• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1551-1558
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• 2021

Beacon signals used in indoor positioning system are reflected and distorted, resulting in noise signals. KF(Kalman Filter) has been widely used to remove this noise. In order to apply the KF, optimization process considering the signal type, signal strength, and environmental elements of each product is required. In this paper, we propose a solution to the optimization problem of KF Parameters using GA(Genetic Algorithm) in BLE(Bluetooth Low Energy) Beacon-based indoor positioning system. After optimizing KF Parameters by applying the proposed technique with a certain distance between Beacon and receiver, we compared the estimated distance passed through KF with the unfiltered distance. The proposed technique is expected to reduce the time required and improve accuracy of KF Parameters optimization in an indoor positioning system based on RSSI (Received Signal Strength Indication).

• Ocean and Polar Research
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• v.30 no.2
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• pp.129-140
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• 2008

As a preliminary effort to establish a data assimilative ocean forecasting system, we reviewed the theory of the Ensemble Kamlan Filter (EnKF) and developed practical techniques to apply the EnKF algorithm in a real ocean circulation modeling system. To verify the performance of the developed EnKF algorithm, a wind-driven double gyre was established in a rectangular ocean using the Regional Ocean Modeling System (ROMS) and the EnKF algorithm was implemented. In the ideal ocean, sea surface temperature and sea surface height were assimilated. The results showed that the multivariate background error covariance is useful in the EnKF system. We also tested the sensitivity of the EnKF algorithm to the localization and inflation of the background error covariance and the number of ensemble members. In the sensitivity tests, the ensemble spread as well as the root-mean square (RMS) error of the ensemble mean was assessed. The EnKF produces the optimal solution as the ensemble spread approaches the RMS error of the ensemble mean because the ensembles are well distributed so that they may include the true state. The localization and inflation of the background error covariance increased the ensemble spread while building up well-distributed ensembles. Without the localization of the background error covariance, the ensemble spread tended to decrease continuously over time. In addition, the ensemble spread is proportional to the number of ensemble members. However, it is difficult to increase the ensemble members because of the computational cost.

• Fisheries and Aquatic Sciences
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• v.14 no.4
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• pp.363-369
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• 2011

Total ammonia nitrogen (TAN) removal efficiencies of a sand filter (SF), polystyrene microbead filter (PF), and Kaldnes bead filter (KF) media were evaluated under ammonia loading rates of 5, 25, and 50 g $m^{-3}day^{-1}$. The volume of each filter media tested was 7 L, and the water flow rate for all filter media was 24 L/min. The specific surface areas of the SF, PF, and KF were 7,836, 3,287, and 500 $m^2/m^3$, respectively. Sand was fluidized and the other two media were trickle filtered. The volumetric TAN removal rate increased with increasing ammonia loading rate for all filter media. Mean volumetric TAN removal rates under the ammonia loading rates of 5, 25, and 50 g $m^{-3}day^{-1}$ in SF (39.3, 168.6, and 322.7 g $m^{-3}day^{-1}$, respectively) were higher than those in PF (35.0, 157.4, and 310.5 g $m^{-3}day^{-1}$, respectively) and KF (32.1, 142.5, and 288.1 g $m^{-3}day^{-1}$, respectively). These results were related to differences in the specific surface areas of the filter media. PF was the most economic media for efficiently removing TAN.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.47-52
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• 2005

This paper describes how a relatively compensate the error of position by using low cost Inertial Measurement Unit (IMU) has been evaluated and compared with the well established method based on a Kalman Filter(KF). The compensation algorithm by using IMU have been applied to the problem of integrating information from an Inertial Navigation System (INS). The KF is to estimate and compensate the errors of an INS by using the integrated INS velocity and position. We verify the proposed algorithm by simulation results.

• International Journal of Ocean System Engineering
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• v.1 no.3
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• pp.165-170
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• 2011

In this paper, for the accurate estimation of the position and orientation of the UUV (unmanned underwater vehicle), an AHRS (Attitude Heading Reference System) was developed using the IMU (inertial measurement unit) sensor which provides information on acceleration and orientation in the object coordinate and the initial alignment algorithm and the E-KF (extended Kalman Filter). The initial position and orientation of the UUV are estimated using the initial alignment algorithm with 3-axis acceleration and geomagnetic information of the IMU sensor. The position and orientation of the UUV are estimated using the AHRS composed of 3-axis acceleration, velocity, and geomagnetic information and the E-KF. For the performance test of the orientation estimation of the AHRS, a testbed using IMU sensor(ADIS16405) and DSP28335 coded with an E-KF algorithm was developed and its performance was verified through tests.

