• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.7
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• pp.59-69
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• 2005

A position domain Hatch filter is proposed as an efficient carrier-smoothed-code processing algorithm for real-time kinematic differential global satellite navigation systems. The well-known range domain Hatch filter is newly interpreted with a stochastical point of view. The interpretation result is extended to derive the position domain Hatch filter. By a covariance simulation, it is shown that Hatch gain is, in general, more efficient than Kalman-type gain in carrier-smoothed-code processing and the proposed position domain Hatch filter is more advantageous than the conventional range domain Hatch filter if the visible satellite constellation changes during the positioning task.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.1015-1023
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• 2001

error behaviour can be considered as a linear combination of low amplitude random noise and abrupt jumps. The reason of jump appearance can be explained by the semi-shading effects(buildings, trees), jamming, high dynamic of vehicle and so on. This study describes the stand-alone GPS error jump smoothing algorithm which is developed based on the scalar adaptive filter. The algorithm consists of the coarse jump smoothing and the fine jump smoothing. On the coarse smoothing step, GPS velocities or position differences are used as the measurement for the scalar adaptive filter. The purpose of adaptive filter is to smooth the jump errors. The coarse positions are detennined by the integration of smoothed velocities. On the fine smoothing step, the differences between GPS positions and the coarse positions are smoothed by another scalar adaptive filter. The reason of fine smoothing is based on the facts that smoothing accuracy depends on the variance ofusefuJ signa\. The coarse smoothing which deal with the difference of positions provides the rough error removing. So the coarse smoothed velocities can have much more low amplitude than the raw ones. The fine smoothing procedure provides high quality of filtering process. Simulation results show the efficiency of proposed scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.11
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• pp.1034-1039
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• 2012

In this paper, a structure of precise positioning based on satellite navigation system is proposed. The proposed system is consisted with three parts, range domain filter, navigation filter and position domain filter. The range domain filter generates carrier phase-smoothed-Doppler and Doppler-smoothed-code measurements. And the navigation filter calculates position and velocity using double-differenced code/carrier phase/Doppler measurements. Finally, position domain filter smooth position error, and it means enhancement of positioning performance. The proposed positioning method is evaluated by trajectory analysis using precise map date. As a result, the position error occurred by multipath or cycle slip was reduced and the calculated trajectory was in true lane.

• Journal of Advanced Navigation Technology
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• v.16 no.4
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• pp.602-610
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• 2012

Ionospheric delay error, one of main error sources in GPS signal, varies with signal frequency. Dual-frequency user uses L1, L2 frequency pseudorange to estimate the ionospheric delay, and there are errors caused by pseudorange measurement noise. So, filter is usually used to smooth the measurement. Weighted hatch filter can estimate optimal smoothed pseudorange measurement. But measurement noise model is needed to use this filter. In this paper, measurement noise modeling is conducted for NDGPS reference station. Using noise modeling result, weighted hatch filter estimate smoothed pseudorange measurement and ionospheric delay. Standard deviation of ionospheric dealy error drops to one-twenty fifth of non-filtered result.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.378-384
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• 2005

This paper proposes a theoretically rigorous analysis procedure that compares the position domain and range domain carrier-smoothed-code filters for differential GNSS positioning. Utilizing consistent error covariance formulation, it is shown that filtering in the position domain is, in theory, more advantageous than range domain carrier-smoothed-code filtering. It is also shown that if the visible satellite set does not change during a sufficiently long time interval the performances of position and range domain filters are similar.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.71-76
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• 2023

In this paper, we propose a smoothed received signal strength indicator (RSSI)-based distance estimation using deep neural network (DNN) for accurate distance estimation in an environment where a single receiver is used. The proposed scheme performs a data preprocessing consisting of data splitting, missing value imputation, and smoothing steps to improve distance estimation accuracy, thereby deriving the smoothed RSSI values. The derived smoothed RSSI values are used as input data of the Multi-Input Single-Output (MISO) DNN model, and are finally returned as an estimated distance in the output layer through input layer and hidden layer. To verify the superiority of the proposed scheme, we compared the performance of the proposed scheme with that of the linear regression-based distance estimation scheme. As a result, the proposed scheme showed 29.09% higher distance estimation accuracy than the linear regression-based distance estimation scheme.

• Journal of Advanced Navigation Technology
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• v.8 no.1
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• pp.26-37
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• 2004

Consistent and realistic error covariance information is important for position estimation, error analysis, fault detection, and integer ambiguity resolution for differential GNSS. In designing a position domain carrier-smoothed-code filter where incremental carrier phases are used for time-propagation, formulation of consistent error covariance information is not easy due to being bounded and temporal correlation of propagation noises. To provide consistent and correct error covariance information, this paper proposes two recursive filter algorithms based on carrier-smoothed-code techniques: (a) the stepwise optimal position projection filter and (b) the stepwise unbiased position projection filter. A Monte-Carlo simulation result shows that the proposed filter algorithms actually generate consistent error covariance information and the neglection of carrier phase noise induces optimistic error covariance information. It is also shown that the stepwise unbiased position projection filter is attractive since its performance is good and its computational burden is moderate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.176-179
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• 2010

In this paper, we propose a fast implementation of Bilateral filter for tone mapping algorithm. Bilateral filter is able to preserve detail while at the same time prevent halo-ing artifacts because of improper scale selection by ensuring image smoothed that not only depend on pixel closeness, but also similarity. We accelerate Bilateral filter by using a piecewise linear approximation and recursive Gaussian filter as its domain filter. Recursive Gaussian filter is scale independent filter that combines low cost 1D filter which makes this filter much faster than conventional convolution filter and filtering in frequency domain. The experiment results show that proposed method is simpler and faster than previous method without mortgaging the quality.

• MALSORI
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• no.67
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• pp.195-216
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• 2008

This paper addresses the problem of single-channel speech separation to extract the speech signal uttered by the speaker of interest from a mixture of speech signals. We propose to apply time-frequency smoothing to the existing statistical single-channel speech separation algorithms: The soft mask and the minimum-mean-square-error (MMSE) algorithms. In the proposed method, we use the two smoothing later. One is the uniform mask filter whose filter length is uniform at the time-Sequency domain, and the other is the met-scale filter whose filter length is met-scaled at the time domain. In our speech separation experiments, the uniform mask filter improves speaker-to-interference ratio (SIR) by 2.1dB and 1dB for the soft mask algorithm and the MMSE algorithm, respectively, whereas the mel-scale filter achieves 1.1dB and 0.8dB for the same algorithms.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.11a
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• pp.188-190
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• 2012

Compressed Sensing (CS) has been developed for several years. Among many CS algorithms for image, the Block-based Compressed Sensing with Smoothed Projected Landweber (BCS-SPL) demonstrates its excellent performance in low-complexity and near-optimal reconstruction. Several noise filtering algorithms of image reconstruction have been introduced such as the Wiener or the median filters, etc. In general, each filter has its own advantages and disadvantages depending on specific coding scheme. In this paper, we show that reconstruction performance can be varied according to the choice of filter. When a sub-rate value is changed, different filter causes different effect as well. Concerning the sub-rate, an inner filter can be chosen to improve the reconstructed image quality.