Empirical Evaluation of Wireless Localization when Using Multiple Antennas

We show that signal strength variability can be reduced by employing multiple low-cost antennas at fixed locations. We further explore the impact of this reduction on wireless localization by analyzing a representative set of algorithms ranging from fingerprint matching, to statistical maximum likelihood estimation, to threshold bounding of signal fingerprints, and to multilateration. Using an indoor wireless testbed, we provide experimental evaluation of the localization performance under multiple antennas. We found that in nearly all cases the performance of localization algorithms improved when using multiple antennas. Specifically, the median and the 90th percentile error can be reduced up to 70 percent. Additionally, we found that multiple antennas improve the localization stability significantly, up to 100 percent improvement, when there are small-scale three-dimensional movements of a mobile device around a given location.