Analysis of Opportunistic Localization Algorithms Based on the Linear Matrix Inequality Method

With the increasing spread of use of mobile devices there is a growing demand for location-aware services in a wide variety of contexts. Yet providing an accurate location estimation is difficult when considering cheap off-the-shelf mobile devices, particularly in indoors or urban environments. In this paper we define and compare different localization algorithms based on an opportunistic paradigm. In particular, we focus on range-free and range-based localization techniques that are based on the solution of a Linear Matrix Inequalities (LMI) problem. The performance achievable with this approach is analyzed in different scenarios, through extensive simulation campaign. Results show that LMI-based schemes, especially the range-based one, are potentially capable of yielding very accurate localization even after a limited number of opportunistic exchange, though performance is rather sensitive to the accuracy of the other nodes' self-localization and to the randomness of the radio channel.