• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.9
• /
• pp.595-602
• /
• 2013

WiFi fingerprinting is well known as an effective localization technique used for indoor environments. However, this technique requires a large amount of pre-built fingerprint maps over the entire space. Moreover, due to environmental changes, these maps have to be newly built or updated periodically by experts. As a way to avoid this problem, crowd-sourced fingerprint mapping attracts many interests from researchers. This approach supports many volunteer users to share their WiFi fingerprints collected at a specific environment. Therefore, crowd-sourced fingerprinting can automatically update fingerprint maps up-to-date. In most previous systems, however, individual users were asked to enter their positions manually to build their local fingerprint maps. Moreover, the systems do not have any principled mechanism to keep fingerprint maps clean by detecting and filtering out erroneous fingerprints collected from multiple users. In this paper, we present the design of a crowd-sourced fingerprint mapping and localization(CMAL) system. The proposed system can not only automatically build and/or update WiFi fingerprint maps from fingerprint collections provided by multiple smartphone users, but also simultaneously track their positions using the up-to-date maps. The CMAL system consists of multiple clients to work on individual smartphones to collect fingerprints and a central server to maintain a database of fingerprint maps. Each client contains a particle filter-based WiFi SLAM engine, tracking the smartphone user's position and building each local fingerprint map. The server of our system adopts a Gaussian interpolation-based error filtering algorithm to maintain the integrity of fingerprint maps. Through various experiments, we show the high performance of our system.

• Journal of KIISE
• /
• v.44 no.6
• /
• pp.643-648
• /
• 2017

Among Wi-Fi based indoor positioning systems, fingerprinting localization is the most common technique with high precision. However, construction of the initial radio map and the update process require considerable labor and time effort. To address this problem, we propose an efficient method that constructs the initial radio map at each vertex based on a graph. In addition, we introduce a method to update the radio map automatically by mapping signal data acquired from users to the reference point created on each edge. Since the proposed method collects signal data manually only at the vertex of the graph to build the initial radio map and updates it automatically, our proposed method can dramatically reduce labor and time effort, which are the disadvantages of the conventional fingerprinting method. In our experimental study, we show validity of our radio map update method by comparing with the actual reference point data. We also show that our proposed method is able to construct the radio map with an accuracy of about 3.5m by automatically updating the radio map.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2011.02a
• /
• pp.36-36
• /
• 2011

반도체 공정 신호는 주기 신호와 비주기 신호로 구분된다. 특정 패턴을 가지는 주기 신호는 해당 파라미터(parameter)에 대해서 패턴 매칭을 수행하여 관리하는 연구가 진행되고 있다. 반면 비주기 신호 데이터의 경우에는 패턴 매칭 방법을 수행할 수 없다. 또한 반도체 공정에서 얻을 수 있는 두 개 타입의 데이터는 그 파라미터가 방대하기 때문에 현재 실제 공정에 적용되고 있는 방식인 각각 하나의 파라미터에 대해 관리도(control chart)를 구성해 관리하는 것은 많은 비용과 시간의 낭비를 초래한다. 따라서 두 타입 데이터의 여러 개의 파라미터를 동시에 관측할 수 있고 파라미터간의 내재된 상관관계를 고려할 수 있는 장점을 가진 분석 기법에 대한 연구가 필요하다. 주기 신호의 이상탐지를 위한 기존 연구는 신호를 구간으로 나누어 구간별로 SPC 차트적용 시키는 방법, 각 시점 마다 측정되는 값을 하나의 변수로 고려하여 Hotelling's T square, PCA, PLS 등과 같은 다변량 통계 분석을 적용 시키는 방법들이 제시되어 왔다. 이러한 방법들은 다양한 특성을 가지는 주기신호를 분석하고 이상을 탐지 하는데 많은 한계점을 가진다. 이에 본 논문은 다양한 형태를 가지는 신호의 특성을 반영하여 자기구상지도를 기반으로 신호의 분류와 공정의 이상을 탐지하는 기법을 제안한다. 제안하는 기법은 자기구상지도를 이용하여 복잡한(고차원, 시계열) 신호를 2차원 상의 노드로 맵핑시킴으로써 신호의 특질(feature)을 추출하고 새로 표현된 신호의 특질을 기반으로 Logistic regression을 적용시켜 이상을 탐지 한다. 다양한 이상 상황을 가진 반도체 공정 신호를 사용하여 제안한 이상탐지 성능을 평가하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2008.04a
• /
• pp.370-372
• /
• 2008

본 연구에서는 이동 로봇에 영역 센서를 장착하여 실내에서 주변환경을 인식하여 지도를 작성하는 방법을 제안한다. 이동 로봇이 미지의 환경에서 자율 주행하기 위해서는 로봇 환경에 대한 지도를 작성하면서 이 지도 상에서 로봇의 위치를 인식할 수 있어야한다. 지도 작성과 위치 인식을 동시에 수행하는 SLAM을 구현하기위한 준비단계로서 본 논문에서는 일정한 시간 간격으로 연속적인 센서 신호들로 부터 동일 특징을 추출하고 이들을 서로 일치시켜서 로봇 이동 및 센서 신호에 불확실성이 있는 경우에도 지도를 작성하는 방법을 연구한다. 실제로 레이저 영역 센서를 장착한 이동 로봇을 이용하여 실내에서 지도를 작성하는 실험을 통하여 제안된 방법의 성능을 검증한다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38A no.8
• /
• pp.629-637
• /
• 2013

