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지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학위논문
- 저자정보
- 지도교수
- 김윤학
- 발행연도
- 2019
- 저작권
- 조선대학교 논문은 저작권에 의해 보호받습니다.
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초록· 키워드
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In this thesis, we study two algorithms for the sequence-based localization
(SBL) systems which have been recently used for in-door positioning.
The first is the node deployment algorithm for SBL systems. The existing node
selection/deployment algorithms seek to place nodes in the centroid of the area
where more targets can be found. However, it is observed that the boundaries
separating these areas might be appropriate for node locations in SBL systems.
From this observation, we propose an efficient node deployment algorithm that
determines boundaries using K-means clustering and finds potential node
locations based on the bisection method for a low complexity design. The second
is a low-complexity algorithm that allows us to design quantizers at sensor
nodes by using the reduced number of training samples which are obtained from
distance samples between targets and centroids, each centroid assigned to one of
the sequences constructed by localization process in SBL systems. In addition,
we further improve performance of the design algorithm by generating more
training samples for the sequences with higher probability. We demonstrate
through experiments that the proposed algorithms for node deployment and
quantizer design at local nodes for SBL systems show a significant performance
gain as compared with typical and previous designs.
(SBL) systems which have been recently used for in-door positioning.
The first is the node deployment algorithm for SBL systems. The existing node
selection/deployment algorithms seek to place nodes in the centroid of the area
where more targets can be found. However, it is observed that the boundaries
separating these areas might be appropriate for node locations in SBL systems.
From this observation, we propose an efficient node deployment algorithm that
determines boundaries using K-means clustering and finds potential node
locations based on the bisection method for a low complexity design. The second
is a low-complexity algorithm that allows us to design quantizers at sensor
nodes by using the reduced number of training samples which are obtained from
distance samples between targets and centroids, each centroid assigned to one of
the sequences constructed by localization process in SBL systems. In addition,
we further improve performance of the design algorithm by generating more
training samples for the sequences with higher probability. We demonstrate
through experiments that the proposed algorithms for node deployment and
quantizer design at local nodes for SBL systems show a significant performance
gain as compared with typical and previous designs.
목차
목 차도 목 차 ………………………………………………………………………………… ⅱABSTRACT ………………………………………………………………………………… ⅲ제1장 서 론 …………………………………………………………………………… 1제2장 위치추정 시스템 ……………………………………………………… 4제1절 시퀀스 기반 위치추정 시스템 …………………………………… 5 제3장 노드 배치 알고리즘 ………………………………………………… 6제1절 제안 노드 배치 알고리즘 …………………………………………… 91. 노드 배치를 위한 가이드라인 결정 ………………………………… 92. 노드 위치 선택 ………………………………………………………… 11제2절 시뮬레이션 ………………………………………………………………… 13제4장 양자기 설계 알고리즘 …………………………………………… 18제1절 제안 양자기 설계 알고리즘 ……………………………………… 191. 표본 추출 및 시스템 복잡도 감소 (SBL Q #1) ……………… 192. 위치할 확률을 고려한 표본 추출 (SBL Q #2) ………………… 203. 검색 알고리즘 ……………………………………………………………… 21제2절 시뮬레이션 ………………………………………………………………… 23제5장 결 론 …………………………………………………………………………… 29Reference ……………………………………………………………………………… 30
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