• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.5
• /
• pp.265-271
• /
• 2023

Recently, location information services are gradually expanding due to the development of information and communication technology. RSSI is widely used to extract indoor and outdoor locations. The indoor and outdoor location estimation methods using RSSI are less accurate due to the influence of radio wave paths, interference, and surrounding wireless devices. In order to improve this problem, a distance estimation method that takes into account the wireless propagation environment is necessary. Therefore, in this study, we propose a distance estimation algorithm that takes into account the radio wave environment. The proposed method estimates the distance by learning RSSI input and output considering the RBF neural network and the propagation environment. To evaluate the performance of the proposed method, the performance of estimating the location of the receiver within a range of up to 55[m] using a BLE beacon transmitter and receiver was compared with the average filter and Kalman filter. As a result, the distance estimation accuracy of the proposed method was 6.7 times higher than that of the average filter and Kalman filter. As shown in the results of this performance evaluation, if the method of this study is applied to location services, more accurate location estimation will be possible.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.6 no.1
• /
• pp.148-156
• /
• 2011

This paper presents an implementation of autonomous navigation of a mobile robot indoors. It explains methods for map building, localization, obstacle avoidance and path planning. Geometric map is used for localization and path planning. The localization method calculates sensor data based on the map for comparison with the real sensor data. Monte Carlo Localization(MCL) method is adopted for estimation of the robot position. For obstacle avoidance, an artificial potential field generates repulsive and attractive force to the robot. Dijkstra algorithm plans the shortest distance path from a start position to a goal point. The methods integrate into autonomous navigation method and implemented for indoor navigation. The experiments show that the proposed method works well for safe autonomous navigation.

• Journal of KIISE:Information Networking
• /
• v.37 no.6
• /
• pp.431-443
• /
• 2010

In this paper, we propose a range-free localization method that can improve the estimation accuracy of Approximate Point in Triangle(APIT), which is the representative localization method for low cost wireless sensor networks. Specifically, we propose extended-APIT(e-APIT) method, which minimizes the error in deciding whether an object is in an area formed by three beacons. We also propose a way to improve the localization by narrowing down the potential localization area using the signals from neighboring beacons. According to the simulation performed, the proposed e-APIT method demonstrated noticeable accuracy improvement over the conventional APIT method.

• The Journal of the Acoustical Society of Korea
• /
• v.42 no.6
• /
• pp.529-535
• /
• 2023

Noise originating from incipient propeller cavitation is assumed to come from a limited number of sources emitting a broadband signal. Conventional methods for cavitation localization have limitations because they cannot distinguish adjacent sound sources effectively due to low accuracy and resolution. On the other hand, sparse Bayesian learning technique demonstrates high-resolution restoration performance for sparse signals and offers greater resolution compared to conventional cavitation localization methods. In this paper, an incipient propeller cavitation localization method using sparse Bayesian learning is proposed and shown to be superior to the conventional method in terms of accuracy and resolution through experimental data from a model ship.

• Proceedings of the KIPE Conference
• /
• 2016.11a
• /
• pp.107-108
• /
• 2016

본 논문에서는 위치 센서 없이 영구자석 선형 전동기의 초기 자극 위치를 추정하는 알고리즘을 제안하였다. 이 알고리즘은 선형 전동기의 고주파 특성을 이용하여 초기 자극 위치를 추정한다. 정지 좌표계 상에서 고주파 전압을 주입하였을 때 유도되는 전류 데이터를 추출하여 분석한 결과, 전류 파형과 기준 신호와의 위상 차이가 자극의 위치에 따라 180도의 주기를 가지고 달라짐을 확인하였다. 이러한 위상 차이와 자극의 위치 사이의 관계를 이용하여 초기 위치를 추정할 수 있다. 제안하는 방법은 이동자의 움직임을 필요로 하지 않으므로 선형 전동기의 수직 방향 움직임을 필요로 하는 분야에서 위 센서 없는 제어에 효과적으로 사용될 수 있다. 실험을 통해 알고리즘의 타당성 및 효과를 검증하였다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.4
• /
• pp.925-932
• /
• 2015

In this paper, by utilizing the iBeacon is BLE (BlueTooth Low Energy) protocol devices that are supported by over the Bluetooth 4.0, and have implemented a system to improve the accuracy in the system for measuring the position of the user. After measuring through the system according to the state of the iBeacon, the interference factors are analyzed through analysis of the collected data, and applying the extended Kalman filter for calibration. Compared with the data after applying a filter with existing data, it was confirmed an increase in accuracy. Improvement techniques for providing the less complexity to the actual implementation, is effective in improving the accuracy of vulnerable services basic iBeacon.

• The Journal of the Acoustical Society of Korea
• /
• v.26 no.8
• /
• pp.415-425
• /
• 2007

This paper proposes a method of underwater source localization using the wideband interference patterns matching. By matching two interference patterns in the spectrogram, it is estimated a ratio of the range from source to sensor5, and then this ratio is applied to the Apollonius circle. The Apollonius circle is defined as the locus of all points whose distances from two fixed points are in a constant value so that it is possible to represent the locus of potential source location. The Apollonius circle alone, however still keeps the ambiguity against the correct source location. Therefore another equation is necessary to estimate the unique locus of the source location. By estimating time differences of signal arrivals between source and sensors, the hyperbola equation is used to get the cross point of the two equations, where the point being assumed to be the source position. Simulations are performed to get performances of the proposed algorithm. Also, comparisons with real sea experiment data are made to prove applicability of the algorithm in real environment. The results show that the proposed algorithm successfully estimates the source position within an error bound of 10%.

• Journal of the Korea Computer Industry Society
• /
• v.6 no.3
• /
• pp.495-508
• /
• 2005

Moving objects are spatiotemporal data that change their location or shape continuously over time. Their location coordinates are periodically measured and stored i3l the application systems. The linear function is mainly used to estimate the location information that is not in the system at the query time point. However, a new method is needed to improve uncertainties of the location representation, because the location estimation by linear function induces the estimation error. This paper proposes an application method of the cubic spline interpolation in order to reduce deviation of the location estimation by linear function. First, we define location information of the moving object on the two-dimensional space. Next, we apply the cubic spline interpolation to location estimation of the proposed data model and describe algorithm of the estimation operation. Finally, the precision of this estimation operation model is experimented. The experimentation comes out more accurate results than the method by linear function.

• Journal of IKEEE
• /
• v.3 no.1 s.4
• /
• pp.101-108
• /
• 1999

In this paper, a real time diagnostic algorithm for estimating the impact location by loose parts is proposed. It is composed of two modules such as the alarm discrimination module (ADM) and the impact-location estimation module(IEM). First, ADM decides whether the detected signal that triggers the alarm is the impact signal by loose parts or the noise signal. Second, IEM by use of the arrival time method estimates the impact location of loose parts. In order to validate the application of this method, the test experiment with a mock-up (flat board and reactor) system is performed. The experimental results show the efficiency of this algorithm even under high level noise and potential application to Loose Part Monitoring System (LPMS) for improving diagnosis capability in nuclear power plants.

• Journal of IKEEE
• /
• v.19 no.4
• /
• pp.557-565
• /
• 2015

In this paper, a method for estimating the location of a quadcopter is proposed by applying an EKF-SLAM algorithm to its flight control, to autonomously control the flight of an unmanned quadcopter. The usefulness of this method is validated through simulations. For autonomously flying the unmanned quadcopter, an algorithm is required to estimate its accurate location, and various approaches exist for this. Among them, SLAM, which has seldom been applied to the quadcopter flight control, was applied in this study to simulate a system that estimates flight trajectories of the quadcopter.