Name
Title | ||
|---|---|---|
Maximum Likelihood Indoor Localization of a WiFi Radio Transmitter with Structural Knowledge. |
Abstract | ||
|---|---|---|
In this paper, we present a method for estimating the location of a WiFi transmitter by a receiver using the radio resource and knowledge of the indoor room structure. We derive a three-ray path propagation model for the received radio signal in a known indoor environment. We show that the position of the transmitter could be localized using the received radio signal measurements. The likelihood under this model exhibits multiple local peaks when only few frequencies are used, which leads to the location ambiguities under the Maximum Likelihood criterion. We observed in simulation that the ambiguous locations under the Maximum Likelihood estimation vary with the WiFi radio frequency used but the ground truth location is always presented as a peak. Therefore, we use multiple WiFi frequency bands to resolve the localization ambiguity. A subspace based method is applied in combination with Maximum Likelihood method utilizing the same set of measurements to improve localization efficiency. Simulation using commercial ray tracing software presents promising result. |
Year | Venue | Field |
|---|---|---|
2017 | ICSPS | Transmitter,Subspace topology,Ray tracing (graphics),Computer science,Algorithm,Radio frequency,Ground truth,Software,Ambiguity,Radio spectrum |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
4 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuai Sun | 1 | 0 | 0.34 |
| Xuezhi Wang | 2 | 94 | 10.88 |
| B. Moran | 3 | 111 | 21.09 |
| Akram Al-Hourani | 4 | 468 | 33.31 |
| Wayne S T Rowe | 5 | 1 | 2.40 |