Multi-frequency sub-1 GHz radio tomographic imaging in a complex indoor environment

Abstract

Unlike most currently available localization systems, tagless localization technologies do not require a target to wear a passive or active hardware device. Radio Tomographic Imaging (RTI) is one such technique, which operates based on the use of a tomographic radio frequency (RF) sensor network. The majority of RTI-systems communicate using a single frequency band: 2.4 GHz. The use of sub-1 GHz frequencies within RTI could potentially provide important benefits regarding energy efficiency, accuracy in complex indoor environments and size of the environments in which a system can be installed. We deployed a combined 433 MHz and 868 MHz RF sensor network in a complex indoor environment and performed localization when a human individual was present in the environment. Two different RTI-algorithms were investigated: a Bayesian-based method we developed earlier and an adaptation of an existing 2.4 GHz technique based on fade level. Both methods turned out to be capable of accurately locating individuals with a median error lower than 1 meter. This proves the feasibility of using a combination of sub-1 GHz frequencies in RTI for indoor localization in complex environments.