Multiple-source localization using line-of-bearing measurements: Approaches to the data association problem

In this paper, we consider the data association problem of multiple-source localization using line-of-bearing measurements. More specifically, we propose two approaches that circumvent the very high complexity of a brute-force solution to this problem. The first approach relies on statistical clustering of the intersections of line-of-bearing measurements and the second approach exploits cyclostationary features of the received signals to allow for line-of-bearing measurement separation based on each signalpsilas transmission modes. These two proposed approaches have reduced time and computational complexity, while maintaining a reasonable amount of accuracy, and are of great value for dense environments with large numbers of sensors and/or targets.