voltage and temperature variations as well as independence of the supply voltage variations. A fabricated two-stage Ku-band driver amplifier MMIC exhibits a typical output power of 30.5 dBm and power-added efficiency (PAE) of 37% over a 13.5 GHz to 15.0 GHz frequency band, while a fabricated three-stage Ku-band high-power amplifier MMIC exhibits a maximum saturated output power of 39.25 dBm (8.4 W) and PAE of 22.7% at 14.5 GHz.

• Journal of Ocean Engineering and Technology
• /
• v.31 no.2
• /
• pp.177-182
• /
• 2017

This paper describes an unscented Kalman filter approach to estimate the bias in magnetic field measurements. A microelectromechanical systems attitude heading reference system (MEMS AHRS) was used to measure the magnetic field, together with the acceleration and angular rate. A magnetic field is usually used for yaw detection, while the acceleration serves to detect the roll and pitch. Magnetic field measurements are vulnerable to distortion due to hard-iron effect and soft-iron effect. The bias in the measurement accounts for the hard-iron effect, and this paper focuses on an approach to estimate this bias. The proposed method is compared with other methods through experiments that implement the navigation of an underwater robot using an AHRS and Doppler velocity log. The results verify that the compensation of the bias by the proposed method improves the navigation performance more than or comparable to the compensation by other methods.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.10C
• /
• pp.1016-1023
• /
• 2009

In this paper, a tracking bias compensation method is proposed for future global navigation satellite systems (GNSSs). It is observed that the correlation function of a GNSS signal has many peaks and remains almost unchanged in the advanced offset region as a result of the multipath signals arriving at the receiver later than a line-of-sight signal. Based on these observations, we use the slopes in the advanced offset region to compensate for the code tracking bias, and obtain the maximum code tracking bias, which is essential to implement the proposed scheme, in static multipath environments. Finally, it is demonstrated that the proposed compensation method is very effective for the GNSS signal tracking in terms of the code tracking biases and their running averages.

• The Journal of the Acoustical Society of Korea
• /
• v.23 no.5
• /
• pp.383-389
• /
• 2004

In this paper. we propose the bias compensation methods and the eigenvoice method using the mean of dimensional eigenvoice to improve the performance of rapid speaker adaptation based on eigenvoice under mismatch between training and test environment. Experimental results for vocabulary-independent word recognition task (using PBW 452 DB) show that the proposed methods yield improvements for small adaptation data. We obtained about 22∼30% relative improvement by the bias compensation methods as amount of adaptation data varied from 1 to 50, and obtained 41% relative improvement in error rate by the eigenvoice method using the mean of dimensional eigenvoice with only single adaptation word.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.2
• /
• pp.55-62
• /
• 2019

The stereo geometry establishment based on the precise sensor modeling is prerequisite for accurate stereo data processing. Ground control points are generally required for the accurate sensor modeling though it is not possible over the area where the accessibility is limited or reference data is not available. For the areas, the relative orientation should be carried out to improve the geometric consistency between the stereo data though it does not improve the absolute positional accuracy. The relative orientation requires conjugate points that are well distributed over the entire image region. Therefore the automatic conjugate point extraction is required because the manual operation is labor-intensive. In this study, we applied the method consisting of the key point extraction, the search space minimization based on the epipolar line, and the rigorous outlier detection based on the RPCs (Rational Polynomial Coefficients) bias compensation modeling. We tested different parameters of window sizes for Kompsat-2 across track stereo data and analyzed the RPCs precision after the bias compensation for the cases whether the epipolar line information is used or not. The experimental results showed that matching outliers were inevitable for the different matching parameterization but they were successfully detected and removed with the rigorous method for sub-pixel level of stereo RPCs precision.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.524-527
• /
• 1997

Conventional target tracking algorithms based on the linear estimation techniques perform quite efficiently when the target motion does not involve maneuvers. Target maneuvers involving short term accelerations, however, cause a bias in the measurement sequence. Accurate compensation for the bias requires processing more samples of which adds to the computational complexity. The primary motivation for employing a neural network for this task comes from the efficiency with which more features can be as inputs for bias compensation. A system architecture that efficiently integrates the fusion capabilities of a trained multilayer neural net with the tracking performance of a Kalman filter is described. The parallel processing capability of a properly trained neural network can permit fast processing of features to yield correct acceleration estimates and hence can take the burden off the primary Kalman filter which still provides the target position and velocity estimates.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.8
• /
• pp.1075-1079
• /
• 2014

In this paper, we describe the analysis and the compensation method of the g-sensitivity error for MEMS vibratory gyroscopes. Usually, the g-sensitivity error has been ignored in the commercial MEMS gyroscope, but it deserves our attention to apply for the missile application as a tactical grade performance. Thus, it is necessary to compensate for the g-sensitivity error to reach a tactical grade performance. Generally, the g-sensitivity error seems intuitively to be a gyroscope bias error proportional to the linear acceleration. However, we assert that the g-sensitivity error mainly causes not a bias error but a scale-factor error. And we verify that the g-sensitivity scale-factor error occurs due to the non-linearity of parallel plate electrodes. Therefore, we propose the compensation method to remove the g-sensitivity scale-factor error. The experimental result showed that a proposed compensation method improved successfully the performance of the MEMS vibratory gyroscope.