A Flexible Distributed Maximum Log-Likelihood Scheme for UWB Indoor Positioning

In this paper, we show that the distributed maximum log-likelihood (DMLL) algorithm, which was originally proposed in (Denis, 2005) as a positioning solution for ultra wideband (UWB) indoor ad hoc networks, exhibits fine flexibility. Indeed, distinct implementation options are offered regarding the integration of range measurements or the distribution of required calculi. One important point is the use of synergetic cooperative protocol transactions that can handle simultaneously ranging, local contributions to the iterative optimization of a global objective, as well as the exchange of positional information. In addition, depending on the retained underlying models and the amount of prior statistical information, either a "blind" approach or more advanced options (e.g. aided by a preliminary channel identification step) could be adopted within a unique generic framework. This algorithm also proves to mitigate the harmful effects of non line of sight (NLOS) ranging biases by incorporating refined time of arrival (TOA) models. Finally, it claims to benefit from redundancy and spatial diversity as network completeness increases. At first, we make a short description of possible algorithmic embodiments. Then, we provide new simulation results obtained under realistic indoor scenarios with various ranging models. Subsequently, we discuss the impact of a few critical parameters on positioning precision and/or reliability.