Noise reduction for variance-based radio tomographic localization

We propose to demonstrate a new radio tomographic localization algorithm - subspace variance-based radio tomography (SubVRT), which is more robust to RSS variations caused by objects that are intrinsic parts of the environment. We first introduce the subspace decomposition method, then we derive the formulations of SubVRT, and finally we describe the demonstration setup, requirements and procedures.