The position accuracy of the traditional fingerprint-based
localization algorithm depends on the accuracy of the matching
algorithm and fingerprint databases. However, in complex
indoor environments impacted by signal reflection,
refraction, and obstacles, RSS value has a greater error due
to large fluctuation, which seriously affects the fingerprint
database’s accuracy. Nevertheless, traditional localization
algorithms only utilize single node while neglecting other
indoor nodes’ information. In fact, current indoor environments
(e.g., offices, shopping malls) are filled with Wi-Fi
devices. Therefore, our intuition is that these Wi-Fi devices’
information may be used to improve positional accuracy; they
can be considered assistant nodes. Hence this paper proposes
a novel Wi-Fi indoor localization algorithm based on the
collaboration of RSS and assistant nodes.