DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Chung, Yeonseung | - |
dc.contributor.advisor | 정연승 | - |
dc.contributor.advisor | Kim, Sung-Ho | - |
dc.contributor.advisor | 김성호 | - |
dc.contributor.author | Yoon, Wansang | - |
dc.date.accessioned | 2021-05-11T19:43:43Z | - |
dc.date.available | 2021-05-11T19:43:43Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=907849&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/283578 | - |
dc.description | 학위논문(박사) - 한국과학기술원 : 수리과학과, 2020.2,[iv, 51 p. :] | - |
dc.description.abstract | In target tracking problem, two important considerations for estimating the position of the target are firstly the optimal formation of sensors that receive the target information and secondly the estimation method based on the received information. In this thesis we studied target localization problem based on the time difference of arrival (TDOA) data. This thesis propose two methods to improve the performance of the target tracking problem. In the first part, we discussed the optimal sensor formation problem in terms of Fisher information. The estimators of the target location expressed in terms of the spherical coordinates are found to be uncorrelated when the sensors are arranged in a concentric ring formation. The proposed optimal formation of sensors is in the concentric ring formation and is shown to change in accordance with sensors' angular positions with respect to the line-of-sight vector from the reference sensor to the target. In the second part, we present a estimation method for the linear state space model with an unknown measurement matrix using a Bayesian method. We explored availability of the Bayes method for parameter estimation with no constraints on the parameter space and found that the estimation for the state vector is acceptable as long as the priors are not vague on both the state and the measurement matrix. We also investigated the model where the measurement matrix is contaminated with noise and found that the estimates for the state vector were more accurate than those by the methods in literature. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Adaptive sensor arrangement▼aFisher information▼aMean squared error▼aRing formation▼aBayes estimation▼aGibbs sampling▼aKalman filter | - |
dc.subject | 적응형 센서 배열▼a피셔 정보량▼a평균 제곱 오차▼a고리 대형▼a베이즈 추정▼a깁스 샘플링▼a칼만 필터 | - |
dc.title | (A) study on target localization problem based on time difference of arrival data | - |
dc.title.alternative | TDOA 자료 기반의 목표위치 추정문제에 관한 연구 | - |
dc.type | Thesis(Ph.D) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :수리과학과, | - |
dc.contributor.alternativeauthor | 윤완상 | - |
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