Optimized super-resolution ranging over ToA measurements

We propose a new accurate ranging algorithm for Time of arrival (ToA)-based wireless network localization. Although many works have been done in the current literature to optimize localization and tracking algorithms, the mitigation of ranging errors is still a very challenging problem. To this end, we combine and optimize two well-known super-resolution algorithms such as Music and Root-Music, commonly used in the estimation of the direction of arrival of incoming signal sources of a linear antenna array, with the powerful mathematical notion of a Golomb Ruler. The results are proved to be tremendously efficient and to almost reach the fundamental localization limits depicted by the Cramér-Rao lower bound (CRLB).