Chaos communication systems have the characteristics such as non-periodic, wide-band, non-predictability of signals and easy implementation. There have been many studies about chaos communication systems because of these advantages. But, chaos communication systems have low BER(Bit Error Rate) compare to general digital communication system. Existing researches on chaos communication systems only analyze BER performance according to various chaos maps. There are no studies on analysis of BER performance according to PDF(Probability Density Function) of chaos maps. In this paper, we analyze the BER performance according to changing parameter, equation, and initial values of chaos map's PDF. In addition, we propose new chaos map to improve BER performance. Simulation results show that BER performance of CDSK(Correlation Delay Shift Keying) is changed when PDF of chaos map changed. And the proposed chaos map has a better BER performance compare to previous chaos maps such as Tent map, Logistic map, and Henon map.

• Journal of Advanced Navigation Technology
• /
• v.11 no.2
• /
• pp.154-162
• /
• 2007

This paper verifies the performance of the wireless-signal map-matching (WSMM) method that is recently proposed to mitigate the effects of non-line-of-sight (NLOS) error in positioning under wireless terrestrial network environments. The WSMM method is the new positioning technology that estimates and compensate the NLOS errors by processing the bulks of anonymous measurements at unknown locations that are collected randomly and automatically. The WSMM method would be advantageous for various configurations of future ubiquitous sensor networks since it is based on the existing network configuration for communication and it requires no additional hardware in base stations and mobile handsets. It is shown that the application of the WSMM concept to the real CDMA pilot strength measurment message (PSMM) actually mitigates the NLOS error effects and improves overall positioning accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.461-462
• /
• 2016

IPS 측위는 GPS음영 지역인 실내의 특정 위치 정보를 판단하는 시스템으로 현재 위치에서 발생되는 신호 정보를 수집하는 시스템과 이 신호들로 구성된 실내 측위 지도, 측위 위치를 결정하기 위한 알고리즘 등에 따라 여러 종류로 나누어진다. 대표적인 IPS로 2.4Ghz, 5.0GHz 대역의 무선 신호(WiFi, BLE, Sensor Network, etc)를 활용하는 RF신호 기반 WPS 등이 있다. RF 신호를 기반으로 하는 실내 측위는 발생 기기의 고장, 장애물 발생, 채널 간섭 현상 등으로 인해 측위 시점 수집된 신호와 구축된 지도의 신호 정보가 달라 측위 정확도가 낮아지는 경우가 발생한다. 본 논문에서는 앞서 언급한 문제점을 해결하기 위해 기존 RF 환경을 사용하는 IPS 방안에 대하여 분석한다. 또한 RF 이외의 실내 측위 기술들에 대해서도 설명하고 측위 정확도를 위해 단일 측위 방식이 아닌 복합 측위 방식에 대한 설계를 제안한다.

• KIISE Transactions on Computing Practices
• /
• v.23 no.2
• /
• pp.110-115
• /
• 2017

We propose a new indoor positioning algorithm named Cut-off algorithm. This algorithm cuts off candidates of beacons and reference points in advance, before looking for K neighbor reference points which are guessed to be closest to the user's actual location. The algorithm consists of two phases: off-line phase, and on-line phase. In the off-line phase, RSSI and UUID data from beacons are gathered at reference points placed in the indoor environment, and construct a fingerprint map of the data. In the on-line phase, the map is reduced to a smaller one according to the RSSI data of beacons received from the user's device. The nearest K reference points are selected using the reduced map, which are used for estimating user's location. In both phases, relative ranks of the peak signals received from each beacon are used, which smoothen the fluctuations of the signals. The algorithm is shown to be more efficient in terms of accuracy and estimating time.

• Journal of the Institute of Convergence Signal Processing
• /
• v.3 no.4
• /
• pp.7-16
• /
• 2002

En this paper, we propose the algorithm that has analyzed the map Information automatically to extract the contour lines and numbers, symbols from the map image. After converting the input image to binary one, thinned image is obtained by thinning algorithm. The contour elements in the thinned image are classified and the classified elements are analyzed to automatically classify the numbers from symbols. Finally, the broken parts are restored by reconstruction algorithm. The performance of proposed algorithm is verified through the simulation. The proposed one has good performance.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.7
• /
• pp.898-903
• /
• 2020

In this paper, we propose an indoor logistic tracking system that identifies the location and inventory of the logistics in the room based on fingerprints. Through this, we constructed the actual infrastructure of the logistics center and designed and implemented the logistics management system. The proposed system collects the signal strength through the location terminal and generates the signal map to locate the goods. The location terminal is composed of a UHF RFID reader and a wireless LAN card, reads the peripheral RFID signal and the signal of the wireless AP, and transmits it to the web server. The web server processes the signal received from the location terminal and stores it in the database, and the user uses the data to produce the signal map. The proposed system combines UHF RFID with existing fingerprinting method to improve performance in the environment of querying multiple objects.