Location estimation in Wi-Fi environment has gained considerable attention over the past years, and the Cramer-Rao Lower Bound (CRLB) can be used to evaluate the performance of the localization system. In this paper, we analyze the CRLB of Wi- Fi indoor localization using fingerprint and assistant nodes. This localization method combines received signal strength (RSS) and Time of Arrival (TOA) into together, and constructs a fixed spatial model with several assistant nodes to improve localization performance. There are two purposes of the CRLB analysis framework proposed in this paper. Firstly, the expression of lower bound on location estimation error can help in designing and refining efficient localization algorithm and parameters. Secondly, the error trends can provide suggestions for a positioning system design and deployment. Furthermore, detailed analysis as well as experimental results are both presented in this paper.
Cramér-Rao Bound Analysis of Wi-Fi Indoor Localization Using Fingerprint and Assistant Nodes
2017-09-01
1523989 byte
Conference paper
Electronic Resource
English
Cramér–Rao Lower Bound Analysis for Elliptic Localization With Random Sensor Placements
IEEE | 2024
|AIAA | 2015
|