Robust time-of-arrival source localization employing error covariance of sample mean and sample median in line-of-sight/non-line-of-sight mixture environmentsopen access
- Authors
- Park, Chee-Hyun; Chang, Joon-Hyuk
- Issue Date
- Aug-2016
- Publisher
- SPRINGEROPEN
- Keywords
- Adaptive selection; Loss function; Sample mean; Sample median; Statistical testing; Error variance
- Citation
- EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING
- Indexed
- SCIE
SCOPUS
- Journal Title
- EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/22288
- DOI
- 10.1186/s13634-016-0385-4
- ISSN
- 1687-6180
- Abstract
- We propose a line-of-sight (LOS)/non-line-of-sight (NLOS) mixture source localization algorithm that utilizes the weighted least squares (WLS) method in LOS/NLOS mixture environments, where the weight matrix is determined in the algebraic form. Unless the contamination ratio exceeds 50 %, the asymptotic variance of the sample median can be approximately related to that of the sample mean. Based on this observation, we use the error covariance matrix for the sample mean and median to minimize the weighted squared error (WSE) loss function. The WSE loss function based on the sample median is utilized when statistical testing supports the LOS/NLOS state, while the WSE function using the sample mean is employed when statistical testing indicates that the sensor is in the LOS state. To testify the superiority of the proposed methods, the mean square error (MSE) performances are compared via simulation.
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