Mapping Techniques for UWB Positioning

This paper deals with a wireless indoor positioning problem in which the location of a tag is estimated from range measurements taken by fixed beacons. The measurements may be affected by non-line-of-sight (NLOS) errors that must be mitigated. We discuss a maximum likelihood (ML) positioning technique that assumes a realistic model for the range errors and a signature database providing information on the propagation conditions at every hypothesized tag spot. The database can be gathered from knowledge of the service area infrastructure and through pre-measurements. It is given in the form of a map indicating, at any node of a close-mesh grid, the nature (LOS/NLOS) of the link between that node and each beacon. The performance of the positioning algorithm is assessed by simulation and is compared with other methods available in literature. The results show that the proposed technique provides significant improvements and is robust against mismatches between true and assumed values of the parameters in the range error model. Comparisons with the Cramer-Rao Bound are made.