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A Signal Detection of Minimum Variance Algorithm on Linear Constraints
국제인공지능학회(구 한국인터넷방송통신학회) International Journal of Internet, Broadcasting and Communication Vol.15 No.3 2023.08 pp.8-13
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
We propose a method for removing interference and noise to estimate target information. In wireless channels, information signals are subject to interference and noise, making it is difficult to accurately estimate the desired signal. To estimate the desired information signal, it is essential to remove the noise and interference from the received signal, extracting only the desired signal. If the received signal noise and interference are not removed, the estimated information signal will have a large error in distance and direction, and the exact location of the target cannot be estimated. This study aims to accurately estimate the desired target in space. The objective is to achieve more presice target estimation than existing methods and enhance target resolution.An estimation method is proposed to improve the accuracy of target estimation. The proposed target estimation method obtains optimal weights using linear constraints and the minimum variance method. Through simulation, the performance of the proposed method and the existing method is analyzed. The proposed method successfully estimated all four targets, while the existing method only estimated two targets. The results show that the proposed method has better resolutiopn and superior estimation capability than the existing method.
최소 분산법을 이용한 GRIN 렌즈의 굴절률 측정에 관한 연구
[Kisti 연계] 한국광학회 한국광학회 학술대회논문집 2009 pp.143-144
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