Accuracy vs. Resolution in Radio Tomography

Radio tomographic imaging (RTI) has recently been proposed for tracking object location via radio waves without requiring the objects to transmit or receive radio signals. The position is extracted by inferring which voxels are obstructing the various radio links in a dense wireless sensor network. This paper derives an analytic expression for the image accuracy (error per voxel) for each of 5 published RTI system models. The formulae show the effects of weight model choice, voxel size, number of sensors, and degree of regularization on the Cramér-Rao Lower Bound (CRLB). This enables analysis of the tradeoffs between these parameters in system design, particularly between image accuracy and image resolution. The theoretical results agree well with simulations, and the new theory is used to interpret an experimental scenario.