1- https://doi.org/10.1007/978-3-319-42836-9_27
Performance Analysis for High Dimensional Non-parametric Estimation in Complicated Indoor Localization
- Jan 1, 2016
- Yubin Zhao +2 more
In this paper, we propose an extended recursive Cramer-Rao lower bound (ER-CRLB) method as a fundamental tool to analyze the performance of wireless indoor localization systems. According to the non-parametric estimation method, the Fisher information matrix of the ER-CRLB is divided into two parts: the state matrix and the auxiliary matrix, which builds a general framework to consider all the possible factors that may influence the estimation performance. Based on this idea, ER-CRLB can fully model the estimation process in the complicated indoor environment, e.g., the sequential position state propagation, target-anchor geometry effect, the NLOS identification, and the related prior information, which are demonstrated in the comprehensive simulations.
- # Complicated Indoor Environment
- # NLOS Identification
- # Complicated Indoor
- # Auxiliary Matrix
- # State Matrix
- # Indoor Localization
- # Comprehensive Simulations
- # Non-parametric Estimation
- # Performance Of Wireless Systems
- # High Dimensional Estimation
