Chipless RFID Tags Placement Optimization as Infrastructure for Maximal Localization Coverage

Indoor localization based on asynchronous and chipless radio frequency identification (RFID) infrastructure has a wide potential for real-world emerging applications like simultaneous localization and mapping (SLAM) systems and mobile material characterization transceivers. Effective deployment of chipless tags within the indoor environment as infrastructure plays an important role to attain connectivity between the infrastructure and the objects of interest at any time and position in the room. As an example, assuming an indoor localization system, a moving or flying robot should be connected to
$k$
reference chipless tags in order to enable self-localization. From system design point of view, the reference tags should be deployed in the room to guarantee that each point in the room is covered by at least
$k$
tags, which is denoted as 3D
$k$
-coverage. In this paper, we propose to formulate the reference chipless tags placement as a binary integer programming to ensure achieving 3D
$k$
-coverage with the minimum number of tags considering system and propagation constraints. Since mm-localization accuracy could be prevailed at Terahertz (THz) band, the optimization problem considers the chipless tags limited distance and angle coverage at this band as optimization constraints. Since discretization of the optimization domain might cause blank areas that are not covered, we propose an iterative method aiming at filling those blank areas and assuring their
$k$
-coverage. Performance evaluation is performed to examine the performance of the proposed algorithms. Results show that the proposed algorithms achieve desirable performance by promoting 3D
$k$
-coverage with minimum number of tags.