DC Field | Value | Language |
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dc.contributor.advisor | Han, Dong-Soo | - |
dc.contributor.advisor | 한동수 | - |
dc.contributor.author | Lee, Sang-Jae | - |
dc.contributor.author | 이상재 | - |
dc.date.accessioned | 2013-09-12T01:49:24Z | - |
dc.date.available | 2013-09-12T01:49:24Z | - |
dc.date.issued | 2012 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=509483&flag=dissertation | - |
dc.identifier.uri | http://hdl.handle.net/10203/180467 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 전산학과, 2012.8, [ iv, 33 p. ] | - |
dc.description.abstract | Although WiFi fingerprint based localization can achieve better accuracy than triangulation, it still suffers from accuracy uctuation problem. As a result, many filtering techniques have been developed to mitigate the uctuation of localization accuracy mainly focused on the post-processing stage of a localization engine. Kalman filter, delay filter, map matching are such filtering techniques adopted and used in both indoor and outdoor environments. However little work has been found for the pre-processing stage of a localization engine. But in fact the pre-processing such as imputing missing signals of a captured WiFi fingerprint can bring us as much effect as we can get through post processing performed by location filters. In WiFi fingerprint based localization, a WiFi radio map (WRM) is constructed in advance and then a location for a captured WiFi fingerprint is estimated based on the WRM. Since we usually collect WiFi fingerprints many times at a location, and then compute their average WiFi fingerprint for the construction of WRM, almost all of the WiFi signals accessible at the location are included in the constructed WRM. On the other hand, a WiFi fingerprint captured at a location in online phase for localization inevitably has missing WiFi signals because it is obtained by scanning WiFi signals just once or twice. Thus, if we estimate a location with the captured fingerprint without padding or imputation of the missing signal, we cannot expect to achieve high localization accuracy. In this paper we propose a technique to enhance the accuracy of WiFi-fingerprint based localization by imputing missing signals of WiFi fingerprints. There can be many different ways of imputing or handling missing signals. For example, we can use a predefined value instead for missing signals or we can even disregard the missing signals for localization. In this paper we develop two techniques for this; one is to impute missing signals by referring to the WRM fingerprint at the very previo... | eng |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Indoor localization | - |
dc.subject | imputation | - |
dc.subject | missing signal | - |
dc.subject | RSS | - |
dc.subject | 실내측위 | - |
dc.subject | 대체기법 | - |
dc.subject | 손실신호 | - |
dc.subject | 라디오맵 | - |
dc.subject | 수신신호강도 | - |
dc.subject | radio map | - |
dc.title | Missing signal imputation for accurate WLAN-based indoor localization system | - |
dc.title.alternative | 무선랜 기반 실내 측위 정확도 향상을 위한 손실 신호 대체 기법 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 509483/325007 | - |
dc.description.department | 한국과학기술원 : 전산학과, | - |
dc.identifier.uid | 020104382 | - |
dc.contributor.localauthor | Han, Dong-Soo | - |
dc.contributor.localauthor | 한동수 | - |
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