• Particle and aerosol research
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• v.19 no.1
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• pp.1-11
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• 2023

Respiratory face masks are protective facepieces that are designed to filter inhaled air. They are easy-to-use devices that can protect the wearer against various hazardous particles in the air. Respiratory face masks also prevent the spread of viruses and bacteria-containing droplets that are released from the coughing or sneezing of the infected people. During the COVID-19 pandemic, various types of face masks have circulated on the market. Their ability to filter sub-micron particles, which are the sizes of harmful particulate matter and airborne viruses, needs to be investigated. Their breathability, the easiness of breath through the mask, also needs to be considered. In this study, wwe evaluated the performance of filters used for different types of face masks certified by different standards including Korean (KF94, KF80, KF-AD), USA (N95), and Chinese (KN95) standards. We also tested the filters of nanofiber masks and surgical masks for which there are no standards for filtration test. The N95 mask filters showed the highest quality factor for capturing virus-sized particles. The other types of mask filters have acceptable performance except for nanofiber mask filters whose performance is very low.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.286-287
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• 2011

Kalman filter(KF) algorithm is a very useful application being used in many engineering fields. Through the KF, the next time step's estimation can be almost simultaneously calculated by the recursive least square optimization method with the present measurement data. It provides us with the superior detection performance of power quality events. This paper deals with the concrete programming example of KF to detect various kinds of PQ disturbances, such as voltage sag, swell, harmonics, voltage fluctuation and Frequency variation.

• Annual Conference of KIPS
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• 2018.10a
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• pp.430-433
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• 2018

This paper proposes the Kalman filter (KF) with optical flow method to estimate the position and the velocity of unmanned aerial vehicles (UAVs) in the absence of global positioning system (GPS). A downward-looking camera, a gyroscope and an ultrasonic sensor are fused to compensate the measurement from optical-flow method. To overcome the problem of dealing with noise in onboard sensors, the KF is incorporated to efficiently predict the velocity and estimate the position. Basic mechanisms of optical flow and the KF are introduced and experiments are conducted to show how the techniques involved improve the estimations.

• Journal of Environmental Health Sciences
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• v.45 no.2
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• pp.134-141
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• 2019

Objectives: The study aimed to investigate the characteristics of health masks and to suggest the proper selection and use of protecting the respiratory system from particulate matters. Methods: The National Standard of masks promulgated by the Ministry of Food and Drug Safety (MFDS) and the Ministry of Employment and Labor (MOEL) were reviewed. The raw data of certified health masks were obtained from the MFDS database. Descriptive statistical analysis was performed. Results: Overall, 543 masks were certified by MFDS as of March 2019. Numbers of certified masks as KF80 (Korea Filter), KF94 and KF99 were 257 (47.3%), 281 (51.8%), and 5 (0.9%), respectively. Names of health masks, which were yellow sand, communicable diseases, health or its combination, were diverse that made customers be confused in selection. Health masks were also classified by particulate size, however, detailed information was not available. Conclusions: We investigated the status of health mask certification in Korea. Appropriate information on KF grade of health masks is required for customers to use them properly. MFDS should update the certification system of health masks periodically.

• Annual Conference of KIPS
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• 2009.04a
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• pp.286-289
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• 2009

센서 네트워크 구조에서는 많은 수의 센서 노드들이 지속적으로 센서 데이터를 베이스 스테이션(Base Station)으로 전송한다. 각 노드의 샘플링 주기는 베이스 스테이션으로 전송되는 길목의 네트워크 자원인 대역폭, 계산 비용 등에 지대한 영향을 끼친다. 본 논문에서는 샘플링 대상의 스트림 데이터 특성에 따른 각 노드의 샘플링 주기에 관련된 새로운 적응적 샘플링 기법을 제안한다. 본 논문에서는 KF(Kalman-Filter) 에 기반을 둔 예측 기법을 사용하였다. 이는 각 노드는 KF의 예측값과 실측값의 차를 사용하여 허용된 범위 안에서 자동적으로 샘플링 주기를 조정하는 방식이다. 따라서, 우리는 샘플링 대상의 데이터 특성에 따른 우선순위에 기반 네트워크 자원을 효과적으로 사용하고 Dual Kalman Filter(DKF) 기법과 결합하여 센서 네트워크에서의 가장 큰 문제 중 하나인 에너지 소비의 최소화하면서 효과적으로 근사 데이터 전송하도록 하여 에너지 소비량을 줄였다.