A Support Vector Data Description Approach to NLOS Identification in UWB Positioning

Abstract

Non-line-of-sight (NLOS) propagation is one of the most important challenges in radio positioning, and, in recent years, significant attention has been drawn to the identification and mitigation of NLOS signals. This paper focuses on the identification of NLOS signals. The authors consider the NLOS identification problem as a one-class classification problem and apply the support vector data description (SVDD), providing accurate data descriptions utilizing kernel techniques, to perform NLOS identification in ultrawide bandwidth (UWB) positioning. Our work is based on the fact that some features extracted from the received signal waveforms, such as the kurtosis, the mean excess delay spread, and the root mean square delay spread, are different between line-of-sight (LOS) and NLOS signals. Numerical simulations are performed to demonstrate the performance, using a dataset derived from a measurement campaign.