• International Journal of Aeronautical and Space Sciences
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• v.3 no.1
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• pp.86-94
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• 2002

The initial alignment of inertial platform for navigation system was considered. An adaptive filtering technique is developed for the system with unknown and varying sway disturbance. It is assumed that the random sway motion is the second order ARMA(Auto Regressive Moving Average) model and performed parameter identification for unknown parameters. Designed adaptive filter contain both a Kalman filter and a self-tuning filter. This filtering system can automatically adapt to varying environmental conditions. To verify the robustness of the filtering system, the computer simulation was performed with unknown and varying sway disturbance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.4
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• pp.47-52
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• 2006

Using the equivalent ARMA model representation of the mixed random errors, we propose Klaman filter design methods for aided INS(Inertial Navigation System) which contains the gyroscope mixed random errors. At first step, considering the characteristic of indirect feedback Kalman filter used in the aided INS, we perform the time difference of equivalent ARMA model. Next, according to the order of the time differenced ARMA model, we achieve the state space conversion of that by two methods. If the order of AR part is greater than MA part, we use controllable or observable canonical form. Otherwise, we establish the state apace equation via the method that several step ahead predicts are included in the state variable, where we can derive high and low order models depending on the variable which is compensated from gyroscope output. At final step, we include the state space equation of gyroscope mixed random errors into aided INS Kalman filter model. Through the simulation, we show that both the high and low order filter models proposed give less navigation errors compared to the conventional filter which assume the mixed random errors as white noise.

• Proceedings of the KIEE Conference
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• 1986.07a
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• pp.140-144
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• 1986

In this paper an FIR(finite impulse response) filter and smoother are introduced for discrete time-invariant state-space models with driving noises. The FIR structure not only quarantees the BIBO stability and the robustness to parameter changes but also improves the filter divergence problem. It is shown that the impulse responses of the FIR filter and the smoother are obtained by Riccati-type difference equations and that they are to be time-invariant and reduced to very simple forms. For implementational purpose, recursive forms of the FIR filler and smoother are derived with each other used as the adjoint variable.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.6
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• pp.510-520
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• 1988

In this paper, the output error variance due to the differential vcariation of the state-space coefficient [ABCD], which is the coefficient quentization error, is normalized on the variance for cases that infinite wordlength state-space digital filter is realized by the finite one. That is, defining S as the statistical sensitivity and extending controllability gramian, observability gramian, and 2nd order mode analysis method to the state space digital filter, we synthesize the realization structure with the minimum statistical sensitivity and prove the effecency of the minimum statistical sensitivity structure synthesis by the simulation.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.2
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• pp.83-89
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• 2021

The extended Kalman filter (EKF) is widely used for global navigation satellite system (GNSS) applications. It is difficult to obtain precise positions with an EKF one-way (forward or backward) filter. In this paper, we propose an EKF smoother to improve the positioning accuracy by integrating forward and backward filters. For the EKF smoother experiment, we performed PPP using GNSS data received at the DAEJ reference station for a month. The effectiveness of the proposed approach is validated with multi-GNSS kinematic PPP experiments. The EKF smoother showed 35%, 6%, and 22% improvement in east, north, and up directions, respectively. In addition, accurate tropospheric zenith total delay (ZTD) values were calculated by a smoother. Therefore, the results from EKF smoother demonstrate that better accuracy of position can be achieved.

• Journal of Astronomy and Space Sciences
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• v.29 no.3
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• pp.269-274
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• 2012

Kinematic global positioning system precise point positioning (GPS PPP) technology is widely used to the several area such as monitoring of crustal movement and precise orbit determination (POD) using the dual-frequency GPS observations. In this study we developed a kinematic PPP technology and applied 3-pass (forward/backward/forward) filter for the stabilization of the initial state of the parameters to be estimated. For verification of results, we obtained GPS data sets from six international GPS reference stations (ALGO, AMC2, BJFS, GRAZ, IENG and TSKB) and processed in daily basis by using the developed software. As a result, the mean position errors by kinematic PPP showed 0.51 cm in the east-west direction, 0.31 cm in the north-south direction and 1.02 cm in the up-down direction. The root mean square values produced from them were 1.59 cm for the east-west component, 1.26 cm for the south-west component and 2.95 cm for the up-down component.

• Journal of the Chungcheong Mathematical Society
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• v.11 no.1
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• pp.87-98
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• 1998

The purpose of this paper is to show that there exists a fibrewise H-complete extension of a quasi-uniform space over a base.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.4
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• pp.153-161
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• 2018

This paper describes the performance improvement of Software (SW) digital filter using GPU (Graphical Processing Unit). The previous developed SW digital filter has a problem that it operates on a CPU (Central Processing Unit) basis and has a slow speed. The GPU was introduced to filter the data of the EAVN (East Asian VLBI Network) observation to improve the operation speed and to process data with other stations through filtering, respectively. In order to enhance the computational speed of the SW digital filter, NVIDIA Titan V GPU board with built-in Tensor Core is used. The processing speed of about 0.78 (1Gbps, 16MHz BW, 16-IF) and 1.1 (2Gbps, 32MHz BW, 16-IF) times for the observing time was achieved by filtering the 95 second observation data of 2 Gbps (512 MHz BW, 1-IF), respectively. In addition, 2Gbps data is digitally filtered for the 1 and 2Gbps simultaneously observed with KVN (Korean VLBI Network), and compared with the 1Gbps, we obtained similar values such as cross power spectrum, phase, and SNR (Signal to Noise Ratio). As a result, the effectiveness of developed SW digital filter using GPU in this research was confirmed for utilizing the data processing and analysis. In the future, it is expected that the observation data will be able to be filtered in real time when the distributed processing optimization of source code for using multiple GPU boards.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.452-457
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• 2008

We performed a study on the contaminant transfer in a clean space for the location of product and fan filter unit using computational fluid dynamics analysis. To simplify the real product moving process, three different non-moving cases regrading the locations of product were selected: no product, at the lower side, and at the upper and lower sides. And to investigate the characteristics of the contaminant transfer, the arrangement of fan filter units was varied. Local mean air-age and contaminant distribution were used as evaluation indices. From the results, the contaminant transfer to the product was the most when the products were simultaneously located at the upper and lower sides. And the contaminant was easily exhausted regardless of the location of product when the fan filter units were properly arranged at the top side of the clean space.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.5
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• pp.455-461
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• 2008

In this paper, the performance of a scalar filter and a scalar adaptive filter are analyzed. In order to make indoor experimental environment similar to outdoor test, ultrasonic sensors are used instead of GPS. The scalar adaptive filter, which is continuously estimating velocity error covariance and measurement noise covariance by using adaptive method, is different from the scalar filter. Experimental results show that the scalar adaptive filter has better position estimating performance than the scalar filter by estimating above two parameters with an adaptive method.